program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}, {"coremltools-component-torch", "2.5.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.3.0"}})]
{
    func main<ios17>(tensor<fp32, [1, ?, 80]> feats) [FlexibleShapeInformation = tuple<tuple<tensor<string, []>, dict<tensor<string, []>, tensor<int32, [?]>>>, tuple<tensor<string, []>, dict<tensor<string, []>, list<tensor<int32, [2]>, ?>>>>((("DefaultShapes", {{"feats", [1, 400, 80]}}), ("RangeDims", {{"feats", [[1, 1], [64, 6000], [80, 80]]}})))] {
            tensor<int32, []> var_3 = const()[name = tensor<string, []>("op_3"), val = tensor<int32, []>(100)];
            tensor<int32, []> var_4 = const()[name = tensor<string, []>("op_4"), val = tensor<int32, []>(-1)];
            tensor<int32, []> var_11 = const()[name = tensor<string, []>("op_11"), val = tensor<int32, []>(1)];
            tensor<int32, [3]> var_16 = const()[name = tensor<string, []>("op_16"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> feats_to_fp16_dtype_0 = const()[name = tensor<string, []>("feats_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<int32, [1]> input_1_axes_0 = const()[name = tensor<string, []>("input_1_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, ?, 80]> feats_to_fp16 = cast(dtype = feats_to_fp16_dtype_0, x = feats)[name = tensor<string, []>("cast_316")];
            tensor<fp16, [1, 80, ?]> x_1_cast_fp16 = transpose(perm = var_16, x = feats_to_fp16)[name = tensor<string, []>("transpose_0")];
            tensor<fp16, [1, 1, 80, ?]> input_1_cast_fp16 = expand_dims(axes = input_1_axes_0, x = x_1_cast_fp16)[name = tensor<string, []>("input_1_cast_fp16")];
            tensor<string, []> input_3_pad_type_0 = const()[name = tensor<string, []>("input_3_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_3_pad_0 = const()[name = tensor<string, []>("input_3_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_3_strides_0 = const()[name = tensor<string, []>("input_3_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_3_dilations_0 = const()[name = tensor<string, []>("input_3_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_3_groups_0 = const()[name = tensor<string, []>("input_3_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 1, 3, 3]> const_0_to_fp16 = const()[name = tensor<string, []>("const_0_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp16, [32]> const_1_to_fp16 = const()[name = tensor<string, []>("const_1_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(704)))];
            tensor<fp16, [1, 32, 80, ?]> input_5_cast_fp16 = conv(bias = const_1_to_fp16, dilations = input_3_dilations_0, groups = input_3_groups_0, pad = input_3_pad_0, pad_type = input_3_pad_type_0, strides = input_3_strides_0, weight = const_0_to_fp16, x = input_1_cast_fp16)[name = tensor<string, []>("input_5_cast_fp16")];
            tensor<fp16, [1, 32, 80, ?]> input_7_cast_fp16 = relu(x = input_5_cast_fp16)[name = tensor<string, []>("input_7_cast_fp16")];
            tensor<string, []> input_9_pad_type_0 = const()[name = tensor<string, []>("input_9_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_9_pad_0 = const()[name = tensor<string, []>("input_9_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_9_strides_0 = const()[name = tensor<string, []>("input_9_strides_0"), val = tensor<int32, [2]>([2, 1])];
            tensor<int32, [2]> input_9_dilations_0 = const()[name = tensor<string, []>("input_9_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_9_groups_0 = const()[name = tensor<string, []>("input_9_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 32, 3, 3]> const_2_to_fp16 = const()[name = tensor<string, []>("const_2_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(832)))];
            tensor<fp16, [32]> const_3_to_fp16 = const()[name = tensor<string, []>("const_3_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19328)))];
            tensor<fp16, [1, 32, 40, ?]> input_11_cast_fp16 = conv(bias = const_3_to_fp16, dilations = input_9_dilations_0, groups = input_9_groups_0, pad = input_9_pad_0, pad_type = input_9_pad_type_0, strides = input_9_strides_0, weight = const_2_to_fp16, x = input_7_cast_fp16)[name = tensor<string, []>("input_11_cast_fp16")];
            tensor<fp16, [1, 32, 40, ?]> input_13_cast_fp16 = relu(x = input_11_cast_fp16)[name = tensor<string, []>("input_13_cast_fp16")];
            tensor<string, []> input_15_pad_type_0 = const()[name = tensor<string, []>("input_15_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_15_pad_0 = const()[name = tensor<string, []>("input_15_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_15_strides_0 = const()[name = tensor<string, []>("input_15_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_15_dilations_0 = const()[name = tensor<string, []>("input_15_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_15_groups_0 = const()[name = tensor<string, []>("input_15_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 32, 3, 3]> const_4_to_fp16 = const()[name = tensor<string, []>("const_4_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(19456)))];
            tensor<fp16, [32]> const_5_to_fp16 = const()[name = tensor<string, []>("const_5_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37952)))];
            tensor<fp16, [1, 32, 40, ?]> out_1_cast_fp16 = conv(bias = const_5_to_fp16, dilations = input_15_dilations_0, groups = input_15_groups_0, pad = input_15_pad_0, pad_type = input_15_pad_type_0, strides = input_15_strides_0, weight = const_4_to_fp16, x = input_13_cast_fp16)[name = tensor<string, []>("out_1_cast_fp16")];
            tensor<string, []> input_17_pad_type_0 = const()[name = tensor<string, []>("input_17_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> input_17_strides_0 = const()[name = tensor<string, []>("input_17_strides_0"), val = tensor<int32, [2]>([2, 1])];
            tensor<int32, [4]> input_17_pad_0 = const()[name = tensor<string, []>("input_17_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_17_dilations_0 = const()[name = tensor<string, []>("input_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_17_groups_0 = const()[name = tensor<string, []>("input_17_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 32, 1, 1]> const_6_to_fp16 = const()[name = tensor<string, []>("const_6_to_fp16"), val = tensor<fp16, [32, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38080)))];
            tensor<fp16, [32]> const_7_to_fp16 = const()[name = tensor<string, []>("const_7_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40192)))];
            tensor<fp16, [1, 32, 40, ?]> var_79_cast_fp16 = conv(bias = const_7_to_fp16, dilations = input_17_dilations_0, groups = input_17_groups_0, pad = input_17_pad_0, pad_type = input_17_pad_type_0, strides = input_17_strides_0, weight = const_6_to_fp16, x = input_7_cast_fp16)[name = tensor<string, []>("op_79_cast_fp16")];
            tensor<fp16, [1, 32, 40, ?]> input_19_cast_fp16 = add(x = out_1_cast_fp16, y = var_79_cast_fp16)[name = tensor<string, []>("input_19_cast_fp16")];
            tensor<fp16, [1, 32, 40, ?]> input_21_cast_fp16 = relu(x = input_19_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")];
            tensor<string, []> input_23_pad_type_0 = const()[name = tensor<string, []>("input_23_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_23_pad_0 = const()[name = tensor<string, []>("input_23_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_23_strides_0 = const()[name = tensor<string, []>("input_23_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_23_dilations_0 = const()[name = tensor<string, []>("input_23_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_23_groups_0 = const()[name = tensor<string, []>("input_23_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 32, 3, 3]> const_8_to_fp16 = const()[name = tensor<string, []>("const_8_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40320)))];
            tensor<fp16, [32]> const_9_to_fp16 = const()[name = tensor<string, []>("const_9_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58816)))];
            tensor<fp16, [1, 32, 40, ?]> input_25_cast_fp16 = conv(bias = const_9_to_fp16, dilations = input_23_dilations_0, groups = input_23_groups_0, pad = input_23_pad_0, pad_type = input_23_pad_type_0, strides = input_23_strides_0, weight = const_8_to_fp16, x = input_21_cast_fp16)[name = tensor<string, []>("input_25_cast_fp16")];
            tensor<fp16, [1, 32, 40, ?]> input_27_cast_fp16 = relu(x = input_25_cast_fp16)[name = tensor<string, []>("input_27_cast_fp16")];
            tensor<string, []> input_29_pad_type_0 = const()[name = tensor<string, []>("input_29_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_29_pad_0 = const()[name = tensor<string, []>("input_29_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_29_strides_0 = const()[name = tensor<string, []>("input_29_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_29_dilations_0 = const()[name = tensor<string, []>("input_29_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_29_groups_0 = const()[name = tensor<string, []>("input_29_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 32, 3, 3]> const_10_to_fp16 = const()[name = tensor<string, []>("const_10_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58944)))];
            tensor<fp16, [32]> const_11_to_fp16 = const()[name = tensor<string, []>("const_11_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77440)))];
            tensor<fp16, [1, 32, 40, ?]> out_3_cast_fp16 = conv(bias = const_11_to_fp16, dilations = input_29_dilations_0, groups = input_29_groups_0, pad = input_29_pad_0, pad_type = input_29_pad_type_0, strides = input_29_strides_0, weight = const_10_to_fp16, x = input_27_cast_fp16)[name = tensor<string, []>("out_3_cast_fp16")];
            tensor<fp16, [1, 32, 40, ?]> input_31_cast_fp16 = add(x = out_3_cast_fp16, y = input_21_cast_fp16)[name = tensor<string, []>("input_31_cast_fp16")];
            tensor<fp16, [1, 32, 40, ?]> input_33_cast_fp16 = relu(x = input_31_cast_fp16)[name = tensor<string, []>("input_33_cast_fp16")];
            tensor<string, []> input_35_pad_type_0 = const()[name = tensor<string, []>("input_35_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_35_pad_0 = const()[name = tensor<string, []>("input_35_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_35_strides_0 = const()[name = tensor<string, []>("input_35_strides_0"), val = tensor<int32, [2]>([2, 1])];
            tensor<int32, [2]> input_35_dilations_0 = const()[name = tensor<string, []>("input_35_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_35_groups_0 = const()[name = tensor<string, []>("input_35_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 32, 3, 3]> const_12_to_fp16 = const()[name = tensor<string, []>("const_12_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77568)))];
            tensor<fp16, [32]> const_13_to_fp16 = const()[name = tensor<string, []>("const_13_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96064)))];
            tensor<fp16, [1, 32, 20, ?]> input_37_cast_fp16 = conv(bias = const_13_to_fp16, dilations = input_35_dilations_0, groups = input_35_groups_0, pad = input_35_pad_0, pad_type = input_35_pad_type_0, strides = input_35_strides_0, weight = const_12_to_fp16, x = input_33_cast_fp16)[name = tensor<string, []>("input_37_cast_fp16")];
            tensor<fp16, [1, 32, 20, ?]> input_39_cast_fp16 = relu(x = input_37_cast_fp16)[name = tensor<string, []>("input_39_cast_fp16")];
            tensor<string, []> input_41_pad_type_0 = const()[name = tensor<string, []>("input_41_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_41_pad_0 = const()[name = tensor<string, []>("input_41_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_41_strides_0 = const()[name = tensor<string, []>("input_41_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_41_dilations_0 = const()[name = tensor<string, []>("input_41_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_41_groups_0 = const()[name = tensor<string, []>("input_41_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 32, 3, 3]> const_14_to_fp16 = const()[name = tensor<string, []>("const_14_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96192)))];
            tensor<fp16, [32]> const_15_to_fp16 = const()[name = tensor<string, []>("const_15_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114688)))];
            tensor<fp16, [1, 32, 20, ?]> out_5_cast_fp16 = conv(bias = const_15_to_fp16, dilations = input_41_dilations_0, groups = input_41_groups_0, pad = input_41_pad_0, pad_type = input_41_pad_type_0, strides = input_41_strides_0, weight = const_14_to_fp16, x = input_39_cast_fp16)[name = tensor<string, []>("out_5_cast_fp16")];
            tensor<string, []> input_43_pad_type_0 = const()[name = tensor<string, []>("input_43_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> input_43_strides_0 = const()[name = tensor<string, []>("input_43_strides_0"), val = tensor<int32, [2]>([2, 1])];
            tensor<int32, [4]> input_43_pad_0 = const()[name = tensor<string, []>("input_43_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            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, [32, 32, 1, 1]> const_16_to_fp16 = const()[name = tensor<string, []>("const_16_to_fp16"), val = tensor<fp16, [32, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114816)))];
            tensor<fp16, [32]> const_17_to_fp16 = const()[name = tensor<string, []>("const_17_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116928)))];
            tensor<fp16, [1, 32, 20, ?]> var_153_cast_fp16 = conv(bias = const_17_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_16_to_fp16, x = input_33_cast_fp16)[name = tensor<string, []>("op_153_cast_fp16")];
            tensor<fp16, [1, 32, 20, ?]> input_45_cast_fp16 = add(x = out_5_cast_fp16, y = var_153_cast_fp16)[name = tensor<string, []>("input_45_cast_fp16")];
            tensor<fp16, [1, 32, 20, ?]> 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, [32, 32, 3, 3]> const_18_to_fp16 = const()[name = tensor<string, []>("const_18_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(117056)))];
            tensor<fp16, [32]> const_19_to_fp16 = const()[name = tensor<string, []>("const_19_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135552)))];
            tensor<fp16, [1, 32, 20, ?]> input_51_cast_fp16 = conv(bias = const_19_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_18_to_fp16, x = input_47_cast_fp16)[name = tensor<string, []>("input_51_cast_fp16")];
            tensor<fp16, [1, 32, 20, ?]> input_53_cast_fp16 = relu(x = input_51_cast_fp16)[name = tensor<string, []>("input_53_cast_fp16")];
            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<fp16, [32, 32, 3, 3]> const_20_to_fp16 = const()[name = tensor<string, []>("const_20_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135680)))];
            tensor<fp16, [32]> const_21_to_fp16 = const()[name = tensor<string, []>("const_21_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154176)))];
            tensor<fp16, [1, 32, 20, ?]> out_7_cast_fp16 = conv(bias = const_21_to_fp16, 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_20_to_fp16, x = input_53_cast_fp16)[name = tensor<string, []>("out_7_cast_fp16")];
            tensor<fp16, [1, 32, 20, ?]> input_57_cast_fp16 = add(x = out_7_cast_fp16, y = input_47_cast_fp16)[name = tensor<string, []>("input_57_cast_fp16")];
            tensor<fp16, [1, 32, 20, ?]> input_59_cast_fp16 = relu(x = input_57_cast_fp16)[name = tensor<string, []>("input_59_cast_fp16")];
            tensor<string, []> input_61_pad_type_0 = const()[name = tensor<string, []>("input_61_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_61_pad_0 = const()[name = tensor<string, []>("input_61_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_61_strides_0 = const()[name = tensor<string, []>("input_61_strides_0"), val = tensor<int32, [2]>([2, 1])];
            tensor<int32, [2]> input_61_dilations_0 = const()[name = tensor<string, []>("input_61_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_61_groups_0 = const()[name = tensor<string, []>("input_61_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 32, 3, 3]> const_22_to_fp16 = const()[name = tensor<string, []>("const_22_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(154304)))];
            tensor<fp16, [32]> const_23_to_fp16 = const()[name = tensor<string, []>("const_23_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172800)))];
            tensor<fp16, [1, 32, 10, ?]> input_63_cast_fp16 = conv(bias = const_23_to_fp16, dilations = input_61_dilations_0, groups = input_61_groups_0, pad = input_61_pad_0, pad_type = input_61_pad_type_0, strides = input_61_strides_0, weight = const_22_to_fp16, x = input_59_cast_fp16)[name = tensor<string, []>("input_63_cast_fp16")];
            tensor<fp16, [1, 32, 10, ?]> out_cast_fp16 = relu(x = input_63_cast_fp16)[name = tensor<string, []>("out_cast_fp16")];
            tensor<int32, [3]> concat_0x = const()[name = tensor<string, []>("concat_0x"), val = tensor<int32, [3]>([1, 320, -1])];
            tensor<fp16, [1, 320, ?]> input_65_cast_fp16 = reshape(shape = concat_0x, x = out_cast_fp16)[name = tensor<string, []>("input_65_cast_fp16")];
            tensor<string, []> input_67_pad_type_0 = const()[name = tensor<string, []>("input_67_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> input_67_pad_0 = const()[name = tensor<string, []>("input_67_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> input_67_strides_0 = const()[name = tensor<string, []>("input_67_strides_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> input_67_dilations_0 = const()[name = tensor<string, []>("input_67_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_67_groups_0 = const()[name = tensor<string, []>("input_67_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 320, 5]> const_24_to_fp16 = const()[name = tensor<string, []>("const_24_to_fp16"), val = tensor<fp16, [128, 320, 5]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172928)))];
            tensor<fp16, [128]> const_25_to_fp16 = const()[name = tensor<string, []>("const_25_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(582592)))];
            tensor<fp16, [1, 128, ?]> input_69_cast_fp16 = conv(bias = const_25_to_fp16, dilations = input_67_dilations_0, groups = input_67_groups_0, pad = input_67_pad_0, pad_type = input_67_pad_type_0, strides = input_67_strides_0, weight = const_24_to_fp16, x = input_65_cast_fp16)[name = tensor<string, []>("input_69_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_71_cast_fp16 = relu(x = input_69_cast_fp16)[name = tensor<string, []>("input_71_cast_fp16")];
            tensor<fp16, [128]> net_xvector_block1_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(582912)))];
            tensor<fp16, [128]> net_xvector_block1_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(583232)))];
            tensor<fp16, [128]> net_xvector_block1_tdnnd1_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd1_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(583552)))];
            tensor<fp16, [128]> net_xvector_block1_tdnnd1_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd1_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(583872)))];
            tensor<fp16, []> var_8_to_fp16 = const()[name = tensor<string, []>("op_8_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 128, ?]> input_73_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd1_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd1_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16, x = input_71_cast_fp16)[name = tensor<string, []>("input_73_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_75_cast_fp16 = relu(x = input_73_cast_fp16)[name = tensor<string, []>("input_75_cast_fp16")];
            tensor<string, []> input_77_pad_type_0 = const()[name = tensor<string, []>("input_77_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_77_strides_0 = const()[name = tensor<string, []>("input_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_77_pad_0 = const()[name = tensor<string, []>("input_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_77_dilations_0 = const()[name = tensor<string, []>("input_77_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_77_groups_0 = const()[name = tensor<string, []>("input_77_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 128, 1]> const_26_to_fp16 = const()[name = tensor<string, []>("const_26_to_fp16"), val = tensor<fp16, [128, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(584192)))];
            tensor<fp16, [128]> const_27_to_fp16 = const()[name = tensor<string, []>("const_27_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(617024)))];
            tensor<fp16, [1, 128, ?]> input_79_cast_fp16 = conv(bias = const_27_to_fp16, dilations = input_77_dilations_0, groups = input_77_groups_0, pad = input_77_pad_0, pad_type = input_77_pad_type_0, strides = input_77_strides_0, weight = const_26_to_fp16, x = input_75_cast_fp16)[name = tensor<string, []>("input_79_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_81_cast_fp16 = relu(x = input_79_cast_fp16)[name = tensor<string, []>("input_81_cast_fp16")];
            tensor<string, []> y_1_pad_type_0 = const()[name = tensor<string, []>("y_1_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_1_pad_0 = const()[name = tensor<string, []>("y_1_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_1_strides_0 = const()[name = tensor<string, []>("y_1_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_1_dilations_0 = const()[name = tensor<string, []>("y_1_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_1_groups_0 = const()[name = tensor<string, []>("y_1_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd1_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd1_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(617344)))];
            tensor<fp16, [1, 32, ?]> y_1_cast_fp16 = conv(dilations = y_1_dilations_0, groups = y_1_groups_0, pad = y_1_pad_0, pad_type = y_1_pad_type_0, strides = y_1_strides_0, weight = net_xvector_block1_tdnnd1_cam_layer_linear_local_weight_to_fp16, x = input_81_cast_fp16)[name = tensor<string, []>("y_1_cast_fp16")];
            tensor<int32, [1]> var_277_axes_0 = const()[name = tensor<string, []>("op_277_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_277_keep_dims_0 = const()[name = tensor<string, []>("op_277_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_277_cast_fp16 = reduce_mean(axes = var_277_axes_0, keep_dims = var_277_keep_dims_0, x = input_81_cast_fp16)[name = tensor<string, []>("op_277_cast_fp16")];
            tensor<int32, [1]> var_278 = const()[name = tensor<string, []>("op_278"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_279 = const()[name = tensor<string, []>("op_279"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_1_pad_type_0 = const()[name = tensor<string, []>("seg_1_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_1_pad_0 = const()[name = tensor<string, []>("seg_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_1_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_1_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_1_ceil_mode_0 = const()[name = tensor<string, []>("seg_1_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_1_cast_fp16 = avg_pool(ceil_mode = seg_1_ceil_mode_0, exclude_padding_from_average = seg_1_exclude_padding_from_average_0, kernel_sizes = var_278, pad = seg_1_pad_0, pad_type = seg_1_pad_type_0, strides = var_279, x = input_81_cast_fp16)[name = tensor<string, []>("seg_1_cast_fp16")];
            tensor<int32, [3]> var_282_shape_cast_fp16 = shape(x = seg_1_cast_fp16)[name = tensor<string, []>("op_282_shape_cast_fp16")];
            tensor<int32, []> gather_4 = const()[name = tensor<string, []>("gather_4"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_5 = const()[name = tensor<string, []>("gather_5"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_6_axis_0 = const()[name = tensor<string, []>("gather_6_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_6_batch_dims_0 = const()[name = tensor<string, []>("gather_6_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_6_validate_indices_0 = const()[name = tensor<string, []>("gather_6_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_282_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_282_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_6_to_uint16 = const()[name = tensor<string, []>("select_6_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_282_shape_cast_fp16_to_uint16 = cast(dtype = var_282_shape_cast_fp16_to_uint16_dtype_0, x = var_282_shape_cast_fp16)[name = tensor<string, []>("cast_315")];
            tensor<uint16, []> gather_6_cast_uint16 = gather(axis = gather_6_axis_0, batch_dims = gather_6_batch_dims_0, indices = select_6_to_uint16, validate_indices = gather_6_validate_indices_0, x = var_282_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_6_cast_uint16")];
            tensor<string, []> gather_6_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_6_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_285_axes_0 = const()[name = tensor<string, []>("op_285_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_285_cast_fp16 = expand_dims(axes = var_285_axes_0, x = seg_1_cast_fp16)[name = tensor<string, []>("op_285_cast_fp16")];
            tensor<int32, []> concat_1_axis_0 = const()[name = tensor<string, []>("concat_1_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_1_interleave_0 = const()[name = tensor<string, []>("concat_1_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_6_cast_uint16_to_int32 = cast(dtype = gather_6_cast_uint16_to_int32_dtype_0, x = gather_6_cast_uint16)[name = tensor<string, []>("cast_314")];
            tensor<int32, [4]> concat_1 = concat(axis = concat_1_axis_0, interleave = concat_1_interleave_0, values = (gather_4, gather_5, gather_6_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_1")];
            tensor<int32, [4]> shape_7_cast_fp16 = shape(x = var_285_cast_fp16)[name = tensor<string, []>("shape_7_cast_fp16")];
            tensor<int32, [4]> real_div_0 = real_div(x = concat_1, y = shape_7_cast_fp16)[name = tensor<string, []>("real_div_0")];
            tensor<fp16, [?, ?, ?, ?]> var_287_cast_fp16 = tile(reps = real_div_0, x = var_285_cast_fp16)[name = tensor<string, []>("op_287_cast_fp16")];
            tensor<int32, [3]> var_288 = const()[name = tensor<string, []>("op_288"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_3_cast_fp16 = reshape(shape = var_288, x = var_287_cast_fp16)[name = tensor<string, []>("seg_3_cast_fp16")];
            tensor<int32, [3]> var_290_shape_cast_fp16 = shape(x = input_81_cast_fp16)[name = tensor<string, []>("op_290_shape_cast_fp16")];
            tensor<int32, []> gather_7_axis_0 = const()[name = tensor<string, []>("gather_7_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_7_batch_dims_0 = const()[name = tensor<string, []>("gather_7_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_7_validate_indices_0 = const()[name = tensor<string, []>("gather_7_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_290_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_290_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_7_to_uint16 = const()[name = tensor<string, []>("select_7_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_290_shape_cast_fp16_to_uint16 = cast(dtype = var_290_shape_cast_fp16_to_uint16_dtype_0, x = var_290_shape_cast_fp16)[name = tensor<string, []>("cast_313")];
            tensor<uint16, []> gather_7_cast_uint16 = gather(axis = gather_7_axis_0, batch_dims = gather_7_batch_dims_0, indices = select_7_to_uint16, validate_indices = gather_7_validate_indices_0, x = var_290_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_7_cast_uint16")];
            tensor<string, []> gather_7_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_7_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_2_values0_0 = const()[name = tensor<string, []>("concat_2_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_2_values1_0 = const()[name = tensor<string, []>("concat_2_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_2_axis_0 = const()[name = tensor<string, []>("concat_2_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_2_interleave_0 = const()[name = tensor<string, []>("concat_2_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_7_cast_uint16_to_int32 = cast(dtype = gather_7_cast_uint16_to_int32_dtype_0, x = gather_7_cast_uint16)[name = tensor<string, []>("cast_312")];
            tensor<int32, [3]> concat_2 = concat(axis = concat_2_axis_0, interleave = concat_2_interleave_0, values = (concat_2_values0_0, concat_2_values1_0, gather_7_cast_uint16_to_int32))[name = tensor<string, []>("concat_2")];
            tensor<int32, [3]> var_291_begin_0 = const()[name = tensor<string, []>("op_291_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_291_end_mask_0 = const()[name = tensor<string, []>("op_291_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_291_cast_fp16 = slice_by_index(begin = var_291_begin_0, end = concat_2, end_mask = var_291_end_mask_0, x = seg_3_cast_fp16)[name = tensor<string, []>("op_291_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_83_cast_fp16 = add(x = var_277_cast_fp16, y = var_291_cast_fp16)[name = tensor<string, []>("input_83_cast_fp16")];
            tensor<string, []> input_85_pad_type_0 = const()[name = tensor<string, []>("input_85_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_85_strides_0 = const()[name = tensor<string, []>("input_85_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_85_pad_0 = const()[name = tensor<string, []>("input_85_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_85_dilations_0 = const()[name = tensor<string, []>("input_85_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_85_groups_0 = const()[name = tensor<string, []>("input_85_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd1_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd1_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(641984)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd1_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd1_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(658432)))];
            tensor<fp16, [1, 64, ?]> input_85_cast_fp16 = conv(bias = net_xvector_block1_tdnnd1_cam_layer_linear1_bias_to_fp16, dilations = input_85_dilations_0, groups = input_85_groups_0, pad = input_85_pad_0, pad_type = input_85_pad_type_0, strides = input_85_strides_0, weight = net_xvector_block1_tdnnd1_cam_layer_linear1_weight_to_fp16, x = input_83_cast_fp16)[name = tensor<string, []>("input_85_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_87_cast_fp16 = relu(x = input_85_cast_fp16)[name = tensor<string, []>("input_87_cast_fp16")];
            tensor<string, []> input_89_pad_type_0 = const()[name = tensor<string, []>("input_89_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_89_strides_0 = const()[name = tensor<string, []>("input_89_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_89_pad_0 = const()[name = tensor<string, []>("input_89_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_89_dilations_0 = const()[name = tensor<string, []>("input_89_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_89_groups_0 = const()[name = tensor<string, []>("input_89_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd1_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd1_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(658624)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd1_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd1_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(662784)))];
            tensor<fp16, [1, 32, ?]> input_89_cast_fp16 = conv(bias = net_xvector_block1_tdnnd1_cam_layer_linear2_bias_to_fp16, dilations = input_89_dilations_0, groups = input_89_groups_0, pad = input_89_pad_0, pad_type = input_89_pad_type_0, strides = input_89_strides_0, weight = net_xvector_block1_tdnnd1_cam_layer_linear2_weight_to_fp16, x = input_87_cast_fp16)[name = tensor<string, []>("input_89_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_1_cast_fp16 = sigmoid(x = input_89_cast_fp16)[name = tensor<string, []>("m_1_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_309_cast_fp16 = mul(x = y_1_cast_fp16, y = m_1_cast_fp16)[name = tensor<string, []>("op_309_cast_fp16")];
            tensor<bool, []> input_91_interleave_0 = const()[name = tensor<string, []>("input_91_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 160, ?]> input_91_cast_fp16 = concat(axis = var_11, interleave = input_91_interleave_0, values = (input_71_cast_fp16, var_309_cast_fp16))[name = tensor<string, []>("input_91_cast_fp16")];
            tensor<fp16, [160]> net_xvector_block1_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(662912)))];
            tensor<fp16, [160]> net_xvector_block1_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(663296)))];
            tensor<fp16, [160]> net_xvector_block1_tdnnd2_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd2_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(663680)))];
            tensor<fp16, [160]> net_xvector_block1_tdnnd2_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd2_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [160]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(664064)))];
            tensor<fp16, [1, 160, ?]> input_93_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd2_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd2_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16, x = input_91_cast_fp16)[name = tensor<string, []>("input_93_cast_fp16")];
            tensor<fp16, [1, 160, ?]> input_95_cast_fp16 = relu(x = input_93_cast_fp16)[name = tensor<string, []>("input_95_cast_fp16")];
            tensor<string, []> input_97_pad_type_0 = const()[name = tensor<string, []>("input_97_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_97_strides_0 = const()[name = tensor<string, []>("input_97_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_97_pad_0 = const()[name = tensor<string, []>("input_97_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_97_dilations_0 = const()[name = tensor<string, []>("input_97_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_97_groups_0 = const()[name = tensor<string, []>("input_97_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 160, 1]> const_28_to_fp16 = const()[name = tensor<string, []>("const_28_to_fp16"), val = tensor<fp16, [128, 160, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(664448)))];
            tensor<fp16, [128]> const_29_to_fp16 = const()[name = tensor<string, []>("const_29_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(705472)))];
            tensor<fp16, [1, 128, ?]> input_99_cast_fp16 = conv(bias = const_29_to_fp16, dilations = input_97_dilations_0, groups = input_97_groups_0, pad = input_97_pad_0, pad_type = input_97_pad_type_0, strides = input_97_strides_0, weight = const_28_to_fp16, x = input_95_cast_fp16)[name = tensor<string, []>("input_99_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_101_cast_fp16 = relu(x = input_99_cast_fp16)[name = tensor<string, []>("input_101_cast_fp16")];
            tensor<string, []> y_3_pad_type_0 = const()[name = tensor<string, []>("y_3_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_3_pad_0 = const()[name = tensor<string, []>("y_3_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_3_strides_0 = const()[name = tensor<string, []>("y_3_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_3_dilations_0 = const()[name = tensor<string, []>("y_3_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_3_groups_0 = const()[name = tensor<string, []>("y_3_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd2_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd2_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(705792)))];
            tensor<fp16, [1, 32, ?]> y_3_cast_fp16 = conv(dilations = y_3_dilations_0, groups = y_3_groups_0, pad = y_3_pad_0, pad_type = y_3_pad_type_0, strides = y_3_strides_0, weight = net_xvector_block1_tdnnd2_cam_layer_linear_local_weight_to_fp16, x = input_101_cast_fp16)[name = tensor<string, []>("y_3_cast_fp16")];
            tensor<int32, [1]> var_346_axes_0 = const()[name = tensor<string, []>("op_346_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_346_keep_dims_0 = const()[name = tensor<string, []>("op_346_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_346_cast_fp16 = reduce_mean(axes = var_346_axes_0, keep_dims = var_346_keep_dims_0, x = input_101_cast_fp16)[name = tensor<string, []>("op_346_cast_fp16")];
            tensor<int32, [1]> var_347 = const()[name = tensor<string, []>("op_347"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_348 = const()[name = tensor<string, []>("op_348"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_5_pad_type_0 = const()[name = tensor<string, []>("seg_5_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_5_pad_0 = const()[name = tensor<string, []>("seg_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_5_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_5_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_5_ceil_mode_0 = const()[name = tensor<string, []>("seg_5_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_5_cast_fp16 = avg_pool(ceil_mode = seg_5_ceil_mode_0, exclude_padding_from_average = seg_5_exclude_padding_from_average_0, kernel_sizes = var_347, pad = seg_5_pad_0, pad_type = seg_5_pad_type_0, strides = var_348, x = input_101_cast_fp16)[name = tensor<string, []>("seg_5_cast_fp16")];
            tensor<int32, [3]> var_351_shape_cast_fp16 = shape(x = seg_5_cast_fp16)[name = tensor<string, []>("op_351_shape_cast_fp16")];
            tensor<int32, []> gather_8 = const()[name = tensor<string, []>("gather_8"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_9 = const()[name = tensor<string, []>("gather_9"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_10_axis_0 = const()[name = tensor<string, []>("gather_10_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_10_batch_dims_0 = const()[name = tensor<string, []>("gather_10_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_10_validate_indices_0 = const()[name = tensor<string, []>("gather_10_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_351_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_351_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_10_to_uint16 = const()[name = tensor<string, []>("select_10_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_351_shape_cast_fp16_to_uint16 = cast(dtype = var_351_shape_cast_fp16_to_uint16_dtype_0, x = var_351_shape_cast_fp16)[name = tensor<string, []>("cast_311")];
            tensor<uint16, []> gather_10_cast_uint16 = gather(axis = gather_10_axis_0, batch_dims = gather_10_batch_dims_0, indices = select_10_to_uint16, validate_indices = gather_10_validate_indices_0, x = var_351_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_10_cast_uint16")];
            tensor<string, []> gather_10_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_10_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_354_axes_0 = const()[name = tensor<string, []>("op_354_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_354_cast_fp16 = expand_dims(axes = var_354_axes_0, x = seg_5_cast_fp16)[name = tensor<string, []>("op_354_cast_fp16")];
            tensor<int32, []> concat_3_axis_0 = const()[name = tensor<string, []>("concat_3_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_3_interleave_0 = const()[name = tensor<string, []>("concat_3_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_10_cast_uint16_to_int32 = cast(dtype = gather_10_cast_uint16_to_int32_dtype_0, x = gather_10_cast_uint16)[name = tensor<string, []>("cast_310")];
            tensor<int32, [4]> concat_3 = concat(axis = concat_3_axis_0, interleave = concat_3_interleave_0, values = (gather_8, gather_9, gather_10_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_3")];
            tensor<int32, [4]> shape_12_cast_fp16 = shape(x = var_354_cast_fp16)[name = tensor<string, []>("shape_12_cast_fp16")];
            tensor<int32, [4]> real_div_1 = real_div(x = concat_3, y = shape_12_cast_fp16)[name = tensor<string, []>("real_div_1")];
            tensor<fp16, [?, ?, ?, ?]> var_356_cast_fp16 = tile(reps = real_div_1, x = var_354_cast_fp16)[name = tensor<string, []>("op_356_cast_fp16")];
            tensor<int32, [3]> var_357 = const()[name = tensor<string, []>("op_357"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_7_cast_fp16 = reshape(shape = var_357, x = var_356_cast_fp16)[name = tensor<string, []>("seg_7_cast_fp16")];
            tensor<int32, [3]> var_359_shape_cast_fp16 = shape(x = input_101_cast_fp16)[name = tensor<string, []>("op_359_shape_cast_fp16")];
            tensor<int32, []> gather_11_axis_0 = const()[name = tensor<string, []>("gather_11_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_11_batch_dims_0 = const()[name = tensor<string, []>("gather_11_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_11_validate_indices_0 = const()[name = tensor<string, []>("gather_11_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_359_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_359_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_11_to_uint16 = const()[name = tensor<string, []>("select_11_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_359_shape_cast_fp16_to_uint16 = cast(dtype = var_359_shape_cast_fp16_to_uint16_dtype_0, x = var_359_shape_cast_fp16)[name = tensor<string, []>("cast_309")];
            tensor<uint16, []> gather_11_cast_uint16 = gather(axis = gather_11_axis_0, batch_dims = gather_11_batch_dims_0, indices = select_11_to_uint16, validate_indices = gather_11_validate_indices_0, x = var_359_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_11_cast_uint16")];
            tensor<string, []> gather_11_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_11_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_4_values0_0 = const()[name = tensor<string, []>("concat_4_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_4_values1_0 = const()[name = tensor<string, []>("concat_4_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_4_axis_0 = const()[name = tensor<string, []>("concat_4_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_4_interleave_0 = const()[name = tensor<string, []>("concat_4_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_11_cast_uint16_to_int32 = cast(dtype = gather_11_cast_uint16_to_int32_dtype_0, x = gather_11_cast_uint16)[name = tensor<string, []>("cast_308")];
            tensor<int32, [3]> concat_4 = concat(axis = concat_4_axis_0, interleave = concat_4_interleave_0, values = (concat_4_values0_0, concat_4_values1_0, gather_11_cast_uint16_to_int32))[name = tensor<string, []>("concat_4")];
            tensor<int32, [3]> var_360_begin_0 = const()[name = tensor<string, []>("op_360_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_360_end_mask_0 = const()[name = tensor<string, []>("op_360_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_360_cast_fp16 = slice_by_index(begin = var_360_begin_0, end = concat_4, end_mask = var_360_end_mask_0, x = seg_7_cast_fp16)[name = tensor<string, []>("op_360_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_103_cast_fp16 = add(x = var_346_cast_fp16, y = var_360_cast_fp16)[name = tensor<string, []>("input_103_cast_fp16")];
            tensor<string, []> input_105_pad_type_0 = const()[name = tensor<string, []>("input_105_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_105_strides_0 = const()[name = tensor<string, []>("input_105_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_105_pad_0 = const()[name = tensor<string, []>("input_105_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_105_dilations_0 = const()[name = tensor<string, []>("input_105_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_105_groups_0 = const()[name = tensor<string, []>("input_105_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd2_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd2_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(730432)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd2_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd2_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(746880)))];
            tensor<fp16, [1, 64, ?]> input_105_cast_fp16 = conv(bias = net_xvector_block1_tdnnd2_cam_layer_linear1_bias_to_fp16, 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 = net_xvector_block1_tdnnd2_cam_layer_linear1_weight_to_fp16, x = input_103_cast_fp16)[name = tensor<string, []>("input_105_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_107_cast_fp16 = relu(x = input_105_cast_fp16)[name = tensor<string, []>("input_107_cast_fp16")];
            tensor<string, []> input_109_pad_type_0 = const()[name = tensor<string, []>("input_109_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_109_strides_0 = const()[name = tensor<string, []>("input_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_109_pad_0 = const()[name = tensor<string, []>("input_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_109_dilations_0 = const()[name = tensor<string, []>("input_109_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_109_groups_0 = const()[name = tensor<string, []>("input_109_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd2_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd2_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(747072)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd2_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd2_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(751232)))];
            tensor<fp16, [1, 32, ?]> input_109_cast_fp16 = conv(bias = net_xvector_block1_tdnnd2_cam_layer_linear2_bias_to_fp16, dilations = input_109_dilations_0, groups = input_109_groups_0, pad = input_109_pad_0, pad_type = input_109_pad_type_0, strides = input_109_strides_0, weight = net_xvector_block1_tdnnd2_cam_layer_linear2_weight_to_fp16, x = input_107_cast_fp16)[name = tensor<string, []>("input_109_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_3_cast_fp16 = sigmoid(x = input_109_cast_fp16)[name = tensor<string, []>("m_3_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_378_cast_fp16 = mul(x = y_3_cast_fp16, y = m_3_cast_fp16)[name = tensor<string, []>("op_378_cast_fp16")];
            tensor<bool, []> input_111_interleave_0 = const()[name = tensor<string, []>("input_111_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 192, ?]> input_111_cast_fp16 = concat(axis = var_11, interleave = input_111_interleave_0, values = (input_91_cast_fp16, var_378_cast_fp16))[name = tensor<string, []>("input_111_cast_fp16")];
            tensor<fp16, [192]> net_xvector_block1_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(751360)))];
            tensor<fp16, [192]> net_xvector_block1_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(751808)))];
            tensor<fp16, [192]> net_xvector_block1_tdnnd3_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd3_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(752256)))];
            tensor<fp16, [192]> net_xvector_block1_tdnnd3_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd3_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(752704)))];
            tensor<fp16, [1, 192, ?]> input_113_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd3_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd3_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16, x = input_111_cast_fp16)[name = tensor<string, []>("input_113_cast_fp16")];
            tensor<fp16, [1, 192, ?]> input_115_cast_fp16 = relu(x = input_113_cast_fp16)[name = tensor<string, []>("input_115_cast_fp16")];
            tensor<string, []> input_117_pad_type_0 = const()[name = tensor<string, []>("input_117_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_117_strides_0 = const()[name = tensor<string, []>("input_117_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_117_pad_0 = const()[name = tensor<string, []>("input_117_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_117_dilations_0 = const()[name = tensor<string, []>("input_117_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_117_groups_0 = const()[name = tensor<string, []>("input_117_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 192, 1]> const_30_to_fp16 = const()[name = tensor<string, []>("const_30_to_fp16"), val = tensor<fp16, [128, 192, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(753152)))];
            tensor<fp16, [128]> const_31_to_fp16 = const()[name = tensor<string, []>("const_31_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(802368)))];
            tensor<fp16, [1, 128, ?]> input_119_cast_fp16 = conv(bias = const_31_to_fp16, dilations = input_117_dilations_0, groups = input_117_groups_0, pad = input_117_pad_0, pad_type = input_117_pad_type_0, strides = input_117_strides_0, weight = const_30_to_fp16, x = input_115_cast_fp16)[name = tensor<string, []>("input_119_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_121_cast_fp16 = relu(x = input_119_cast_fp16)[name = tensor<string, []>("input_121_cast_fp16")];
            tensor<string, []> y_5_pad_type_0 = const()[name = tensor<string, []>("y_5_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_5_pad_0 = const()[name = tensor<string, []>("y_5_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_5_strides_0 = const()[name = tensor<string, []>("y_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_5_dilations_0 = const()[name = tensor<string, []>("y_5_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_5_groups_0 = const()[name = tensor<string, []>("y_5_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd3_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd3_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(802688)))];
            tensor<fp16, [1, 32, ?]> y_5_cast_fp16 = conv(dilations = y_5_dilations_0, groups = y_5_groups_0, pad = y_5_pad_0, pad_type = y_5_pad_type_0, strides = y_5_strides_0, weight = net_xvector_block1_tdnnd3_cam_layer_linear_local_weight_to_fp16, x = input_121_cast_fp16)[name = tensor<string, []>("y_5_cast_fp16")];
            tensor<int32, [1]> var_415_axes_0 = const()[name = tensor<string, []>("op_415_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_415_keep_dims_0 = const()[name = tensor<string, []>("op_415_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_415_cast_fp16 = reduce_mean(axes = var_415_axes_0, keep_dims = var_415_keep_dims_0, x = input_121_cast_fp16)[name = tensor<string, []>("op_415_cast_fp16")];
            tensor<int32, [1]> var_416 = const()[name = tensor<string, []>("op_416"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_417 = const()[name = tensor<string, []>("op_417"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_9_pad_type_0 = const()[name = tensor<string, []>("seg_9_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_9_pad_0 = const()[name = tensor<string, []>("seg_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_9_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_9_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_9_ceil_mode_0 = const()[name = tensor<string, []>("seg_9_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_9_cast_fp16 = avg_pool(ceil_mode = seg_9_ceil_mode_0, exclude_padding_from_average = seg_9_exclude_padding_from_average_0, kernel_sizes = var_416, pad = seg_9_pad_0, pad_type = seg_9_pad_type_0, strides = var_417, x = input_121_cast_fp16)[name = tensor<string, []>("seg_9_cast_fp16")];
            tensor<int32, [3]> var_420_shape_cast_fp16 = shape(x = seg_9_cast_fp16)[name = tensor<string, []>("op_420_shape_cast_fp16")];
            tensor<int32, []> gather_12 = const()[name = tensor<string, []>("gather_12"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_13 = const()[name = tensor<string, []>("gather_13"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_14_axis_0 = const()[name = tensor<string, []>("gather_14_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_14_batch_dims_0 = const()[name = tensor<string, []>("gather_14_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_14_validate_indices_0 = const()[name = tensor<string, []>("gather_14_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_420_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_420_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_14_to_uint16 = const()[name = tensor<string, []>("select_14_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_420_shape_cast_fp16_to_uint16 = cast(dtype = var_420_shape_cast_fp16_to_uint16_dtype_0, x = var_420_shape_cast_fp16)[name = tensor<string, []>("cast_307")];
            tensor<uint16, []> gather_14_cast_uint16 = gather(axis = gather_14_axis_0, batch_dims = gather_14_batch_dims_0, indices = select_14_to_uint16, validate_indices = gather_14_validate_indices_0, x = var_420_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_14_cast_uint16")];
            tensor<string, []> gather_14_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_14_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_423_axes_0 = const()[name = tensor<string, []>("op_423_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_423_cast_fp16 = expand_dims(axes = var_423_axes_0, x = seg_9_cast_fp16)[name = tensor<string, []>("op_423_cast_fp16")];
            tensor<int32, []> concat_5_axis_0 = const()[name = tensor<string, []>("concat_5_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_5_interleave_0 = const()[name = tensor<string, []>("concat_5_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_14_cast_uint16_to_int32 = cast(dtype = gather_14_cast_uint16_to_int32_dtype_0, x = gather_14_cast_uint16)[name = tensor<string, []>("cast_306")];
            tensor<int32, [4]> concat_5 = concat(axis = concat_5_axis_0, interleave = concat_5_interleave_0, values = (gather_12, gather_13, gather_14_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_5")];
            tensor<int32, [4]> shape_17_cast_fp16 = shape(x = var_423_cast_fp16)[name = tensor<string, []>("shape_17_cast_fp16")];
            tensor<int32, [4]> real_div_2 = real_div(x = concat_5, y = shape_17_cast_fp16)[name = tensor<string, []>("real_div_2")];
            tensor<fp16, [?, ?, ?, ?]> var_425_cast_fp16 = tile(reps = real_div_2, x = var_423_cast_fp16)[name = tensor<string, []>("op_425_cast_fp16")];
            tensor<int32, [3]> var_426 = const()[name = tensor<string, []>("op_426"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_11_cast_fp16 = reshape(shape = var_426, x = var_425_cast_fp16)[name = tensor<string, []>("seg_11_cast_fp16")];
            tensor<int32, [3]> var_428_shape_cast_fp16 = shape(x = input_121_cast_fp16)[name = tensor<string, []>("op_428_shape_cast_fp16")];
            tensor<int32, []> gather_15_axis_0 = const()[name = tensor<string, []>("gather_15_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_15_batch_dims_0 = const()[name = tensor<string, []>("gather_15_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_15_validate_indices_0 = const()[name = tensor<string, []>("gather_15_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_428_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_428_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_15_to_uint16 = const()[name = tensor<string, []>("select_15_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_428_shape_cast_fp16_to_uint16 = cast(dtype = var_428_shape_cast_fp16_to_uint16_dtype_0, x = var_428_shape_cast_fp16)[name = tensor<string, []>("cast_305")];
            tensor<uint16, []> gather_15_cast_uint16 = gather(axis = gather_15_axis_0, batch_dims = gather_15_batch_dims_0, indices = select_15_to_uint16, validate_indices = gather_15_validate_indices_0, x = var_428_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_15_cast_uint16")];
            tensor<string, []> gather_15_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_15_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_6_values0_0 = const()[name = tensor<string, []>("concat_6_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_6_values1_0 = const()[name = tensor<string, []>("concat_6_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_6_axis_0 = const()[name = tensor<string, []>("concat_6_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_6_interleave_0 = const()[name = tensor<string, []>("concat_6_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_15_cast_uint16_to_int32 = cast(dtype = gather_15_cast_uint16_to_int32_dtype_0, x = gather_15_cast_uint16)[name = tensor<string, []>("cast_304")];
            tensor<int32, [3]> concat_6 = concat(axis = concat_6_axis_0, interleave = concat_6_interleave_0, values = (concat_6_values0_0, concat_6_values1_0, gather_15_cast_uint16_to_int32))[name = tensor<string, []>("concat_6")];
            tensor<int32, [3]> var_429_begin_0 = const()[name = tensor<string, []>("op_429_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_429_end_mask_0 = const()[name = tensor<string, []>("op_429_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_429_cast_fp16 = slice_by_index(begin = var_429_begin_0, end = concat_6, end_mask = var_429_end_mask_0, x = seg_11_cast_fp16)[name = tensor<string, []>("op_429_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_123_cast_fp16 = add(x = var_415_cast_fp16, y = var_429_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, []>("valid")];
            tensor<int32, [1]> input_125_strides_0 = const()[name = tensor<string, []>("input_125_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_125_pad_0 = const()[name = tensor<string, []>("input_125_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_125_dilations_0 = const()[name = tensor<string, []>("input_125_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_125_groups_0 = const()[name = tensor<string, []>("input_125_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd3_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd3_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(827328)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd3_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd3_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(843776)))];
            tensor<fp16, [1, 64, ?]> input_125_cast_fp16 = conv(bias = net_xvector_block1_tdnnd3_cam_layer_linear1_bias_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 = net_xvector_block1_tdnnd3_cam_layer_linear1_weight_to_fp16, x = input_123_cast_fp16)[name = tensor<string, []>("input_125_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_127_cast_fp16 = relu(x = input_125_cast_fp16)[name = tensor<string, []>("input_127_cast_fp16")];
            tensor<string, []> input_129_pad_type_0 = const()[name = tensor<string, []>("input_129_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_129_strides_0 = const()[name = tensor<string, []>("input_129_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_129_pad_0 = const()[name = tensor<string, []>("input_129_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_129_dilations_0 = const()[name = tensor<string, []>("input_129_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_129_groups_0 = const()[name = tensor<string, []>("input_129_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd3_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd3_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(843968)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd3_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd3_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848128)))];
            tensor<fp16, [1, 32, ?]> input_129_cast_fp16 = conv(bias = net_xvector_block1_tdnnd3_cam_layer_linear2_bias_to_fp16, dilations = input_129_dilations_0, groups = input_129_groups_0, pad = input_129_pad_0, pad_type = input_129_pad_type_0, strides = input_129_strides_0, weight = net_xvector_block1_tdnnd3_cam_layer_linear2_weight_to_fp16, x = input_127_cast_fp16)[name = tensor<string, []>("input_129_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_5_cast_fp16 = sigmoid(x = input_129_cast_fp16)[name = tensor<string, []>("m_5_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_447_cast_fp16 = mul(x = y_5_cast_fp16, y = m_5_cast_fp16)[name = tensor<string, []>("op_447_cast_fp16")];
            tensor<bool, []> input_131_interleave_0 = const()[name = tensor<string, []>("input_131_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 224, ?]> input_131_cast_fp16 = concat(axis = var_11, interleave = input_131_interleave_0, values = (input_111_cast_fp16, var_447_cast_fp16))[name = tensor<string, []>("input_131_cast_fp16")];
            tensor<fp16, [224]> net_xvector_block1_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [224]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848256)))];
            tensor<fp16, [224]> net_xvector_block1_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [224]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848768)))];
            tensor<fp16, [224]> net_xvector_block1_tdnnd4_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd4_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [224]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(849280)))];
            tensor<fp16, [224]> net_xvector_block1_tdnnd4_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd4_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [224]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(849792)))];
            tensor<fp16, [1, 224, ?]> input_133_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd4_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd4_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16, x = input_131_cast_fp16)[name = tensor<string, []>("input_133_cast_fp16")];
            tensor<fp16, [1, 224, ?]> 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, []>("valid")];
            tensor<int32, [1]> input_137_strides_0 = const()[name = tensor<string, []>("input_137_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_137_pad_0 = const()[name = tensor<string, []>("input_137_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_137_dilations_0 = const()[name = tensor<string, []>("input_137_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_137_groups_0 = const()[name = tensor<string, []>("input_137_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 224, 1]> const_32_to_fp16 = const()[name = tensor<string, []>("const_32_to_fp16"), val = tensor<fp16, [128, 224, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(850304)))];
            tensor<fp16, [128]> const_33_to_fp16 = const()[name = tensor<string, []>("const_33_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(907712)))];
            tensor<fp16, [1, 128, ?]> input_139_cast_fp16 = conv(bias = const_33_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_32_to_fp16, x = input_135_cast_fp16)[name = tensor<string, []>("input_139_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_141_cast_fp16 = relu(x = input_139_cast_fp16)[name = tensor<string, []>("input_141_cast_fp16")];
            tensor<string, []> y_7_pad_type_0 = const()[name = tensor<string, []>("y_7_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_7_pad_0 = const()[name = tensor<string, []>("y_7_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_7_strides_0 = const()[name = tensor<string, []>("y_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_7_dilations_0 = const()[name = tensor<string, []>("y_7_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_7_groups_0 = const()[name = tensor<string, []>("y_7_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd4_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd4_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(908032)))];
            tensor<fp16, [1, 32, ?]> y_7_cast_fp16 = conv(dilations = y_7_dilations_0, groups = y_7_groups_0, pad = y_7_pad_0, pad_type = y_7_pad_type_0, strides = y_7_strides_0, weight = net_xvector_block1_tdnnd4_cam_layer_linear_local_weight_to_fp16, x = input_141_cast_fp16)[name = tensor<string, []>("y_7_cast_fp16")];
            tensor<int32, [1]> var_484_axes_0 = const()[name = tensor<string, []>("op_484_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_484_keep_dims_0 = const()[name = tensor<string, []>("op_484_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_484_cast_fp16 = reduce_mean(axes = var_484_axes_0, keep_dims = var_484_keep_dims_0, x = input_141_cast_fp16)[name = tensor<string, []>("op_484_cast_fp16")];
            tensor<int32, [1]> var_485 = const()[name = tensor<string, []>("op_485"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_486 = const()[name = tensor<string, []>("op_486"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_13_pad_type_0 = const()[name = tensor<string, []>("seg_13_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_13_pad_0 = const()[name = tensor<string, []>("seg_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_13_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_13_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_13_ceil_mode_0 = const()[name = tensor<string, []>("seg_13_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_13_cast_fp16 = avg_pool(ceil_mode = seg_13_ceil_mode_0, exclude_padding_from_average = seg_13_exclude_padding_from_average_0, kernel_sizes = var_485, pad = seg_13_pad_0, pad_type = seg_13_pad_type_0, strides = var_486, x = input_141_cast_fp16)[name = tensor<string, []>("seg_13_cast_fp16")];
            tensor<int32, [3]> var_489_shape_cast_fp16 = shape(x = seg_13_cast_fp16)[name = tensor<string, []>("op_489_shape_cast_fp16")];
            tensor<int32, []> gather_16 = const()[name = tensor<string, []>("gather_16"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_17 = const()[name = tensor<string, []>("gather_17"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_18_axis_0 = const()[name = tensor<string, []>("gather_18_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_18_batch_dims_0 = const()[name = tensor<string, []>("gather_18_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_18_validate_indices_0 = const()[name = tensor<string, []>("gather_18_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_489_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_489_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_18_to_uint16 = const()[name = tensor<string, []>("select_18_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_489_shape_cast_fp16_to_uint16 = cast(dtype = var_489_shape_cast_fp16_to_uint16_dtype_0, x = var_489_shape_cast_fp16)[name = tensor<string, []>("cast_303")];
            tensor<uint16, []> gather_18_cast_uint16 = gather(axis = gather_18_axis_0, batch_dims = gather_18_batch_dims_0, indices = select_18_to_uint16, validate_indices = gather_18_validate_indices_0, x = var_489_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_18_cast_uint16")];
            tensor<string, []> gather_18_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_18_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_492_axes_0 = const()[name = tensor<string, []>("op_492_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_492_cast_fp16 = expand_dims(axes = var_492_axes_0, x = seg_13_cast_fp16)[name = tensor<string, []>("op_492_cast_fp16")];
            tensor<int32, []> concat_7_axis_0 = const()[name = tensor<string, []>("concat_7_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_7_interleave_0 = const()[name = tensor<string, []>("concat_7_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_18_cast_uint16_to_int32 = cast(dtype = gather_18_cast_uint16_to_int32_dtype_0, x = gather_18_cast_uint16)[name = tensor<string, []>("cast_302")];
            tensor<int32, [4]> concat_7 = concat(axis = concat_7_axis_0, interleave = concat_7_interleave_0, values = (gather_16, gather_17, gather_18_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_7")];
            tensor<int32, [4]> shape_22_cast_fp16 = shape(x = var_492_cast_fp16)[name = tensor<string, []>("shape_22_cast_fp16")];
            tensor<int32, [4]> real_div_3 = real_div(x = concat_7, y = shape_22_cast_fp16)[name = tensor<string, []>("real_div_3")];
            tensor<fp16, [?, ?, ?, ?]> var_494_cast_fp16 = tile(reps = real_div_3, x = var_492_cast_fp16)[name = tensor<string, []>("op_494_cast_fp16")];
            tensor<int32, [3]> var_495 = const()[name = tensor<string, []>("op_495"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_15_cast_fp16 = reshape(shape = var_495, x = var_494_cast_fp16)[name = tensor<string, []>("seg_15_cast_fp16")];
            tensor<int32, [3]> var_497_shape_cast_fp16 = shape(x = input_141_cast_fp16)[name = tensor<string, []>("op_497_shape_cast_fp16")];
            tensor<int32, []> gather_19_axis_0 = const()[name = tensor<string, []>("gather_19_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_19_batch_dims_0 = const()[name = tensor<string, []>("gather_19_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_19_validate_indices_0 = const()[name = tensor<string, []>("gather_19_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_497_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_497_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_19_to_uint16 = const()[name = tensor<string, []>("select_19_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_497_shape_cast_fp16_to_uint16 = cast(dtype = var_497_shape_cast_fp16_to_uint16_dtype_0, x = var_497_shape_cast_fp16)[name = tensor<string, []>("cast_301")];
            tensor<uint16, []> gather_19_cast_uint16 = gather(axis = gather_19_axis_0, batch_dims = gather_19_batch_dims_0, indices = select_19_to_uint16, validate_indices = gather_19_validate_indices_0, x = var_497_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_19_cast_uint16")];
            tensor<string, []> gather_19_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_19_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_8_values0_0 = const()[name = tensor<string, []>("concat_8_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_8_values1_0 = const()[name = tensor<string, []>("concat_8_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_8_axis_0 = const()[name = tensor<string, []>("concat_8_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_8_interleave_0 = const()[name = tensor<string, []>("concat_8_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_19_cast_uint16_to_int32 = cast(dtype = gather_19_cast_uint16_to_int32_dtype_0, x = gather_19_cast_uint16)[name = tensor<string, []>("cast_300")];
            tensor<int32, [3]> concat_8 = concat(axis = concat_8_axis_0, interleave = concat_8_interleave_0, values = (concat_8_values0_0, concat_8_values1_0, gather_19_cast_uint16_to_int32))[name = tensor<string, []>("concat_8")];
            tensor<int32, [3]> var_498_begin_0 = const()[name = tensor<string, []>("op_498_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_498_end_mask_0 = const()[name = tensor<string, []>("op_498_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_498_cast_fp16 = slice_by_index(begin = var_498_begin_0, end = concat_8, end_mask = var_498_end_mask_0, x = seg_15_cast_fp16)[name = tensor<string, []>("op_498_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_143_cast_fp16 = add(x = var_484_cast_fp16, y = var_498_cast_fp16)[name = tensor<string, []>("input_143_cast_fp16")];
            tensor<string, []> input_145_pad_type_0 = const()[name = tensor<string, []>("input_145_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_145_strides_0 = const()[name = tensor<string, []>("input_145_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_145_pad_0 = const()[name = tensor<string, []>("input_145_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_145_dilations_0 = const()[name = tensor<string, []>("input_145_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_145_groups_0 = const()[name = tensor<string, []>("input_145_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd4_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd4_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(932672)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd4_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd4_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(949120)))];
            tensor<fp16, [1, 64, ?]> input_145_cast_fp16 = conv(bias = net_xvector_block1_tdnnd4_cam_layer_linear1_bias_to_fp16, dilations = input_145_dilations_0, groups = input_145_groups_0, pad = input_145_pad_0, pad_type = input_145_pad_type_0, strides = input_145_strides_0, weight = net_xvector_block1_tdnnd4_cam_layer_linear1_weight_to_fp16, x = input_143_cast_fp16)[name = tensor<string, []>("input_145_cast_fp16")];
            tensor<fp16, [1, 64, ?]> 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, []>("valid")];
            tensor<int32, [1]> input_149_strides_0 = const()[name = tensor<string, []>("input_149_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_149_pad_0 = const()[name = tensor<string, []>("input_149_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_149_dilations_0 = const()[name = tensor<string, []>("input_149_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_149_groups_0 = const()[name = tensor<string, []>("input_149_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd4_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd4_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(949312)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd4_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd4_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953472)))];
            tensor<fp16, [1, 32, ?]> input_149_cast_fp16 = conv(bias = net_xvector_block1_tdnnd4_cam_layer_linear2_bias_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 = net_xvector_block1_tdnnd4_cam_layer_linear2_weight_to_fp16, x = input_147_cast_fp16)[name = tensor<string, []>("input_149_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_7_cast_fp16 = sigmoid(x = input_149_cast_fp16)[name = tensor<string, []>("m_7_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_516_cast_fp16 = mul(x = y_7_cast_fp16, y = m_7_cast_fp16)[name = tensor<string, []>("op_516_cast_fp16")];
            tensor<bool, []> input_151_interleave_0 = const()[name = tensor<string, []>("input_151_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 256, ?]> input_151_cast_fp16 = concat(axis = var_11, interleave = input_151_interleave_0, values = (input_131_cast_fp16, var_516_cast_fp16))[name = tensor<string, []>("input_151_cast_fp16")];
            tensor<fp16, [256]> net_xvector_block1_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953600)))];
            tensor<fp16, [256]> net_xvector_block1_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(954176)))];
            tensor<fp16, [256]> net_xvector_block1_tdnnd5_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd5_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(954752)))];
            tensor<fp16, [256]> net_xvector_block1_tdnnd5_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd5_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(955328)))];
            tensor<fp16, [1, 256, ?]> input_153_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd5_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd5_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16, x = input_151_cast_fp16)[name = tensor<string, []>("input_153_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_155_cast_fp16 = relu(x = input_153_cast_fp16)[name = tensor<string, []>("input_155_cast_fp16")];
            tensor<string, []> input_157_pad_type_0 = const()[name = tensor<string, []>("input_157_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_157_strides_0 = const()[name = tensor<string, []>("input_157_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_157_pad_0 = const()[name = tensor<string, []>("input_157_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_157_dilations_0 = const()[name = tensor<string, []>("input_157_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_157_groups_0 = const()[name = tensor<string, []>("input_157_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 256, 1]> const_34_to_fp16 = const()[name = tensor<string, []>("const_34_to_fp16"), val = tensor<fp16, [128, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(955904)))];
            tensor<fp16, [128]> const_35_to_fp16 = const()[name = tensor<string, []>("const_35_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1021504)))];
            tensor<fp16, [1, 128, ?]> input_159_cast_fp16 = conv(bias = const_35_to_fp16, dilations = input_157_dilations_0, groups = input_157_groups_0, pad = input_157_pad_0, pad_type = input_157_pad_type_0, strides = input_157_strides_0, weight = const_34_to_fp16, x = input_155_cast_fp16)[name = tensor<string, []>("input_159_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_161_cast_fp16 = relu(x = input_159_cast_fp16)[name = tensor<string, []>("input_161_cast_fp16")];
            tensor<string, []> y_9_pad_type_0 = const()[name = tensor<string, []>("y_9_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_9_pad_0 = const()[name = tensor<string, []>("y_9_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_9_strides_0 = const()[name = tensor<string, []>("y_9_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_9_dilations_0 = const()[name = tensor<string, []>("y_9_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_9_groups_0 = const()[name = tensor<string, []>("y_9_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd5_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd5_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1021824)))];
            tensor<fp16, [1, 32, ?]> y_9_cast_fp16 = conv(dilations = y_9_dilations_0, groups = y_9_groups_0, pad = y_9_pad_0, pad_type = y_9_pad_type_0, strides = y_9_strides_0, weight = net_xvector_block1_tdnnd5_cam_layer_linear_local_weight_to_fp16, x = input_161_cast_fp16)[name = tensor<string, []>("y_9_cast_fp16")];
            tensor<int32, [1]> var_553_axes_0 = const()[name = tensor<string, []>("op_553_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_553_keep_dims_0 = const()[name = tensor<string, []>("op_553_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_553_cast_fp16 = reduce_mean(axes = var_553_axes_0, keep_dims = var_553_keep_dims_0, x = input_161_cast_fp16)[name = tensor<string, []>("op_553_cast_fp16")];
            tensor<int32, [1]> var_554 = const()[name = tensor<string, []>("op_554"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_555 = const()[name = tensor<string, []>("op_555"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_17_pad_type_0 = const()[name = tensor<string, []>("seg_17_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_17_pad_0 = const()[name = tensor<string, []>("seg_17_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_17_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_17_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_17_ceil_mode_0 = const()[name = tensor<string, []>("seg_17_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_17_cast_fp16 = avg_pool(ceil_mode = seg_17_ceil_mode_0, exclude_padding_from_average = seg_17_exclude_padding_from_average_0, kernel_sizes = var_554, pad = seg_17_pad_0, pad_type = seg_17_pad_type_0, strides = var_555, x = input_161_cast_fp16)[name = tensor<string, []>("seg_17_cast_fp16")];
            tensor<int32, [3]> var_558_shape_cast_fp16 = shape(x = seg_17_cast_fp16)[name = tensor<string, []>("op_558_shape_cast_fp16")];
            tensor<int32, []> gather_20 = const()[name = tensor<string, []>("gather_20"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_21 = const()[name = tensor<string, []>("gather_21"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_22_axis_0 = const()[name = tensor<string, []>("gather_22_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_22_batch_dims_0 = const()[name = tensor<string, []>("gather_22_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_22_validate_indices_0 = const()[name = tensor<string, []>("gather_22_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_558_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_558_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_22_to_uint16 = const()[name = tensor<string, []>("select_22_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_558_shape_cast_fp16_to_uint16 = cast(dtype = var_558_shape_cast_fp16_to_uint16_dtype_0, x = var_558_shape_cast_fp16)[name = tensor<string, []>("cast_299")];
            tensor<uint16, []> gather_22_cast_uint16 = gather(axis = gather_22_axis_0, batch_dims = gather_22_batch_dims_0, indices = select_22_to_uint16, validate_indices = gather_22_validate_indices_0, x = var_558_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_22_cast_uint16")];
            tensor<string, []> gather_22_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_22_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_561_axes_0 = const()[name = tensor<string, []>("op_561_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_561_cast_fp16 = expand_dims(axes = var_561_axes_0, x = seg_17_cast_fp16)[name = tensor<string, []>("op_561_cast_fp16")];
            tensor<int32, []> concat_9_axis_0 = const()[name = tensor<string, []>("concat_9_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_9_interleave_0 = const()[name = tensor<string, []>("concat_9_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_22_cast_uint16_to_int32 = cast(dtype = gather_22_cast_uint16_to_int32_dtype_0, x = gather_22_cast_uint16)[name = tensor<string, []>("cast_298")];
            tensor<int32, [4]> concat_9 = concat(axis = concat_9_axis_0, interleave = concat_9_interleave_0, values = (gather_20, gather_21, gather_22_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_9")];
            tensor<int32, [4]> shape_27_cast_fp16 = shape(x = var_561_cast_fp16)[name = tensor<string, []>("shape_27_cast_fp16")];
            tensor<int32, [4]> real_div_4 = real_div(x = concat_9, y = shape_27_cast_fp16)[name = tensor<string, []>("real_div_4")];
            tensor<fp16, [?, ?, ?, ?]> var_563_cast_fp16 = tile(reps = real_div_4, x = var_561_cast_fp16)[name = tensor<string, []>("op_563_cast_fp16")];
            tensor<int32, [3]> var_564 = const()[name = tensor<string, []>("op_564"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_19_cast_fp16 = reshape(shape = var_564, x = var_563_cast_fp16)[name = tensor<string, []>("seg_19_cast_fp16")];
            tensor<int32, [3]> var_566_shape_cast_fp16 = shape(x = input_161_cast_fp16)[name = tensor<string, []>("op_566_shape_cast_fp16")];
            tensor<int32, []> gather_23_axis_0 = const()[name = tensor<string, []>("gather_23_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_23_batch_dims_0 = const()[name = tensor<string, []>("gather_23_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_23_validate_indices_0 = const()[name = tensor<string, []>("gather_23_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_566_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_566_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_23_to_uint16 = const()[name = tensor<string, []>("select_23_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_566_shape_cast_fp16_to_uint16 = cast(dtype = var_566_shape_cast_fp16_to_uint16_dtype_0, x = var_566_shape_cast_fp16)[name = tensor<string, []>("cast_297")];
            tensor<uint16, []> gather_23_cast_uint16 = gather(axis = gather_23_axis_0, batch_dims = gather_23_batch_dims_0, indices = select_23_to_uint16, validate_indices = gather_23_validate_indices_0, x = var_566_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_23_cast_uint16")];
            tensor<string, []> gather_23_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_23_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_10_values0_0 = const()[name = tensor<string, []>("concat_10_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_10_values1_0 = const()[name = tensor<string, []>("concat_10_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_10_axis_0 = const()[name = tensor<string, []>("concat_10_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_10_interleave_0 = const()[name = tensor<string, []>("concat_10_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_23_cast_uint16_to_int32 = cast(dtype = gather_23_cast_uint16_to_int32_dtype_0, x = gather_23_cast_uint16)[name = tensor<string, []>("cast_296")];
            tensor<int32, [3]> concat_10 = concat(axis = concat_10_axis_0, interleave = concat_10_interleave_0, values = (concat_10_values0_0, concat_10_values1_0, gather_23_cast_uint16_to_int32))[name = tensor<string, []>("concat_10")];
            tensor<int32, [3]> var_567_begin_0 = const()[name = tensor<string, []>("op_567_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_567_end_mask_0 = const()[name = tensor<string, []>("op_567_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_567_cast_fp16 = slice_by_index(begin = var_567_begin_0, end = concat_10, end_mask = var_567_end_mask_0, x = seg_19_cast_fp16)[name = tensor<string, []>("op_567_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_163_cast_fp16 = add(x = var_553_cast_fp16, y = var_567_cast_fp16)[name = tensor<string, []>("input_163_cast_fp16")];
            tensor<string, []> input_165_pad_type_0 = const()[name = tensor<string, []>("input_165_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_165_strides_0 = const()[name = tensor<string, []>("input_165_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_165_pad_0 = const()[name = tensor<string, []>("input_165_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_165_dilations_0 = const()[name = tensor<string, []>("input_165_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_165_groups_0 = const()[name = tensor<string, []>("input_165_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd5_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd5_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1046464)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd5_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd5_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1062912)))];
            tensor<fp16, [1, 64, ?]> input_165_cast_fp16 = conv(bias = net_xvector_block1_tdnnd5_cam_layer_linear1_bias_to_fp16, dilations = input_165_dilations_0, groups = input_165_groups_0, pad = input_165_pad_0, pad_type = input_165_pad_type_0, strides = input_165_strides_0, weight = net_xvector_block1_tdnnd5_cam_layer_linear1_weight_to_fp16, x = input_163_cast_fp16)[name = tensor<string, []>("input_165_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_167_cast_fp16 = relu(x = input_165_cast_fp16)[name = tensor<string, []>("input_167_cast_fp16")];
            tensor<string, []> input_169_pad_type_0 = const()[name = tensor<string, []>("input_169_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_169_strides_0 = const()[name = tensor<string, []>("input_169_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_169_pad_0 = const()[name = tensor<string, []>("input_169_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_169_dilations_0 = const()[name = tensor<string, []>("input_169_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_169_groups_0 = const()[name = tensor<string, []>("input_169_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd5_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd5_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1063104)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd5_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd5_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1067264)))];
            tensor<fp16, [1, 32, ?]> input_169_cast_fp16 = conv(bias = net_xvector_block1_tdnnd5_cam_layer_linear2_bias_to_fp16, dilations = input_169_dilations_0, groups = input_169_groups_0, pad = input_169_pad_0, pad_type = input_169_pad_type_0, strides = input_169_strides_0, weight = net_xvector_block1_tdnnd5_cam_layer_linear2_weight_to_fp16, x = input_167_cast_fp16)[name = tensor<string, []>("input_169_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_9_cast_fp16 = sigmoid(x = input_169_cast_fp16)[name = tensor<string, []>("m_9_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_585_cast_fp16 = mul(x = y_9_cast_fp16, y = m_9_cast_fp16)[name = tensor<string, []>("op_585_cast_fp16")];
            tensor<bool, []> input_171_interleave_0 = const()[name = tensor<string, []>("input_171_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 288, ?]> input_171_cast_fp16 = concat(axis = var_11, interleave = input_171_interleave_0, values = (input_151_cast_fp16, var_585_cast_fp16))[name = tensor<string, []>("input_171_cast_fp16")];
            tensor<fp16, [288]> net_xvector_block1_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [288]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1067392)))];
            tensor<fp16, [288]> net_xvector_block1_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [288]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1068032)))];
            tensor<fp16, [288]> net_xvector_block1_tdnnd6_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd6_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [288]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1068672)))];
            tensor<fp16, [288]> net_xvector_block1_tdnnd6_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd6_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [288]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1069312)))];
            tensor<fp16, [1, 288, ?]> input_173_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd6_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd6_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16, x = input_171_cast_fp16)[name = tensor<string, []>("input_173_cast_fp16")];
            tensor<fp16, [1, 288, ?]> input_175_cast_fp16 = relu(x = input_173_cast_fp16)[name = tensor<string, []>("input_175_cast_fp16")];
            tensor<string, []> input_177_pad_type_0 = const()[name = tensor<string, []>("input_177_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_177_strides_0 = const()[name = tensor<string, []>("input_177_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_177_pad_0 = const()[name = tensor<string, []>("input_177_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_177_dilations_0 = const()[name = tensor<string, []>("input_177_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_177_groups_0 = const()[name = tensor<string, []>("input_177_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 288, 1]> const_36_to_fp16 = const()[name = tensor<string, []>("const_36_to_fp16"), val = tensor<fp16, [128, 288, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1069952)))];
            tensor<fp16, [128]> const_37_to_fp16 = const()[name = tensor<string, []>("const_37_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1143744)))];
            tensor<fp16, [1, 128, ?]> input_179_cast_fp16 = conv(bias = const_37_to_fp16, dilations = input_177_dilations_0, groups = input_177_groups_0, pad = input_177_pad_0, pad_type = input_177_pad_type_0, strides = input_177_strides_0, weight = const_36_to_fp16, x = input_175_cast_fp16)[name = tensor<string, []>("input_179_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_181_cast_fp16 = relu(x = input_179_cast_fp16)[name = tensor<string, []>("input_181_cast_fp16")];
            tensor<string, []> y_11_pad_type_0 = const()[name = tensor<string, []>("y_11_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_11_pad_0 = const()[name = tensor<string, []>("y_11_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_11_strides_0 = const()[name = tensor<string, []>("y_11_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_11_dilations_0 = const()[name = tensor<string, []>("y_11_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_11_groups_0 = const()[name = tensor<string, []>("y_11_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd6_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd6_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1144064)))];
            tensor<fp16, [1, 32, ?]> y_11_cast_fp16 = conv(dilations = y_11_dilations_0, groups = y_11_groups_0, pad = y_11_pad_0, pad_type = y_11_pad_type_0, strides = y_11_strides_0, weight = net_xvector_block1_tdnnd6_cam_layer_linear_local_weight_to_fp16, x = input_181_cast_fp16)[name = tensor<string, []>("y_11_cast_fp16")];
            tensor<int32, [1]> var_622_axes_0 = const()[name = tensor<string, []>("op_622_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_622_keep_dims_0 = const()[name = tensor<string, []>("op_622_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_622_cast_fp16 = reduce_mean(axes = var_622_axes_0, keep_dims = var_622_keep_dims_0, x = input_181_cast_fp16)[name = tensor<string, []>("op_622_cast_fp16")];
            tensor<int32, [1]> var_623 = const()[name = tensor<string, []>("op_623"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_624 = const()[name = tensor<string, []>("op_624"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_21_pad_type_0 = const()[name = tensor<string, []>("seg_21_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_21_pad_0 = const()[name = tensor<string, []>("seg_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_21_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_21_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_21_ceil_mode_0 = const()[name = tensor<string, []>("seg_21_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_21_cast_fp16 = avg_pool(ceil_mode = seg_21_ceil_mode_0, exclude_padding_from_average = seg_21_exclude_padding_from_average_0, kernel_sizes = var_623, pad = seg_21_pad_0, pad_type = seg_21_pad_type_0, strides = var_624, x = input_181_cast_fp16)[name = tensor<string, []>("seg_21_cast_fp16")];
            tensor<int32, [3]> var_627_shape_cast_fp16 = shape(x = seg_21_cast_fp16)[name = tensor<string, []>("op_627_shape_cast_fp16")];
            tensor<int32, []> gather_24 = const()[name = tensor<string, []>("gather_24"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_25 = const()[name = tensor<string, []>("gather_25"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_26_axis_0 = const()[name = tensor<string, []>("gather_26_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_26_batch_dims_0 = const()[name = tensor<string, []>("gather_26_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_26_validate_indices_0 = const()[name = tensor<string, []>("gather_26_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_627_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_627_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_26_to_uint16 = const()[name = tensor<string, []>("select_26_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_627_shape_cast_fp16_to_uint16 = cast(dtype = var_627_shape_cast_fp16_to_uint16_dtype_0, x = var_627_shape_cast_fp16)[name = tensor<string, []>("cast_295")];
            tensor<uint16, []> gather_26_cast_uint16 = gather(axis = gather_26_axis_0, batch_dims = gather_26_batch_dims_0, indices = select_26_to_uint16, validate_indices = gather_26_validate_indices_0, x = var_627_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_26_cast_uint16")];
            tensor<string, []> gather_26_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_26_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_630_axes_0 = const()[name = tensor<string, []>("op_630_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_630_cast_fp16 = expand_dims(axes = var_630_axes_0, x = seg_21_cast_fp16)[name = tensor<string, []>("op_630_cast_fp16")];
            tensor<int32, []> concat_11_axis_0 = const()[name = tensor<string, []>("concat_11_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_11_interleave_0 = const()[name = tensor<string, []>("concat_11_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_26_cast_uint16_to_int32 = cast(dtype = gather_26_cast_uint16_to_int32_dtype_0, x = gather_26_cast_uint16)[name = tensor<string, []>("cast_294")];
            tensor<int32, [4]> concat_11 = concat(axis = concat_11_axis_0, interleave = concat_11_interleave_0, values = (gather_24, gather_25, gather_26_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_11")];
            tensor<int32, [4]> shape_32_cast_fp16 = shape(x = var_630_cast_fp16)[name = tensor<string, []>("shape_32_cast_fp16")];
            tensor<int32, [4]> real_div_5 = real_div(x = concat_11, y = shape_32_cast_fp16)[name = tensor<string, []>("real_div_5")];
            tensor<fp16, [?, ?, ?, ?]> var_632_cast_fp16 = tile(reps = real_div_5, x = var_630_cast_fp16)[name = tensor<string, []>("op_632_cast_fp16")];
            tensor<int32, [3]> var_633 = const()[name = tensor<string, []>("op_633"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_23_cast_fp16 = reshape(shape = var_633, x = var_632_cast_fp16)[name = tensor<string, []>("seg_23_cast_fp16")];
            tensor<int32, [3]> var_635_shape_cast_fp16 = shape(x = input_181_cast_fp16)[name = tensor<string, []>("op_635_shape_cast_fp16")];
            tensor<int32, []> gather_27_axis_0 = const()[name = tensor<string, []>("gather_27_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_27_batch_dims_0 = const()[name = tensor<string, []>("gather_27_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_27_validate_indices_0 = const()[name = tensor<string, []>("gather_27_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_635_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_635_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_27_to_uint16 = const()[name = tensor<string, []>("select_27_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_635_shape_cast_fp16_to_uint16 = cast(dtype = var_635_shape_cast_fp16_to_uint16_dtype_0, x = var_635_shape_cast_fp16)[name = tensor<string, []>("cast_293")];
            tensor<uint16, []> gather_27_cast_uint16 = gather(axis = gather_27_axis_0, batch_dims = gather_27_batch_dims_0, indices = select_27_to_uint16, validate_indices = gather_27_validate_indices_0, x = var_635_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_27_cast_uint16")];
            tensor<string, []> gather_27_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_27_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_12_values0_0 = const()[name = tensor<string, []>("concat_12_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_12_values1_0 = const()[name = tensor<string, []>("concat_12_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_12_axis_0 = const()[name = tensor<string, []>("concat_12_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_12_interleave_0 = const()[name = tensor<string, []>("concat_12_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_27_cast_uint16_to_int32 = cast(dtype = gather_27_cast_uint16_to_int32_dtype_0, x = gather_27_cast_uint16)[name = tensor<string, []>("cast_292")];
            tensor<int32, [3]> concat_12 = concat(axis = concat_12_axis_0, interleave = concat_12_interleave_0, values = (concat_12_values0_0, concat_12_values1_0, gather_27_cast_uint16_to_int32))[name = tensor<string, []>("concat_12")];
            tensor<int32, [3]> var_636_begin_0 = const()[name = tensor<string, []>("op_636_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_636_end_mask_0 = const()[name = tensor<string, []>("op_636_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_636_cast_fp16 = slice_by_index(begin = var_636_begin_0, end = concat_12, end_mask = var_636_end_mask_0, x = seg_23_cast_fp16)[name = tensor<string, []>("op_636_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_183_cast_fp16 = add(x = var_622_cast_fp16, y = var_636_cast_fp16)[name = tensor<string, []>("input_183_cast_fp16")];
            tensor<string, []> input_185_pad_type_0 = const()[name = tensor<string, []>("input_185_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_185_strides_0 = const()[name = tensor<string, []>("input_185_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_185_pad_0 = const()[name = tensor<string, []>("input_185_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_185_dilations_0 = const()[name = tensor<string, []>("input_185_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_185_groups_0 = const()[name = tensor<string, []>("input_185_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd6_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd6_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1168704)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd6_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd6_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1185152)))];
            tensor<fp16, [1, 64, ?]> input_185_cast_fp16 = conv(bias = net_xvector_block1_tdnnd6_cam_layer_linear1_bias_to_fp16, dilations = input_185_dilations_0, groups = input_185_groups_0, pad = input_185_pad_0, pad_type = input_185_pad_type_0, strides = input_185_strides_0, weight = net_xvector_block1_tdnnd6_cam_layer_linear1_weight_to_fp16, x = input_183_cast_fp16)[name = tensor<string, []>("input_185_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_187_cast_fp16 = relu(x = input_185_cast_fp16)[name = tensor<string, []>("input_187_cast_fp16")];
            tensor<string, []> input_189_pad_type_0 = const()[name = tensor<string, []>("input_189_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_189_strides_0 = const()[name = tensor<string, []>("input_189_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_189_pad_0 = const()[name = tensor<string, []>("input_189_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_189_dilations_0 = const()[name = tensor<string, []>("input_189_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_189_groups_0 = const()[name = tensor<string, []>("input_189_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd6_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd6_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1185344)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd6_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd6_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1189504)))];
            tensor<fp16, [1, 32, ?]> input_189_cast_fp16 = conv(bias = net_xvector_block1_tdnnd6_cam_layer_linear2_bias_to_fp16, dilations = input_189_dilations_0, groups = input_189_groups_0, pad = input_189_pad_0, pad_type = input_189_pad_type_0, strides = input_189_strides_0, weight = net_xvector_block1_tdnnd6_cam_layer_linear2_weight_to_fp16, x = input_187_cast_fp16)[name = tensor<string, []>("input_189_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_11_cast_fp16 = sigmoid(x = input_189_cast_fp16)[name = tensor<string, []>("m_11_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_654_cast_fp16 = mul(x = y_11_cast_fp16, y = m_11_cast_fp16)[name = tensor<string, []>("op_654_cast_fp16")];
            tensor<bool, []> input_191_interleave_0 = const()[name = tensor<string, []>("input_191_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 320, ?]> input_191_cast_fp16 = concat(axis = var_11, interleave = input_191_interleave_0, values = (input_171_cast_fp16, var_654_cast_fp16))[name = tensor<string, []>("input_191_cast_fp16")];
            tensor<fp16, [320]> net_xvector_block1_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1189632)))];
            tensor<fp16, [320]> net_xvector_block1_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1190336)))];
            tensor<fp16, [320]> net_xvector_block1_tdnnd7_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd7_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1191040)))];
            tensor<fp16, [320]> net_xvector_block1_tdnnd7_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd7_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1191744)))];
            tensor<fp16, [1, 320, ?]> input_193_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd7_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd7_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16, x = input_191_cast_fp16)[name = tensor<string, []>("input_193_cast_fp16")];
            tensor<fp16, [1, 320, ?]> input_195_cast_fp16 = relu(x = input_193_cast_fp16)[name = tensor<string, []>("input_195_cast_fp16")];
            tensor<string, []> input_197_pad_type_0 = const()[name = tensor<string, []>("input_197_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_197_strides_0 = const()[name = tensor<string, []>("input_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_197_pad_0 = const()[name = tensor<string, []>("input_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_197_dilations_0 = const()[name = tensor<string, []>("input_197_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_197_groups_0 = const()[name = tensor<string, []>("input_197_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 320, 1]> const_38_to_fp16 = const()[name = tensor<string, []>("const_38_to_fp16"), val = tensor<fp16, [128, 320, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1192448)))];
            tensor<fp16, [128]> const_39_to_fp16 = const()[name = tensor<string, []>("const_39_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1274432)))];
            tensor<fp16, [1, 128, ?]> input_199_cast_fp16 = conv(bias = const_39_to_fp16, dilations = input_197_dilations_0, groups = input_197_groups_0, pad = input_197_pad_0, pad_type = input_197_pad_type_0, strides = input_197_strides_0, weight = const_38_to_fp16, x = input_195_cast_fp16)[name = tensor<string, []>("input_199_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_201_cast_fp16 = relu(x = input_199_cast_fp16)[name = tensor<string, []>("input_201_cast_fp16")];
            tensor<string, []> y_13_pad_type_0 = const()[name = tensor<string, []>("y_13_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_13_pad_0 = const()[name = tensor<string, []>("y_13_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_13_strides_0 = const()[name = tensor<string, []>("y_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_13_dilations_0 = const()[name = tensor<string, []>("y_13_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_13_groups_0 = const()[name = tensor<string, []>("y_13_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd7_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd7_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1274752)))];
            tensor<fp16, [1, 32, ?]> y_13_cast_fp16 = conv(dilations = y_13_dilations_0, groups = y_13_groups_0, pad = y_13_pad_0, pad_type = y_13_pad_type_0, strides = y_13_strides_0, weight = net_xvector_block1_tdnnd7_cam_layer_linear_local_weight_to_fp16, x = input_201_cast_fp16)[name = tensor<string, []>("y_13_cast_fp16")];
            tensor<int32, [1]> var_691_axes_0 = const()[name = tensor<string, []>("op_691_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_691_keep_dims_0 = const()[name = tensor<string, []>("op_691_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_691_cast_fp16 = reduce_mean(axes = var_691_axes_0, keep_dims = var_691_keep_dims_0, x = input_201_cast_fp16)[name = tensor<string, []>("op_691_cast_fp16")];
            tensor<int32, [1]> var_692 = const()[name = tensor<string, []>("op_692"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_693 = const()[name = tensor<string, []>("op_693"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_25_pad_type_0 = const()[name = tensor<string, []>("seg_25_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_25_pad_0 = const()[name = tensor<string, []>("seg_25_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_25_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_25_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_25_ceil_mode_0 = const()[name = tensor<string, []>("seg_25_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_25_cast_fp16 = avg_pool(ceil_mode = seg_25_ceil_mode_0, exclude_padding_from_average = seg_25_exclude_padding_from_average_0, kernel_sizes = var_692, pad = seg_25_pad_0, pad_type = seg_25_pad_type_0, strides = var_693, x = input_201_cast_fp16)[name = tensor<string, []>("seg_25_cast_fp16")];
            tensor<int32, [3]> var_696_shape_cast_fp16 = shape(x = seg_25_cast_fp16)[name = tensor<string, []>("op_696_shape_cast_fp16")];
            tensor<int32, []> gather_28 = const()[name = tensor<string, []>("gather_28"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_29 = const()[name = tensor<string, []>("gather_29"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_30_axis_0 = const()[name = tensor<string, []>("gather_30_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_30_batch_dims_0 = const()[name = tensor<string, []>("gather_30_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_30_validate_indices_0 = const()[name = tensor<string, []>("gather_30_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_696_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_696_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_30_to_uint16 = const()[name = tensor<string, []>("select_30_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_696_shape_cast_fp16_to_uint16 = cast(dtype = var_696_shape_cast_fp16_to_uint16_dtype_0, x = var_696_shape_cast_fp16)[name = tensor<string, []>("cast_291")];
            tensor<uint16, []> gather_30_cast_uint16 = gather(axis = gather_30_axis_0, batch_dims = gather_30_batch_dims_0, indices = select_30_to_uint16, validate_indices = gather_30_validate_indices_0, x = var_696_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_30_cast_uint16")];
            tensor<string, []> gather_30_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_30_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_699_axes_0 = const()[name = tensor<string, []>("op_699_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_699_cast_fp16 = expand_dims(axes = var_699_axes_0, x = seg_25_cast_fp16)[name = tensor<string, []>("op_699_cast_fp16")];
            tensor<int32, []> concat_13_axis_0 = const()[name = tensor<string, []>("concat_13_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_13_interleave_0 = const()[name = tensor<string, []>("concat_13_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_30_cast_uint16_to_int32 = cast(dtype = gather_30_cast_uint16_to_int32_dtype_0, x = gather_30_cast_uint16)[name = tensor<string, []>("cast_290")];
            tensor<int32, [4]> concat_13 = concat(axis = concat_13_axis_0, interleave = concat_13_interleave_0, values = (gather_28, gather_29, gather_30_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_13")];
            tensor<int32, [4]> shape_37_cast_fp16 = shape(x = var_699_cast_fp16)[name = tensor<string, []>("shape_37_cast_fp16")];
            tensor<int32, [4]> real_div_6 = real_div(x = concat_13, y = shape_37_cast_fp16)[name = tensor<string, []>("real_div_6")];
            tensor<fp16, [?, ?, ?, ?]> var_701_cast_fp16 = tile(reps = real_div_6, x = var_699_cast_fp16)[name = tensor<string, []>("op_701_cast_fp16")];
            tensor<int32, [3]> var_702 = const()[name = tensor<string, []>("op_702"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_27_cast_fp16 = reshape(shape = var_702, x = var_701_cast_fp16)[name = tensor<string, []>("seg_27_cast_fp16")];
            tensor<int32, [3]> var_704_shape_cast_fp16 = shape(x = input_201_cast_fp16)[name = tensor<string, []>("op_704_shape_cast_fp16")];
            tensor<int32, []> gather_31_axis_0 = const()[name = tensor<string, []>("gather_31_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_31_batch_dims_0 = const()[name = tensor<string, []>("gather_31_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_31_validate_indices_0 = const()[name = tensor<string, []>("gather_31_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_704_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_704_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_31_to_uint16 = const()[name = tensor<string, []>("select_31_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_704_shape_cast_fp16_to_uint16 = cast(dtype = var_704_shape_cast_fp16_to_uint16_dtype_0, x = var_704_shape_cast_fp16)[name = tensor<string, []>("cast_289")];
            tensor<uint16, []> gather_31_cast_uint16 = gather(axis = gather_31_axis_0, batch_dims = gather_31_batch_dims_0, indices = select_31_to_uint16, validate_indices = gather_31_validate_indices_0, x = var_704_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_31_cast_uint16")];
            tensor<string, []> gather_31_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_31_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_14_values0_0 = const()[name = tensor<string, []>("concat_14_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_14_values1_0 = const()[name = tensor<string, []>("concat_14_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_14_axis_0 = const()[name = tensor<string, []>("concat_14_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_14_interleave_0 = const()[name = tensor<string, []>("concat_14_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_31_cast_uint16_to_int32 = cast(dtype = gather_31_cast_uint16_to_int32_dtype_0, x = gather_31_cast_uint16)[name = tensor<string, []>("cast_288")];
            tensor<int32, [3]> concat_14 = concat(axis = concat_14_axis_0, interleave = concat_14_interleave_0, values = (concat_14_values0_0, concat_14_values1_0, gather_31_cast_uint16_to_int32))[name = tensor<string, []>("concat_14")];
            tensor<int32, [3]> var_705_begin_0 = const()[name = tensor<string, []>("op_705_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_705_end_mask_0 = const()[name = tensor<string, []>("op_705_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_705_cast_fp16 = slice_by_index(begin = var_705_begin_0, end = concat_14, end_mask = var_705_end_mask_0, x = seg_27_cast_fp16)[name = tensor<string, []>("op_705_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_203_cast_fp16 = add(x = var_691_cast_fp16, y = var_705_cast_fp16)[name = tensor<string, []>("input_203_cast_fp16")];
            tensor<string, []> input_205_pad_type_0 = const()[name = tensor<string, []>("input_205_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_205_strides_0 = const()[name = tensor<string, []>("input_205_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_205_pad_0 = const()[name = tensor<string, []>("input_205_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_205_dilations_0 = const()[name = tensor<string, []>("input_205_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_205_groups_0 = const()[name = tensor<string, []>("input_205_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd7_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd7_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1299392)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd7_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd7_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1315840)))];
            tensor<fp16, [1, 64, ?]> input_205_cast_fp16 = conv(bias = net_xvector_block1_tdnnd7_cam_layer_linear1_bias_to_fp16, dilations = input_205_dilations_0, groups = input_205_groups_0, pad = input_205_pad_0, pad_type = input_205_pad_type_0, strides = input_205_strides_0, weight = net_xvector_block1_tdnnd7_cam_layer_linear1_weight_to_fp16, x = input_203_cast_fp16)[name = tensor<string, []>("input_205_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_207_cast_fp16 = relu(x = input_205_cast_fp16)[name = tensor<string, []>("input_207_cast_fp16")];
            tensor<string, []> input_209_pad_type_0 = const()[name = tensor<string, []>("input_209_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_209_strides_0 = const()[name = tensor<string, []>("input_209_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_209_pad_0 = const()[name = tensor<string, []>("input_209_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_209_dilations_0 = const()[name = tensor<string, []>("input_209_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_209_groups_0 = const()[name = tensor<string, []>("input_209_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd7_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd7_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1316032)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd7_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd7_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1320192)))];
            tensor<fp16, [1, 32, ?]> input_209_cast_fp16 = conv(bias = net_xvector_block1_tdnnd7_cam_layer_linear2_bias_to_fp16, dilations = input_209_dilations_0, groups = input_209_groups_0, pad = input_209_pad_0, pad_type = input_209_pad_type_0, strides = input_209_strides_0, weight = net_xvector_block1_tdnnd7_cam_layer_linear2_weight_to_fp16, x = input_207_cast_fp16)[name = tensor<string, []>("input_209_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_13_cast_fp16 = sigmoid(x = input_209_cast_fp16)[name = tensor<string, []>("m_13_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_723_cast_fp16 = mul(x = y_13_cast_fp16, y = m_13_cast_fp16)[name = tensor<string, []>("op_723_cast_fp16")];
            tensor<bool, []> input_211_interleave_0 = const()[name = tensor<string, []>("input_211_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 352, ?]> input_211_cast_fp16 = concat(axis = var_11, interleave = input_211_interleave_0, values = (input_191_cast_fp16, var_723_cast_fp16))[name = tensor<string, []>("input_211_cast_fp16")];
            tensor<fp16, [352]> net_xvector_block1_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [352]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1320320)))];
            tensor<fp16, [352]> net_xvector_block1_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [352]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1321088)))];
            tensor<fp16, [352]> net_xvector_block1_tdnnd8_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd8_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [352]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1321856)))];
            tensor<fp16, [352]> net_xvector_block1_tdnnd8_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd8_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [352]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1322624)))];
            tensor<fp16, [1, 352, ?]> input_213_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd8_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd8_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16, x = input_211_cast_fp16)[name = tensor<string, []>("input_213_cast_fp16")];
            tensor<fp16, [1, 352, ?]> input_215_cast_fp16 = relu(x = input_213_cast_fp16)[name = tensor<string, []>("input_215_cast_fp16")];
            tensor<string, []> input_217_pad_type_0 = const()[name = tensor<string, []>("input_217_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_217_strides_0 = const()[name = tensor<string, []>("input_217_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_217_pad_0 = const()[name = tensor<string, []>("input_217_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_217_dilations_0 = const()[name = tensor<string, []>("input_217_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_217_groups_0 = const()[name = tensor<string, []>("input_217_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 352, 1]> const_40_to_fp16 = const()[name = tensor<string, []>("const_40_to_fp16"), val = tensor<fp16, [128, 352, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1323392)))];
            tensor<fp16, [128]> const_41_to_fp16 = const()[name = tensor<string, []>("const_41_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1413568)))];
            tensor<fp16, [1, 128, ?]> input_219_cast_fp16 = conv(bias = const_41_to_fp16, dilations = input_217_dilations_0, groups = input_217_groups_0, pad = input_217_pad_0, pad_type = input_217_pad_type_0, strides = input_217_strides_0, weight = const_40_to_fp16, x = input_215_cast_fp16)[name = tensor<string, []>("input_219_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_221_cast_fp16 = relu(x = input_219_cast_fp16)[name = tensor<string, []>("input_221_cast_fp16")];
            tensor<string, []> y_15_pad_type_0 = const()[name = tensor<string, []>("y_15_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_15_pad_0 = const()[name = tensor<string, []>("y_15_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_15_strides_0 = const()[name = tensor<string, []>("y_15_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_15_dilations_0 = const()[name = tensor<string, []>("y_15_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_15_groups_0 = const()[name = tensor<string, []>("y_15_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd8_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd8_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1413888)))];
            tensor<fp16, [1, 32, ?]> y_15_cast_fp16 = conv(dilations = y_15_dilations_0, groups = y_15_groups_0, pad = y_15_pad_0, pad_type = y_15_pad_type_0, strides = y_15_strides_0, weight = net_xvector_block1_tdnnd8_cam_layer_linear_local_weight_to_fp16, x = input_221_cast_fp16)[name = tensor<string, []>("y_15_cast_fp16")];
            tensor<int32, [1]> var_760_axes_0 = const()[name = tensor<string, []>("op_760_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_760_keep_dims_0 = const()[name = tensor<string, []>("op_760_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_760_cast_fp16 = reduce_mean(axes = var_760_axes_0, keep_dims = var_760_keep_dims_0, x = input_221_cast_fp16)[name = tensor<string, []>("op_760_cast_fp16")];
            tensor<int32, [1]> var_761 = const()[name = tensor<string, []>("op_761"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_762 = const()[name = tensor<string, []>("op_762"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_29_pad_type_0 = const()[name = tensor<string, []>("seg_29_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_29_pad_0 = const()[name = tensor<string, []>("seg_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_29_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_29_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_29_ceil_mode_0 = const()[name = tensor<string, []>("seg_29_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_29_cast_fp16 = avg_pool(ceil_mode = seg_29_ceil_mode_0, exclude_padding_from_average = seg_29_exclude_padding_from_average_0, kernel_sizes = var_761, pad = seg_29_pad_0, pad_type = seg_29_pad_type_0, strides = var_762, x = input_221_cast_fp16)[name = tensor<string, []>("seg_29_cast_fp16")];
            tensor<int32, [3]> var_765_shape_cast_fp16 = shape(x = seg_29_cast_fp16)[name = tensor<string, []>("op_765_shape_cast_fp16")];
            tensor<int32, []> gather_32 = const()[name = tensor<string, []>("gather_32"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_33 = const()[name = tensor<string, []>("gather_33"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_34_axis_0 = const()[name = tensor<string, []>("gather_34_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_34_batch_dims_0 = const()[name = tensor<string, []>("gather_34_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_34_validate_indices_0 = const()[name = tensor<string, []>("gather_34_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_765_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_765_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_34_to_uint16 = const()[name = tensor<string, []>("select_34_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_765_shape_cast_fp16_to_uint16 = cast(dtype = var_765_shape_cast_fp16_to_uint16_dtype_0, x = var_765_shape_cast_fp16)[name = tensor<string, []>("cast_287")];
            tensor<uint16, []> gather_34_cast_uint16 = gather(axis = gather_34_axis_0, batch_dims = gather_34_batch_dims_0, indices = select_34_to_uint16, validate_indices = gather_34_validate_indices_0, x = var_765_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_34_cast_uint16")];
            tensor<string, []> gather_34_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_34_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_768_axes_0 = const()[name = tensor<string, []>("op_768_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_768_cast_fp16 = expand_dims(axes = var_768_axes_0, x = seg_29_cast_fp16)[name = tensor<string, []>("op_768_cast_fp16")];
            tensor<int32, []> concat_15_axis_0 = const()[name = tensor<string, []>("concat_15_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_15_interleave_0 = const()[name = tensor<string, []>("concat_15_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_34_cast_uint16_to_int32 = cast(dtype = gather_34_cast_uint16_to_int32_dtype_0, x = gather_34_cast_uint16)[name = tensor<string, []>("cast_286")];
            tensor<int32, [4]> concat_15 = concat(axis = concat_15_axis_0, interleave = concat_15_interleave_0, values = (gather_32, gather_33, gather_34_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_15")];
            tensor<int32, [4]> shape_42_cast_fp16 = shape(x = var_768_cast_fp16)[name = tensor<string, []>("shape_42_cast_fp16")];
            tensor<int32, [4]> real_div_7 = real_div(x = concat_15, y = shape_42_cast_fp16)[name = tensor<string, []>("real_div_7")];
            tensor<fp16, [?, ?, ?, ?]> var_770_cast_fp16 = tile(reps = real_div_7, x = var_768_cast_fp16)[name = tensor<string, []>("op_770_cast_fp16")];
            tensor<int32, [3]> var_771 = const()[name = tensor<string, []>("op_771"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_31_cast_fp16 = reshape(shape = var_771, x = var_770_cast_fp16)[name = tensor<string, []>("seg_31_cast_fp16")];
            tensor<int32, [3]> var_773_shape_cast_fp16 = shape(x = input_221_cast_fp16)[name = tensor<string, []>("op_773_shape_cast_fp16")];
            tensor<int32, []> gather_35_axis_0 = const()[name = tensor<string, []>("gather_35_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_35_batch_dims_0 = const()[name = tensor<string, []>("gather_35_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_35_validate_indices_0 = const()[name = tensor<string, []>("gather_35_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_773_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_773_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_35_to_uint16 = const()[name = tensor<string, []>("select_35_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_773_shape_cast_fp16_to_uint16 = cast(dtype = var_773_shape_cast_fp16_to_uint16_dtype_0, x = var_773_shape_cast_fp16)[name = tensor<string, []>("cast_285")];
            tensor<uint16, []> gather_35_cast_uint16 = gather(axis = gather_35_axis_0, batch_dims = gather_35_batch_dims_0, indices = select_35_to_uint16, validate_indices = gather_35_validate_indices_0, x = var_773_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_35_cast_uint16")];
            tensor<string, []> gather_35_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_35_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_16_values0_0 = const()[name = tensor<string, []>("concat_16_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_16_values1_0 = const()[name = tensor<string, []>("concat_16_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_16_axis_0 = const()[name = tensor<string, []>("concat_16_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_16_interleave_0 = const()[name = tensor<string, []>("concat_16_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_35_cast_uint16_to_int32 = cast(dtype = gather_35_cast_uint16_to_int32_dtype_0, x = gather_35_cast_uint16)[name = tensor<string, []>("cast_284")];
            tensor<int32, [3]> concat_16 = concat(axis = concat_16_axis_0, interleave = concat_16_interleave_0, values = (concat_16_values0_0, concat_16_values1_0, gather_35_cast_uint16_to_int32))[name = tensor<string, []>("concat_16")];
            tensor<int32, [3]> var_774_begin_0 = const()[name = tensor<string, []>("op_774_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_774_end_mask_0 = const()[name = tensor<string, []>("op_774_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_774_cast_fp16 = slice_by_index(begin = var_774_begin_0, end = concat_16, end_mask = var_774_end_mask_0, x = seg_31_cast_fp16)[name = tensor<string, []>("op_774_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_223_cast_fp16 = add(x = var_760_cast_fp16, y = var_774_cast_fp16)[name = tensor<string, []>("input_223_cast_fp16")];
            tensor<string, []> input_225_pad_type_0 = const()[name = tensor<string, []>("input_225_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_225_strides_0 = const()[name = tensor<string, []>("input_225_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_225_pad_0 = const()[name = tensor<string, []>("input_225_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_225_dilations_0 = const()[name = tensor<string, []>("input_225_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_225_groups_0 = const()[name = tensor<string, []>("input_225_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd8_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd8_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1438528)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd8_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd8_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1454976)))];
            tensor<fp16, [1, 64, ?]> input_225_cast_fp16 = conv(bias = net_xvector_block1_tdnnd8_cam_layer_linear1_bias_to_fp16, dilations = input_225_dilations_0, groups = input_225_groups_0, pad = input_225_pad_0, pad_type = input_225_pad_type_0, strides = input_225_strides_0, weight = net_xvector_block1_tdnnd8_cam_layer_linear1_weight_to_fp16, x = input_223_cast_fp16)[name = tensor<string, []>("input_225_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_227_cast_fp16 = relu(x = input_225_cast_fp16)[name = tensor<string, []>("input_227_cast_fp16")];
            tensor<string, []> input_229_pad_type_0 = const()[name = tensor<string, []>("input_229_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_229_strides_0 = const()[name = tensor<string, []>("input_229_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_229_pad_0 = const()[name = tensor<string, []>("input_229_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_229_dilations_0 = const()[name = tensor<string, []>("input_229_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_229_groups_0 = const()[name = tensor<string, []>("input_229_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd8_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd8_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1455168)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd8_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd8_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1459328)))];
            tensor<fp16, [1, 32, ?]> input_229_cast_fp16 = conv(bias = net_xvector_block1_tdnnd8_cam_layer_linear2_bias_to_fp16, dilations = input_229_dilations_0, groups = input_229_groups_0, pad = input_229_pad_0, pad_type = input_229_pad_type_0, strides = input_229_strides_0, weight = net_xvector_block1_tdnnd8_cam_layer_linear2_weight_to_fp16, x = input_227_cast_fp16)[name = tensor<string, []>("input_229_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_15_cast_fp16 = sigmoid(x = input_229_cast_fp16)[name = tensor<string, []>("m_15_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_792_cast_fp16 = mul(x = y_15_cast_fp16, y = m_15_cast_fp16)[name = tensor<string, []>("op_792_cast_fp16")];
            tensor<bool, []> input_231_interleave_0 = const()[name = tensor<string, []>("input_231_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 384, ?]> input_231_cast_fp16 = concat(axis = var_11, interleave = input_231_interleave_0, values = (input_211_cast_fp16, var_792_cast_fp16))[name = tensor<string, []>("input_231_cast_fp16")];
            tensor<fp16, [384]> net_xvector_block1_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1459456)))];
            tensor<fp16, [384]> net_xvector_block1_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1460288)))];
            tensor<fp16, [384]> net_xvector_block1_tdnnd9_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd9_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1461120)))];
            tensor<fp16, [384]> net_xvector_block1_tdnnd9_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd9_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1461952)))];
            tensor<fp16, [1, 384, ?]> input_233_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd9_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd9_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16, x = input_231_cast_fp16)[name = tensor<string, []>("input_233_cast_fp16")];
            tensor<fp16, [1, 384, ?]> input_235_cast_fp16 = relu(x = input_233_cast_fp16)[name = tensor<string, []>("input_235_cast_fp16")];
            tensor<string, []> input_237_pad_type_0 = const()[name = tensor<string, []>("input_237_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_237_strides_0 = const()[name = tensor<string, []>("input_237_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_237_pad_0 = const()[name = tensor<string, []>("input_237_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_237_dilations_0 = const()[name = tensor<string, []>("input_237_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_237_groups_0 = const()[name = tensor<string, []>("input_237_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 384, 1]> const_42_to_fp16 = const()[name = tensor<string, []>("const_42_to_fp16"), val = tensor<fp16, [128, 384, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1462784)))];
            tensor<fp16, [128]> const_43_to_fp16 = const()[name = tensor<string, []>("const_43_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1561152)))];
            tensor<fp16, [1, 128, ?]> input_239_cast_fp16 = conv(bias = const_43_to_fp16, dilations = input_237_dilations_0, groups = input_237_groups_0, pad = input_237_pad_0, pad_type = input_237_pad_type_0, strides = input_237_strides_0, weight = const_42_to_fp16, x = input_235_cast_fp16)[name = tensor<string, []>("input_239_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_241_cast_fp16 = relu(x = input_239_cast_fp16)[name = tensor<string, []>("input_241_cast_fp16")];
            tensor<string, []> y_17_pad_type_0 = const()[name = tensor<string, []>("y_17_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_17_pad_0 = const()[name = tensor<string, []>("y_17_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_17_strides_0 = const()[name = tensor<string, []>("y_17_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_17_dilations_0 = const()[name = tensor<string, []>("y_17_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_17_groups_0 = const()[name = tensor<string, []>("y_17_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd9_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd9_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1561472)))];
            tensor<fp16, [1, 32, ?]> y_17_cast_fp16 = conv(dilations = y_17_dilations_0, groups = y_17_groups_0, pad = y_17_pad_0, pad_type = y_17_pad_type_0, strides = y_17_strides_0, weight = net_xvector_block1_tdnnd9_cam_layer_linear_local_weight_to_fp16, x = input_241_cast_fp16)[name = tensor<string, []>("y_17_cast_fp16")];
            tensor<int32, [1]> var_829_axes_0 = const()[name = tensor<string, []>("op_829_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_829_keep_dims_0 = const()[name = tensor<string, []>("op_829_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_829_cast_fp16 = reduce_mean(axes = var_829_axes_0, keep_dims = var_829_keep_dims_0, x = input_241_cast_fp16)[name = tensor<string, []>("op_829_cast_fp16")];
            tensor<int32, [1]> var_830 = const()[name = tensor<string, []>("op_830"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_831 = const()[name = tensor<string, []>("op_831"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_33_pad_type_0 = const()[name = tensor<string, []>("seg_33_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_33_pad_0 = const()[name = tensor<string, []>("seg_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_33_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_33_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_33_ceil_mode_0 = const()[name = tensor<string, []>("seg_33_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_33_cast_fp16 = avg_pool(ceil_mode = seg_33_ceil_mode_0, exclude_padding_from_average = seg_33_exclude_padding_from_average_0, kernel_sizes = var_830, pad = seg_33_pad_0, pad_type = seg_33_pad_type_0, strides = var_831, x = input_241_cast_fp16)[name = tensor<string, []>("seg_33_cast_fp16")];
            tensor<int32, [3]> var_834_shape_cast_fp16 = shape(x = seg_33_cast_fp16)[name = tensor<string, []>("op_834_shape_cast_fp16")];
            tensor<int32, []> gather_36 = const()[name = tensor<string, []>("gather_36"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_37 = const()[name = tensor<string, []>("gather_37"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_38_axis_0 = const()[name = tensor<string, []>("gather_38_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_38_batch_dims_0 = const()[name = tensor<string, []>("gather_38_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_38_validate_indices_0 = const()[name = tensor<string, []>("gather_38_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_834_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_834_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_38_to_uint16 = const()[name = tensor<string, []>("select_38_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_834_shape_cast_fp16_to_uint16 = cast(dtype = var_834_shape_cast_fp16_to_uint16_dtype_0, x = var_834_shape_cast_fp16)[name = tensor<string, []>("cast_283")];
            tensor<uint16, []> gather_38_cast_uint16 = gather(axis = gather_38_axis_0, batch_dims = gather_38_batch_dims_0, indices = select_38_to_uint16, validate_indices = gather_38_validate_indices_0, x = var_834_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_38_cast_uint16")];
            tensor<string, []> gather_38_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_38_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_837_axes_0 = const()[name = tensor<string, []>("op_837_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_837_cast_fp16 = expand_dims(axes = var_837_axes_0, x = seg_33_cast_fp16)[name = tensor<string, []>("op_837_cast_fp16")];
            tensor<int32, []> concat_17_axis_0 = const()[name = tensor<string, []>("concat_17_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_17_interleave_0 = const()[name = tensor<string, []>("concat_17_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_38_cast_uint16_to_int32 = cast(dtype = gather_38_cast_uint16_to_int32_dtype_0, x = gather_38_cast_uint16)[name = tensor<string, []>("cast_282")];
            tensor<int32, [4]> concat_17 = concat(axis = concat_17_axis_0, interleave = concat_17_interleave_0, values = (gather_36, gather_37, gather_38_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_17")];
            tensor<int32, [4]> shape_47_cast_fp16 = shape(x = var_837_cast_fp16)[name = tensor<string, []>("shape_47_cast_fp16")];
            tensor<int32, [4]> real_div_8 = real_div(x = concat_17, y = shape_47_cast_fp16)[name = tensor<string, []>("real_div_8")];
            tensor<fp16, [?, ?, ?, ?]> var_839_cast_fp16 = tile(reps = real_div_8, x = var_837_cast_fp16)[name = tensor<string, []>("op_839_cast_fp16")];
            tensor<int32, [3]> var_840 = const()[name = tensor<string, []>("op_840"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_35_cast_fp16 = reshape(shape = var_840, x = var_839_cast_fp16)[name = tensor<string, []>("seg_35_cast_fp16")];
            tensor<int32, [3]> var_842_shape_cast_fp16 = shape(x = input_241_cast_fp16)[name = tensor<string, []>("op_842_shape_cast_fp16")];
            tensor<int32, []> gather_39_axis_0 = const()[name = tensor<string, []>("gather_39_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_39_batch_dims_0 = const()[name = tensor<string, []>("gather_39_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_39_validate_indices_0 = const()[name = tensor<string, []>("gather_39_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_842_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_842_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_39_to_uint16 = const()[name = tensor<string, []>("select_39_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_842_shape_cast_fp16_to_uint16 = cast(dtype = var_842_shape_cast_fp16_to_uint16_dtype_0, x = var_842_shape_cast_fp16)[name = tensor<string, []>("cast_281")];
            tensor<uint16, []> gather_39_cast_uint16 = gather(axis = gather_39_axis_0, batch_dims = gather_39_batch_dims_0, indices = select_39_to_uint16, validate_indices = gather_39_validate_indices_0, x = var_842_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_39_cast_uint16")];
            tensor<string, []> gather_39_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_39_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_18_values0_0 = const()[name = tensor<string, []>("concat_18_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_18_values1_0 = const()[name = tensor<string, []>("concat_18_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_18_axis_0 = const()[name = tensor<string, []>("concat_18_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_18_interleave_0 = const()[name = tensor<string, []>("concat_18_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_39_cast_uint16_to_int32 = cast(dtype = gather_39_cast_uint16_to_int32_dtype_0, x = gather_39_cast_uint16)[name = tensor<string, []>("cast_280")];
            tensor<int32, [3]> concat_18 = concat(axis = concat_18_axis_0, interleave = concat_18_interleave_0, values = (concat_18_values0_0, concat_18_values1_0, gather_39_cast_uint16_to_int32))[name = tensor<string, []>("concat_18")];
            tensor<int32, [3]> var_843_begin_0 = const()[name = tensor<string, []>("op_843_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_843_end_mask_0 = const()[name = tensor<string, []>("op_843_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_843_cast_fp16 = slice_by_index(begin = var_843_begin_0, end = concat_18, end_mask = var_843_end_mask_0, x = seg_35_cast_fp16)[name = tensor<string, []>("op_843_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_243_cast_fp16 = add(x = var_829_cast_fp16, y = var_843_cast_fp16)[name = tensor<string, []>("input_243_cast_fp16")];
            tensor<string, []> input_245_pad_type_0 = const()[name = tensor<string, []>("input_245_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_245_strides_0 = const()[name = tensor<string, []>("input_245_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_245_pad_0 = const()[name = tensor<string, []>("input_245_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_245_dilations_0 = const()[name = tensor<string, []>("input_245_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_245_groups_0 = const()[name = tensor<string, []>("input_245_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd9_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd9_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1586112)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd9_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd9_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1602560)))];
            tensor<fp16, [1, 64, ?]> input_245_cast_fp16 = conv(bias = net_xvector_block1_tdnnd9_cam_layer_linear1_bias_to_fp16, dilations = input_245_dilations_0, groups = input_245_groups_0, pad = input_245_pad_0, pad_type = input_245_pad_type_0, strides = input_245_strides_0, weight = net_xvector_block1_tdnnd9_cam_layer_linear1_weight_to_fp16, x = input_243_cast_fp16)[name = tensor<string, []>("input_245_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_247_cast_fp16 = relu(x = input_245_cast_fp16)[name = tensor<string, []>("input_247_cast_fp16")];
            tensor<string, []> input_249_pad_type_0 = const()[name = tensor<string, []>("input_249_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_249_strides_0 = const()[name = tensor<string, []>("input_249_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_249_pad_0 = const()[name = tensor<string, []>("input_249_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_249_dilations_0 = const()[name = tensor<string, []>("input_249_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_249_groups_0 = const()[name = tensor<string, []>("input_249_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd9_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd9_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1602752)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd9_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd9_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1606912)))];
            tensor<fp16, [1, 32, ?]> input_249_cast_fp16 = conv(bias = net_xvector_block1_tdnnd9_cam_layer_linear2_bias_to_fp16, dilations = input_249_dilations_0, groups = input_249_groups_0, pad = input_249_pad_0, pad_type = input_249_pad_type_0, strides = input_249_strides_0, weight = net_xvector_block1_tdnnd9_cam_layer_linear2_weight_to_fp16, x = input_247_cast_fp16)[name = tensor<string, []>("input_249_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_17_cast_fp16 = sigmoid(x = input_249_cast_fp16)[name = tensor<string, []>("m_17_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_861_cast_fp16 = mul(x = y_17_cast_fp16, y = m_17_cast_fp16)[name = tensor<string, []>("op_861_cast_fp16")];
            tensor<bool, []> input_251_interleave_0 = const()[name = tensor<string, []>("input_251_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 416, ?]> input_251_cast_fp16 = concat(axis = var_11, interleave = input_251_interleave_0, values = (input_231_cast_fp16, var_861_cast_fp16))[name = tensor<string, []>("input_251_cast_fp16")];
            tensor<fp16, [416]> net_xvector_block1_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [416]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1607040)))];
            tensor<fp16, [416]> net_xvector_block1_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [416]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1607936)))];
            tensor<fp16, [416]> net_xvector_block1_tdnnd10_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd10_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [416]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1608832)))];
            tensor<fp16, [416]> net_xvector_block1_tdnnd10_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd10_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [416]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1609728)))];
            tensor<fp16, [1, 416, ?]> input_253_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd10_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd10_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16, x = input_251_cast_fp16)[name = tensor<string, []>("input_253_cast_fp16")];
            tensor<fp16, [1, 416, ?]> input_255_cast_fp16 = relu(x = input_253_cast_fp16)[name = tensor<string, []>("input_255_cast_fp16")];
            tensor<string, []> input_257_pad_type_0 = const()[name = tensor<string, []>("input_257_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_257_strides_0 = const()[name = tensor<string, []>("input_257_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_257_pad_0 = const()[name = tensor<string, []>("input_257_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_257_dilations_0 = const()[name = tensor<string, []>("input_257_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_257_groups_0 = const()[name = tensor<string, []>("input_257_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 416, 1]> const_44_to_fp16 = const()[name = tensor<string, []>("const_44_to_fp16"), val = tensor<fp16, [128, 416, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1610624)))];
            tensor<fp16, [128]> const_45_to_fp16 = const()[name = tensor<string, []>("const_45_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1717184)))];
            tensor<fp16, [1, 128, ?]> input_259_cast_fp16 = conv(bias = const_45_to_fp16, dilations = input_257_dilations_0, groups = input_257_groups_0, pad = input_257_pad_0, pad_type = input_257_pad_type_0, strides = input_257_strides_0, weight = const_44_to_fp16, x = input_255_cast_fp16)[name = tensor<string, []>("input_259_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_261_cast_fp16 = relu(x = input_259_cast_fp16)[name = tensor<string, []>("input_261_cast_fp16")];
            tensor<string, []> y_19_pad_type_0 = const()[name = tensor<string, []>("y_19_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_19_pad_0 = const()[name = tensor<string, []>("y_19_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_19_strides_0 = const()[name = tensor<string, []>("y_19_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_19_dilations_0 = const()[name = tensor<string, []>("y_19_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_19_groups_0 = const()[name = tensor<string, []>("y_19_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd10_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd10_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1717504)))];
            tensor<fp16, [1, 32, ?]> y_19_cast_fp16 = conv(dilations = y_19_dilations_0, groups = y_19_groups_0, pad = y_19_pad_0, pad_type = y_19_pad_type_0, strides = y_19_strides_0, weight = net_xvector_block1_tdnnd10_cam_layer_linear_local_weight_to_fp16, x = input_261_cast_fp16)[name = tensor<string, []>("y_19_cast_fp16")];
            tensor<int32, [1]> var_898_axes_0 = const()[name = tensor<string, []>("op_898_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_898_keep_dims_0 = const()[name = tensor<string, []>("op_898_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_898_cast_fp16 = reduce_mean(axes = var_898_axes_0, keep_dims = var_898_keep_dims_0, x = input_261_cast_fp16)[name = tensor<string, []>("op_898_cast_fp16")];
            tensor<int32, [1]> var_899 = const()[name = tensor<string, []>("op_899"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_900 = const()[name = tensor<string, []>("op_900"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_37_pad_type_0 = const()[name = tensor<string, []>("seg_37_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_37_pad_0 = const()[name = tensor<string, []>("seg_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_37_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_37_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_37_ceil_mode_0 = const()[name = tensor<string, []>("seg_37_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_37_cast_fp16 = avg_pool(ceil_mode = seg_37_ceil_mode_0, exclude_padding_from_average = seg_37_exclude_padding_from_average_0, kernel_sizes = var_899, pad = seg_37_pad_0, pad_type = seg_37_pad_type_0, strides = var_900, x = input_261_cast_fp16)[name = tensor<string, []>("seg_37_cast_fp16")];
            tensor<int32, [3]> var_903_shape_cast_fp16 = shape(x = seg_37_cast_fp16)[name = tensor<string, []>("op_903_shape_cast_fp16")];
            tensor<int32, []> gather_40 = const()[name = tensor<string, []>("gather_40"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_41 = const()[name = tensor<string, []>("gather_41"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_42_axis_0 = const()[name = tensor<string, []>("gather_42_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_42_batch_dims_0 = const()[name = tensor<string, []>("gather_42_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_42_validate_indices_0 = const()[name = tensor<string, []>("gather_42_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_903_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_903_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_42_to_uint16 = const()[name = tensor<string, []>("select_42_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_903_shape_cast_fp16_to_uint16 = cast(dtype = var_903_shape_cast_fp16_to_uint16_dtype_0, x = var_903_shape_cast_fp16)[name = tensor<string, []>("cast_279")];
            tensor<uint16, []> gather_42_cast_uint16 = gather(axis = gather_42_axis_0, batch_dims = gather_42_batch_dims_0, indices = select_42_to_uint16, validate_indices = gather_42_validate_indices_0, x = var_903_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_42_cast_uint16")];
            tensor<string, []> gather_42_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_42_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_906_axes_0 = const()[name = tensor<string, []>("op_906_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_906_cast_fp16 = expand_dims(axes = var_906_axes_0, x = seg_37_cast_fp16)[name = tensor<string, []>("op_906_cast_fp16")];
            tensor<int32, []> concat_19_axis_0 = const()[name = tensor<string, []>("concat_19_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_19_interleave_0 = const()[name = tensor<string, []>("concat_19_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_42_cast_uint16_to_int32 = cast(dtype = gather_42_cast_uint16_to_int32_dtype_0, x = gather_42_cast_uint16)[name = tensor<string, []>("cast_278")];
            tensor<int32, [4]> concat_19 = concat(axis = concat_19_axis_0, interleave = concat_19_interleave_0, values = (gather_40, gather_41, gather_42_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_19")];
            tensor<int32, [4]> shape_52_cast_fp16 = shape(x = var_906_cast_fp16)[name = tensor<string, []>("shape_52_cast_fp16")];
            tensor<int32, [4]> real_div_9 = real_div(x = concat_19, y = shape_52_cast_fp16)[name = tensor<string, []>("real_div_9")];
            tensor<fp16, [?, ?, ?, ?]> var_908_cast_fp16 = tile(reps = real_div_9, x = var_906_cast_fp16)[name = tensor<string, []>("op_908_cast_fp16")];
            tensor<int32, [3]> var_909 = const()[name = tensor<string, []>("op_909"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_39_cast_fp16 = reshape(shape = var_909, x = var_908_cast_fp16)[name = tensor<string, []>("seg_39_cast_fp16")];
            tensor<int32, [3]> var_911_shape_cast_fp16 = shape(x = input_261_cast_fp16)[name = tensor<string, []>("op_911_shape_cast_fp16")];
            tensor<int32, []> gather_43_axis_0 = const()[name = tensor<string, []>("gather_43_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_43_batch_dims_0 = const()[name = tensor<string, []>("gather_43_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_43_validate_indices_0 = const()[name = tensor<string, []>("gather_43_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_911_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_911_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_43_to_uint16 = const()[name = tensor<string, []>("select_43_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_911_shape_cast_fp16_to_uint16 = cast(dtype = var_911_shape_cast_fp16_to_uint16_dtype_0, x = var_911_shape_cast_fp16)[name = tensor<string, []>("cast_277")];
            tensor<uint16, []> gather_43_cast_uint16 = gather(axis = gather_43_axis_0, batch_dims = gather_43_batch_dims_0, indices = select_43_to_uint16, validate_indices = gather_43_validate_indices_0, x = var_911_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_43_cast_uint16")];
            tensor<string, []> gather_43_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_43_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_20_values0_0 = const()[name = tensor<string, []>("concat_20_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_20_values1_0 = const()[name = tensor<string, []>("concat_20_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_20_axis_0 = const()[name = tensor<string, []>("concat_20_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_20_interleave_0 = const()[name = tensor<string, []>("concat_20_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_43_cast_uint16_to_int32 = cast(dtype = gather_43_cast_uint16_to_int32_dtype_0, x = gather_43_cast_uint16)[name = tensor<string, []>("cast_276")];
            tensor<int32, [3]> concat_20 = concat(axis = concat_20_axis_0, interleave = concat_20_interleave_0, values = (concat_20_values0_0, concat_20_values1_0, gather_43_cast_uint16_to_int32))[name = tensor<string, []>("concat_20")];
            tensor<int32, [3]> var_912_begin_0 = const()[name = tensor<string, []>("op_912_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_912_end_mask_0 = const()[name = tensor<string, []>("op_912_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_912_cast_fp16 = slice_by_index(begin = var_912_begin_0, end = concat_20, end_mask = var_912_end_mask_0, x = seg_39_cast_fp16)[name = tensor<string, []>("op_912_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_263_cast_fp16 = add(x = var_898_cast_fp16, y = var_912_cast_fp16)[name = tensor<string, []>("input_263_cast_fp16")];
            tensor<string, []> input_265_pad_type_0 = const()[name = tensor<string, []>("input_265_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_265_strides_0 = const()[name = tensor<string, []>("input_265_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_265_pad_0 = const()[name = tensor<string, []>("input_265_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_265_dilations_0 = const()[name = tensor<string, []>("input_265_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_265_groups_0 = const()[name = tensor<string, []>("input_265_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd10_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd10_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1742144)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd10_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd10_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1758592)))];
            tensor<fp16, [1, 64, ?]> input_265_cast_fp16 = conv(bias = net_xvector_block1_tdnnd10_cam_layer_linear1_bias_to_fp16, dilations = input_265_dilations_0, groups = input_265_groups_0, pad = input_265_pad_0, pad_type = input_265_pad_type_0, strides = input_265_strides_0, weight = net_xvector_block1_tdnnd10_cam_layer_linear1_weight_to_fp16, x = input_263_cast_fp16)[name = tensor<string, []>("input_265_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_267_cast_fp16 = relu(x = input_265_cast_fp16)[name = tensor<string, []>("input_267_cast_fp16")];
            tensor<string, []> input_269_pad_type_0 = const()[name = tensor<string, []>("input_269_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_269_strides_0 = const()[name = tensor<string, []>("input_269_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_269_pad_0 = const()[name = tensor<string, []>("input_269_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_269_dilations_0 = const()[name = tensor<string, []>("input_269_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_269_groups_0 = const()[name = tensor<string, []>("input_269_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd10_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd10_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1758784)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd10_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd10_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1762944)))];
            tensor<fp16, [1, 32, ?]> input_269_cast_fp16 = conv(bias = net_xvector_block1_tdnnd10_cam_layer_linear2_bias_to_fp16, dilations = input_269_dilations_0, groups = input_269_groups_0, pad = input_269_pad_0, pad_type = input_269_pad_type_0, strides = input_269_strides_0, weight = net_xvector_block1_tdnnd10_cam_layer_linear2_weight_to_fp16, x = input_267_cast_fp16)[name = tensor<string, []>("input_269_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_19_cast_fp16 = sigmoid(x = input_269_cast_fp16)[name = tensor<string, []>("m_19_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_930_cast_fp16 = mul(x = y_19_cast_fp16, y = m_19_cast_fp16)[name = tensor<string, []>("op_930_cast_fp16")];
            tensor<bool, []> input_271_interleave_0 = const()[name = tensor<string, []>("input_271_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 448, ?]> input_271_cast_fp16 = concat(axis = var_11, interleave = input_271_interleave_0, values = (input_251_cast_fp16, var_930_cast_fp16))[name = tensor<string, []>("input_271_cast_fp16")];
            tensor<fp16, [448]> net_xvector_block1_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [448]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1763072)))];
            tensor<fp16, [448]> net_xvector_block1_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [448]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1764032)))];
            tensor<fp16, [448]> net_xvector_block1_tdnnd11_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd11_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [448]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1764992)))];
            tensor<fp16, [448]> net_xvector_block1_tdnnd11_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd11_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [448]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1765952)))];
            tensor<fp16, [1, 448, ?]> input_273_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd11_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd11_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16, x = input_271_cast_fp16)[name = tensor<string, []>("input_273_cast_fp16")];
            tensor<fp16, [1, 448, ?]> input_275_cast_fp16 = relu(x = input_273_cast_fp16)[name = tensor<string, []>("input_275_cast_fp16")];
            tensor<string, []> input_277_pad_type_0 = const()[name = tensor<string, []>("input_277_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_277_strides_0 = const()[name = tensor<string, []>("input_277_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_277_pad_0 = const()[name = tensor<string, []>("input_277_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_277_dilations_0 = const()[name = tensor<string, []>("input_277_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_277_groups_0 = const()[name = tensor<string, []>("input_277_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 448, 1]> const_46_to_fp16 = const()[name = tensor<string, []>("const_46_to_fp16"), val = tensor<fp16, [128, 448, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1766912)))];
            tensor<fp16, [128]> const_47_to_fp16 = const()[name = tensor<string, []>("const_47_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1881664)))];
            tensor<fp16, [1, 128, ?]> input_279_cast_fp16 = conv(bias = const_47_to_fp16, dilations = input_277_dilations_0, groups = input_277_groups_0, pad = input_277_pad_0, pad_type = input_277_pad_type_0, strides = input_277_strides_0, weight = const_46_to_fp16, x = input_275_cast_fp16)[name = tensor<string, []>("input_279_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_281_cast_fp16 = relu(x = input_279_cast_fp16)[name = tensor<string, []>("input_281_cast_fp16")];
            tensor<string, []> y_21_pad_type_0 = const()[name = tensor<string, []>("y_21_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_21_pad_0 = const()[name = tensor<string, []>("y_21_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_21_strides_0 = const()[name = tensor<string, []>("y_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_21_dilations_0 = const()[name = tensor<string, []>("y_21_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_21_groups_0 = const()[name = tensor<string, []>("y_21_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd11_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd11_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1881984)))];
            tensor<fp16, [1, 32, ?]> y_21_cast_fp16 = conv(dilations = y_21_dilations_0, groups = y_21_groups_0, pad = y_21_pad_0, pad_type = y_21_pad_type_0, strides = y_21_strides_0, weight = net_xvector_block1_tdnnd11_cam_layer_linear_local_weight_to_fp16, x = input_281_cast_fp16)[name = tensor<string, []>("y_21_cast_fp16")];
            tensor<int32, [1]> var_967_axes_0 = const()[name = tensor<string, []>("op_967_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_967_keep_dims_0 = const()[name = tensor<string, []>("op_967_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_967_cast_fp16 = reduce_mean(axes = var_967_axes_0, keep_dims = var_967_keep_dims_0, x = input_281_cast_fp16)[name = tensor<string, []>("op_967_cast_fp16")];
            tensor<int32, [1]> var_968 = const()[name = tensor<string, []>("op_968"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_969 = const()[name = tensor<string, []>("op_969"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_41_pad_type_0 = const()[name = tensor<string, []>("seg_41_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_41_pad_0 = const()[name = tensor<string, []>("seg_41_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_41_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_41_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_41_ceil_mode_0 = const()[name = tensor<string, []>("seg_41_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_41_cast_fp16 = avg_pool(ceil_mode = seg_41_ceil_mode_0, exclude_padding_from_average = seg_41_exclude_padding_from_average_0, kernel_sizes = var_968, pad = seg_41_pad_0, pad_type = seg_41_pad_type_0, strides = var_969, x = input_281_cast_fp16)[name = tensor<string, []>("seg_41_cast_fp16")];
            tensor<int32, [3]> var_972_shape_cast_fp16 = shape(x = seg_41_cast_fp16)[name = tensor<string, []>("op_972_shape_cast_fp16")];
            tensor<int32, []> gather_44 = const()[name = tensor<string, []>("gather_44"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_45 = const()[name = tensor<string, []>("gather_45"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_46_axis_0 = const()[name = tensor<string, []>("gather_46_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_46_batch_dims_0 = const()[name = tensor<string, []>("gather_46_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_46_validate_indices_0 = const()[name = tensor<string, []>("gather_46_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_972_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_972_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_46_to_uint16 = const()[name = tensor<string, []>("select_46_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_972_shape_cast_fp16_to_uint16 = cast(dtype = var_972_shape_cast_fp16_to_uint16_dtype_0, x = var_972_shape_cast_fp16)[name = tensor<string, []>("cast_275")];
            tensor<uint16, []> gather_46_cast_uint16 = gather(axis = gather_46_axis_0, batch_dims = gather_46_batch_dims_0, indices = select_46_to_uint16, validate_indices = gather_46_validate_indices_0, x = var_972_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_46_cast_uint16")];
            tensor<string, []> gather_46_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_46_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_975_axes_0 = const()[name = tensor<string, []>("op_975_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_975_cast_fp16 = expand_dims(axes = var_975_axes_0, x = seg_41_cast_fp16)[name = tensor<string, []>("op_975_cast_fp16")];
            tensor<int32, []> concat_21_axis_0 = const()[name = tensor<string, []>("concat_21_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_21_interleave_0 = const()[name = tensor<string, []>("concat_21_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_46_cast_uint16_to_int32 = cast(dtype = gather_46_cast_uint16_to_int32_dtype_0, x = gather_46_cast_uint16)[name = tensor<string, []>("cast_274")];
            tensor<int32, [4]> concat_21 = concat(axis = concat_21_axis_0, interleave = concat_21_interleave_0, values = (gather_44, gather_45, gather_46_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_21")];
            tensor<int32, [4]> shape_57_cast_fp16 = shape(x = var_975_cast_fp16)[name = tensor<string, []>("shape_57_cast_fp16")];
            tensor<int32, [4]> real_div_10 = real_div(x = concat_21, y = shape_57_cast_fp16)[name = tensor<string, []>("real_div_10")];
            tensor<fp16, [?, ?, ?, ?]> var_977_cast_fp16 = tile(reps = real_div_10, x = var_975_cast_fp16)[name = tensor<string, []>("op_977_cast_fp16")];
            tensor<int32, [3]> var_978 = const()[name = tensor<string, []>("op_978"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_43_cast_fp16 = reshape(shape = var_978, x = var_977_cast_fp16)[name = tensor<string, []>("seg_43_cast_fp16")];
            tensor<int32, [3]> var_980_shape_cast_fp16 = shape(x = input_281_cast_fp16)[name = tensor<string, []>("op_980_shape_cast_fp16")];
            tensor<int32, []> gather_47_axis_0 = const()[name = tensor<string, []>("gather_47_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_47_batch_dims_0 = const()[name = tensor<string, []>("gather_47_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_47_validate_indices_0 = const()[name = tensor<string, []>("gather_47_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_980_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_980_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_47_to_uint16 = const()[name = tensor<string, []>("select_47_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_980_shape_cast_fp16_to_uint16 = cast(dtype = var_980_shape_cast_fp16_to_uint16_dtype_0, x = var_980_shape_cast_fp16)[name = tensor<string, []>("cast_273")];
            tensor<uint16, []> gather_47_cast_uint16 = gather(axis = gather_47_axis_0, batch_dims = gather_47_batch_dims_0, indices = select_47_to_uint16, validate_indices = gather_47_validate_indices_0, x = var_980_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_47_cast_uint16")];
            tensor<string, []> gather_47_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_47_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_22_values0_0 = const()[name = tensor<string, []>("concat_22_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_22_values1_0 = const()[name = tensor<string, []>("concat_22_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_22_axis_0 = const()[name = tensor<string, []>("concat_22_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_22_interleave_0 = const()[name = tensor<string, []>("concat_22_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_47_cast_uint16_to_int32 = cast(dtype = gather_47_cast_uint16_to_int32_dtype_0, x = gather_47_cast_uint16)[name = tensor<string, []>("cast_272")];
            tensor<int32, [3]> concat_22 = concat(axis = concat_22_axis_0, interleave = concat_22_interleave_0, values = (concat_22_values0_0, concat_22_values1_0, gather_47_cast_uint16_to_int32))[name = tensor<string, []>("concat_22")];
            tensor<int32, [3]> var_981_begin_0 = const()[name = tensor<string, []>("op_981_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_981_end_mask_0 = const()[name = tensor<string, []>("op_981_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_981_cast_fp16 = slice_by_index(begin = var_981_begin_0, end = concat_22, end_mask = var_981_end_mask_0, x = seg_43_cast_fp16)[name = tensor<string, []>("op_981_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_283_cast_fp16 = add(x = var_967_cast_fp16, y = var_981_cast_fp16)[name = tensor<string, []>("input_283_cast_fp16")];
            tensor<string, []> input_285_pad_type_0 = const()[name = tensor<string, []>("input_285_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_285_strides_0 = const()[name = tensor<string, []>("input_285_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_285_pad_0 = const()[name = tensor<string, []>("input_285_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_285_dilations_0 = const()[name = tensor<string, []>("input_285_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_285_groups_0 = const()[name = tensor<string, []>("input_285_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd11_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd11_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1906624)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd11_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd11_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1923072)))];
            tensor<fp16, [1, 64, ?]> input_285_cast_fp16 = conv(bias = net_xvector_block1_tdnnd11_cam_layer_linear1_bias_to_fp16, dilations = input_285_dilations_0, groups = input_285_groups_0, pad = input_285_pad_0, pad_type = input_285_pad_type_0, strides = input_285_strides_0, weight = net_xvector_block1_tdnnd11_cam_layer_linear1_weight_to_fp16, x = input_283_cast_fp16)[name = tensor<string, []>("input_285_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_287_cast_fp16 = relu(x = input_285_cast_fp16)[name = tensor<string, []>("input_287_cast_fp16")];
            tensor<string, []> input_289_pad_type_0 = const()[name = tensor<string, []>("input_289_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_289_strides_0 = const()[name = tensor<string, []>("input_289_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_289_pad_0 = const()[name = tensor<string, []>("input_289_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_289_dilations_0 = const()[name = tensor<string, []>("input_289_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_289_groups_0 = const()[name = tensor<string, []>("input_289_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd11_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd11_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1923264)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd11_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd11_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1927424)))];
            tensor<fp16, [1, 32, ?]> input_289_cast_fp16 = conv(bias = net_xvector_block1_tdnnd11_cam_layer_linear2_bias_to_fp16, dilations = input_289_dilations_0, groups = input_289_groups_0, pad = input_289_pad_0, pad_type = input_289_pad_type_0, strides = input_289_strides_0, weight = net_xvector_block1_tdnnd11_cam_layer_linear2_weight_to_fp16, x = input_287_cast_fp16)[name = tensor<string, []>("input_289_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_21_cast_fp16 = sigmoid(x = input_289_cast_fp16)[name = tensor<string, []>("m_21_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_999_cast_fp16 = mul(x = y_21_cast_fp16, y = m_21_cast_fp16)[name = tensor<string, []>("op_999_cast_fp16")];
            tensor<bool, []> input_291_interleave_0 = const()[name = tensor<string, []>("input_291_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 480, ?]> input_291_cast_fp16 = concat(axis = var_11, interleave = input_291_interleave_0, values = (input_271_cast_fp16, var_999_cast_fp16))[name = tensor<string, []>("input_291_cast_fp16")];
            tensor<fp16, [480]> net_xvector_block1_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1927552)))];
            tensor<fp16, [480]> net_xvector_block1_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1928576)))];
            tensor<fp16, [480]> net_xvector_block1_tdnnd12_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd12_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1929600)))];
            tensor<fp16, [480]> net_xvector_block1_tdnnd12_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd12_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1930624)))];
            tensor<fp16, [1, 480, ?]> input_293_cast_fp16 = batch_norm(beta = net_xvector_block1_tdnnd12_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block1_tdnnd12_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block1_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block1_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16, x = input_291_cast_fp16)[name = tensor<string, []>("input_293_cast_fp16")];
            tensor<fp16, [1, 480, ?]> input_295_cast_fp16 = relu(x = input_293_cast_fp16)[name = tensor<string, []>("input_295_cast_fp16")];
            tensor<string, []> input_297_pad_type_0 = const()[name = tensor<string, []>("input_297_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_297_strides_0 = const()[name = tensor<string, []>("input_297_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_297_pad_0 = const()[name = tensor<string, []>("input_297_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_297_dilations_0 = const()[name = tensor<string, []>("input_297_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_297_groups_0 = const()[name = tensor<string, []>("input_297_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 480, 1]> const_48_to_fp16 = const()[name = tensor<string, []>("const_48_to_fp16"), val = tensor<fp16, [128, 480, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1931648)))];
            tensor<fp16, [128]> const_49_to_fp16 = const()[name = tensor<string, []>("const_49_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2054592)))];
            tensor<fp16, [1, 128, ?]> input_299_cast_fp16 = conv(bias = const_49_to_fp16, dilations = input_297_dilations_0, groups = input_297_groups_0, pad = input_297_pad_0, pad_type = input_297_pad_type_0, strides = input_297_strides_0, weight = const_48_to_fp16, x = input_295_cast_fp16)[name = tensor<string, []>("input_299_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_301_cast_fp16 = relu(x = input_299_cast_fp16)[name = tensor<string, []>("input_301_cast_fp16")];
            tensor<string, []> y_23_pad_type_0 = const()[name = tensor<string, []>("y_23_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_23_pad_0 = const()[name = tensor<string, []>("y_23_pad_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [1]> y_23_strides_0 = const()[name = tensor<string, []>("y_23_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> y_23_dilations_0 = const()[name = tensor<string, []>("y_23_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_23_groups_0 = const()[name = tensor<string, []>("y_23_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block1_tdnnd12_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd12_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2054912)))];
            tensor<fp16, [1, 32, ?]> y_23_cast_fp16 = conv(dilations = y_23_dilations_0, groups = y_23_groups_0, pad = y_23_pad_0, pad_type = y_23_pad_type_0, strides = y_23_strides_0, weight = net_xvector_block1_tdnnd12_cam_layer_linear_local_weight_to_fp16, x = input_301_cast_fp16)[name = tensor<string, []>("y_23_cast_fp16")];
            tensor<int32, [1]> var_1036_axes_0 = const()[name = tensor<string, []>("op_1036_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1036_keep_dims_0 = const()[name = tensor<string, []>("op_1036_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1036_cast_fp16 = reduce_mean(axes = var_1036_axes_0, keep_dims = var_1036_keep_dims_0, x = input_301_cast_fp16)[name = tensor<string, []>("op_1036_cast_fp16")];
            tensor<int32, [1]> var_1037 = const()[name = tensor<string, []>("op_1037"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1038 = const()[name = tensor<string, []>("op_1038"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_45_pad_type_0 = const()[name = tensor<string, []>("seg_45_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_45_pad_0 = const()[name = tensor<string, []>("seg_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_45_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_45_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_45_ceil_mode_0 = const()[name = tensor<string, []>("seg_45_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_45_cast_fp16 = avg_pool(ceil_mode = seg_45_ceil_mode_0, exclude_padding_from_average = seg_45_exclude_padding_from_average_0, kernel_sizes = var_1037, pad = seg_45_pad_0, pad_type = seg_45_pad_type_0, strides = var_1038, x = input_301_cast_fp16)[name = tensor<string, []>("seg_45_cast_fp16")];
            tensor<int32, [3]> var_1041_shape_cast_fp16 = shape(x = seg_45_cast_fp16)[name = tensor<string, []>("op_1041_shape_cast_fp16")];
            tensor<int32, []> gather_48 = const()[name = tensor<string, []>("gather_48"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_49 = const()[name = tensor<string, []>("gather_49"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_50_axis_0 = const()[name = tensor<string, []>("gather_50_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_50_batch_dims_0 = const()[name = tensor<string, []>("gather_50_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_50_validate_indices_0 = const()[name = tensor<string, []>("gather_50_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1041_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1041_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_50_to_uint16 = const()[name = tensor<string, []>("select_50_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1041_shape_cast_fp16_to_uint16 = cast(dtype = var_1041_shape_cast_fp16_to_uint16_dtype_0, x = var_1041_shape_cast_fp16)[name = tensor<string, []>("cast_271")];
            tensor<uint16, []> gather_50_cast_uint16 = gather(axis = gather_50_axis_0, batch_dims = gather_50_batch_dims_0, indices = select_50_to_uint16, validate_indices = gather_50_validate_indices_0, x = var_1041_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_50_cast_uint16")];
            tensor<string, []> gather_50_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_50_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1044_axes_0 = const()[name = tensor<string, []>("op_1044_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1044_cast_fp16 = expand_dims(axes = var_1044_axes_0, x = seg_45_cast_fp16)[name = tensor<string, []>("op_1044_cast_fp16")];
            tensor<int32, []> concat_23_axis_0 = const()[name = tensor<string, []>("concat_23_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_23_interleave_0 = const()[name = tensor<string, []>("concat_23_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_50_cast_uint16_to_int32 = cast(dtype = gather_50_cast_uint16_to_int32_dtype_0, x = gather_50_cast_uint16)[name = tensor<string, []>("cast_270")];
            tensor<int32, [4]> concat_23 = concat(axis = concat_23_axis_0, interleave = concat_23_interleave_0, values = (gather_48, gather_49, gather_50_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_23")];
            tensor<int32, [4]> shape_62_cast_fp16 = shape(x = var_1044_cast_fp16)[name = tensor<string, []>("shape_62_cast_fp16")];
            tensor<int32, [4]> real_div_11 = real_div(x = concat_23, y = shape_62_cast_fp16)[name = tensor<string, []>("real_div_11")];
            tensor<fp16, [?, ?, ?, ?]> var_1046_cast_fp16 = tile(reps = real_div_11, x = var_1044_cast_fp16)[name = tensor<string, []>("op_1046_cast_fp16")];
            tensor<int32, [3]> var_1047 = const()[name = tensor<string, []>("op_1047"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_47_cast_fp16 = reshape(shape = var_1047, x = var_1046_cast_fp16)[name = tensor<string, []>("seg_47_cast_fp16")];
            tensor<int32, [3]> var_1049_shape_cast_fp16 = shape(x = input_301_cast_fp16)[name = tensor<string, []>("op_1049_shape_cast_fp16")];
            tensor<int32, []> gather_51_axis_0 = const()[name = tensor<string, []>("gather_51_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_51_batch_dims_0 = const()[name = tensor<string, []>("gather_51_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_51_validate_indices_0 = const()[name = tensor<string, []>("gather_51_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1049_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1049_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_51_to_uint16 = const()[name = tensor<string, []>("select_51_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1049_shape_cast_fp16_to_uint16 = cast(dtype = var_1049_shape_cast_fp16_to_uint16_dtype_0, x = var_1049_shape_cast_fp16)[name = tensor<string, []>("cast_269")];
            tensor<uint16, []> gather_51_cast_uint16 = gather(axis = gather_51_axis_0, batch_dims = gather_51_batch_dims_0, indices = select_51_to_uint16, validate_indices = gather_51_validate_indices_0, x = var_1049_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_51_cast_uint16")];
            tensor<string, []> gather_51_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_51_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_24_values0_0 = const()[name = tensor<string, []>("concat_24_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_24_values1_0 = const()[name = tensor<string, []>("concat_24_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_24_axis_0 = const()[name = tensor<string, []>("concat_24_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_24_interleave_0 = const()[name = tensor<string, []>("concat_24_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_51_cast_uint16_to_int32 = cast(dtype = gather_51_cast_uint16_to_int32_dtype_0, x = gather_51_cast_uint16)[name = tensor<string, []>("cast_268")];
            tensor<int32, [3]> concat_24 = concat(axis = concat_24_axis_0, interleave = concat_24_interleave_0, values = (concat_24_values0_0, concat_24_values1_0, gather_51_cast_uint16_to_int32))[name = tensor<string, []>("concat_24")];
            tensor<int32, [3]> var_1050_begin_0 = const()[name = tensor<string, []>("op_1050_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1050_end_mask_0 = const()[name = tensor<string, []>("op_1050_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1050_cast_fp16 = slice_by_index(begin = var_1050_begin_0, end = concat_24, end_mask = var_1050_end_mask_0, x = seg_47_cast_fp16)[name = tensor<string, []>("op_1050_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_303_cast_fp16 = add(x = var_1036_cast_fp16, y = var_1050_cast_fp16)[name = tensor<string, []>("input_303_cast_fp16")];
            tensor<string, []> input_305_pad_type_0 = const()[name = tensor<string, []>("input_305_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_305_strides_0 = const()[name = tensor<string, []>("input_305_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_305_pad_0 = const()[name = tensor<string, []>("input_305_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_305_dilations_0 = const()[name = tensor<string, []>("input_305_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_305_groups_0 = const()[name = tensor<string, []>("input_305_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block1_tdnnd12_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd12_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2079552)))];
            tensor<fp16, [64]> net_xvector_block1_tdnnd12_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd12_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2096000)))];
            tensor<fp16, [1, 64, ?]> input_305_cast_fp16 = conv(bias = net_xvector_block1_tdnnd12_cam_layer_linear1_bias_to_fp16, dilations = input_305_dilations_0, groups = input_305_groups_0, pad = input_305_pad_0, pad_type = input_305_pad_type_0, strides = input_305_strides_0, weight = net_xvector_block1_tdnnd12_cam_layer_linear1_weight_to_fp16, x = input_303_cast_fp16)[name = tensor<string, []>("input_305_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_307_cast_fp16 = relu(x = input_305_cast_fp16)[name = tensor<string, []>("input_307_cast_fp16")];
            tensor<string, []> input_309_pad_type_0 = const()[name = tensor<string, []>("input_309_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_309_strides_0 = const()[name = tensor<string, []>("input_309_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_309_pad_0 = const()[name = tensor<string, []>("input_309_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_309_dilations_0 = const()[name = tensor<string, []>("input_309_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_309_groups_0 = const()[name = tensor<string, []>("input_309_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block1_tdnnd12_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd12_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2096192)))];
            tensor<fp16, [32]> net_xvector_block1_tdnnd12_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block1_tdnnd12_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2100352)))];
            tensor<fp16, [1, 32, ?]> input_309_cast_fp16 = conv(bias = net_xvector_block1_tdnnd12_cam_layer_linear2_bias_to_fp16, dilations = input_309_dilations_0, groups = input_309_groups_0, pad = input_309_pad_0, pad_type = input_309_pad_type_0, strides = input_309_strides_0, weight = net_xvector_block1_tdnnd12_cam_layer_linear2_weight_to_fp16, x = input_307_cast_fp16)[name = tensor<string, []>("input_309_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_23_cast_fp16 = sigmoid(x = input_309_cast_fp16)[name = tensor<string, []>("m_23_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1068_cast_fp16 = mul(x = y_23_cast_fp16, y = m_23_cast_fp16)[name = tensor<string, []>("op_1068_cast_fp16")];
            tensor<bool, []> input_311_interleave_0 = const()[name = tensor<string, []>("input_311_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 512, ?]> input_311_cast_fp16 = concat(axis = var_11, interleave = input_311_interleave_0, values = (input_291_cast_fp16, var_1068_cast_fp16))[name = tensor<string, []>("input_311_cast_fp16")];
            tensor<fp16, [512]> net_xvector_transit1_nonlinear_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit1_nonlinear_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2100480)))];
            tensor<fp16, [512]> net_xvector_transit1_nonlinear_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit1_nonlinear_batchnorm_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2101568)))];
            tensor<fp16, [512]> net_xvector_transit1_nonlinear_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit1_nonlinear_batchnorm_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2102656)))];
            tensor<fp16, [512]> net_xvector_transit1_nonlinear_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit1_nonlinear_batchnorm_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2103744)))];
            tensor<fp16, [1, 512, ?]> input_313_cast_fp16 = batch_norm(beta = net_xvector_transit1_nonlinear_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_transit1_nonlinear_batchnorm_weight_to_fp16, mean = net_xvector_transit1_nonlinear_batchnorm_running_mean_to_fp16, variance = net_xvector_transit1_nonlinear_batchnorm_running_var_to_fp16, x = input_311_cast_fp16)[name = tensor<string, []>("input_313_cast_fp16")];
            tensor<fp16, [1, 512, ?]> input_315_cast_fp16 = relu(x = input_313_cast_fp16)[name = tensor<string, []>("input_315_cast_fp16")];
            tensor<string, []> input_317_pad_type_0 = const()[name = tensor<string, []>("input_317_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_317_strides_0 = const()[name = tensor<string, []>("input_317_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_317_pad_0 = const()[name = tensor<string, []>("input_317_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_317_dilations_0 = const()[name = tensor<string, []>("input_317_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_317_groups_0 = const()[name = tensor<string, []>("input_317_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 512, 1]> net_xvector_transit1_linear_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit1_linear_weight_to_fp16"), val = tensor<fp16, [256, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2104832)))];
            tensor<fp16, [1, 256, ?]> input_317_cast_fp16 = conv(dilations = input_317_dilations_0, groups = input_317_groups_0, pad = input_317_pad_0, pad_type = input_317_pad_type_0, strides = input_317_strides_0, weight = net_xvector_transit1_linear_weight_to_fp16, x = input_315_cast_fp16)[name = tensor<string, []>("input_317_cast_fp16")];
            tensor<fp16, [256]> net_xvector_block2_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2367040)))];
            tensor<fp16, [256]> net_xvector_block2_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2367616)))];
            tensor<fp16, [256]> net_xvector_block2_tdnnd1_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd1_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2368192)))];
            tensor<fp16, [256]> net_xvector_block2_tdnnd1_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd1_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2368768)))];
            tensor<fp16, [1, 256, ?]> input_319_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd1_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd1_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16, x = input_317_cast_fp16)[name = tensor<string, []>("input_319_cast_fp16")];
            tensor<fp16, [1, 256, ?]> input_321_cast_fp16 = relu(x = input_319_cast_fp16)[name = tensor<string, []>("input_321_cast_fp16")];
            tensor<string, []> input_323_pad_type_0 = const()[name = tensor<string, []>("input_323_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_323_strides_0 = const()[name = tensor<string, []>("input_323_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_323_pad_0 = const()[name = tensor<string, []>("input_323_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_323_dilations_0 = const()[name = tensor<string, []>("input_323_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_323_groups_0 = const()[name = tensor<string, []>("input_323_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 256, 1]> const_50_to_fp16 = const()[name = tensor<string, []>("const_50_to_fp16"), val = tensor<fp16, [128, 256, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2369344)))];
            tensor<fp16, [128]> const_51_to_fp16 = const()[name = tensor<string, []>("const_51_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2434944)))];
            tensor<fp16, [1, 128, ?]> input_325_cast_fp16 = conv(bias = const_51_to_fp16, dilations = input_323_dilations_0, groups = input_323_groups_0, pad = input_323_pad_0, pad_type = input_323_pad_type_0, strides = input_323_strides_0, weight = const_50_to_fp16, x = input_321_cast_fp16)[name = tensor<string, []>("input_325_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_327_cast_fp16 = relu(x = input_325_cast_fp16)[name = tensor<string, []>("input_327_cast_fp16")];
            tensor<string, []> y_25_pad_type_0 = const()[name = tensor<string, []>("y_25_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_25_pad_0 = const()[name = tensor<string, []>("y_25_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_25_dilations_0 = const()[name = tensor<string, []>("y_25_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_25_strides_0 = const()[name = tensor<string, []>("y_25_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_25_groups_0 = const()[name = tensor<string, []>("y_25_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd1_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd1_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2435264)))];
            tensor<fp16, [1, 32, ?]> y_25_cast_fp16 = conv(dilations = y_25_dilations_0, groups = y_25_groups_0, pad = y_25_pad_0, pad_type = y_25_pad_type_0, strides = y_25_strides_0, weight = net_xvector_block2_tdnnd1_cam_layer_linear_local_weight_to_fp16, x = input_327_cast_fp16)[name = tensor<string, []>("y_25_cast_fp16")];
            tensor<int32, [1]> var_1144_axes_0 = const()[name = tensor<string, []>("op_1144_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1144_keep_dims_0 = const()[name = tensor<string, []>("op_1144_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1144_cast_fp16 = reduce_mean(axes = var_1144_axes_0, keep_dims = var_1144_keep_dims_0, x = input_327_cast_fp16)[name = tensor<string, []>("op_1144_cast_fp16")];
            tensor<int32, [1]> var_1145 = const()[name = tensor<string, []>("op_1145"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1146 = const()[name = tensor<string, []>("op_1146"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_49_pad_type_0 = const()[name = tensor<string, []>("seg_49_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_49_pad_0 = const()[name = tensor<string, []>("seg_49_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_49_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_49_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_49_ceil_mode_0 = const()[name = tensor<string, []>("seg_49_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_49_cast_fp16 = avg_pool(ceil_mode = seg_49_ceil_mode_0, exclude_padding_from_average = seg_49_exclude_padding_from_average_0, kernel_sizes = var_1145, pad = seg_49_pad_0, pad_type = seg_49_pad_type_0, strides = var_1146, x = input_327_cast_fp16)[name = tensor<string, []>("seg_49_cast_fp16")];
            tensor<int32, [3]> var_1149_shape_cast_fp16 = shape(x = seg_49_cast_fp16)[name = tensor<string, []>("op_1149_shape_cast_fp16")];
            tensor<int32, []> gather_52 = const()[name = tensor<string, []>("gather_52"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_53 = const()[name = tensor<string, []>("gather_53"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_54_axis_0 = const()[name = tensor<string, []>("gather_54_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_54_batch_dims_0 = const()[name = tensor<string, []>("gather_54_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_54_validate_indices_0 = const()[name = tensor<string, []>("gather_54_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1149_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1149_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_54_to_uint16 = const()[name = tensor<string, []>("select_54_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1149_shape_cast_fp16_to_uint16 = cast(dtype = var_1149_shape_cast_fp16_to_uint16_dtype_0, x = var_1149_shape_cast_fp16)[name = tensor<string, []>("cast_267")];
            tensor<uint16, []> gather_54_cast_uint16 = gather(axis = gather_54_axis_0, batch_dims = gather_54_batch_dims_0, indices = select_54_to_uint16, validate_indices = gather_54_validate_indices_0, x = var_1149_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_54_cast_uint16")];
            tensor<string, []> gather_54_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_54_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1152_axes_0 = const()[name = tensor<string, []>("op_1152_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1152_cast_fp16 = expand_dims(axes = var_1152_axes_0, x = seg_49_cast_fp16)[name = tensor<string, []>("op_1152_cast_fp16")];
            tensor<int32, []> concat_25_axis_0 = const()[name = tensor<string, []>("concat_25_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_25_interleave_0 = const()[name = tensor<string, []>("concat_25_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_54_cast_uint16_to_int32 = cast(dtype = gather_54_cast_uint16_to_int32_dtype_0, x = gather_54_cast_uint16)[name = tensor<string, []>("cast_266")];
            tensor<int32, [4]> concat_25 = concat(axis = concat_25_axis_0, interleave = concat_25_interleave_0, values = (gather_52, gather_53, gather_54_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_25")];
            tensor<int32, [4]> shape_67_cast_fp16 = shape(x = var_1152_cast_fp16)[name = tensor<string, []>("shape_67_cast_fp16")];
            tensor<int32, [4]> real_div_12 = real_div(x = concat_25, y = shape_67_cast_fp16)[name = tensor<string, []>("real_div_12")];
            tensor<fp16, [?, ?, ?, ?]> var_1154_cast_fp16 = tile(reps = real_div_12, x = var_1152_cast_fp16)[name = tensor<string, []>("op_1154_cast_fp16")];
            tensor<int32, [3]> var_1155 = const()[name = tensor<string, []>("op_1155"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_51_cast_fp16 = reshape(shape = var_1155, x = var_1154_cast_fp16)[name = tensor<string, []>("seg_51_cast_fp16")];
            tensor<int32, [3]> var_1157_shape_cast_fp16 = shape(x = input_327_cast_fp16)[name = tensor<string, []>("op_1157_shape_cast_fp16")];
            tensor<int32, []> gather_55_axis_0 = const()[name = tensor<string, []>("gather_55_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_55_batch_dims_0 = const()[name = tensor<string, []>("gather_55_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_55_validate_indices_0 = const()[name = tensor<string, []>("gather_55_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1157_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1157_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_55_to_uint16 = const()[name = tensor<string, []>("select_55_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1157_shape_cast_fp16_to_uint16 = cast(dtype = var_1157_shape_cast_fp16_to_uint16_dtype_0, x = var_1157_shape_cast_fp16)[name = tensor<string, []>("cast_265")];
            tensor<uint16, []> gather_55_cast_uint16 = gather(axis = gather_55_axis_0, batch_dims = gather_55_batch_dims_0, indices = select_55_to_uint16, validate_indices = gather_55_validate_indices_0, x = var_1157_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_55_cast_uint16")];
            tensor<string, []> gather_55_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_55_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_26_values0_0 = const()[name = tensor<string, []>("concat_26_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_26_values1_0 = const()[name = tensor<string, []>("concat_26_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_26_axis_0 = const()[name = tensor<string, []>("concat_26_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_26_interleave_0 = const()[name = tensor<string, []>("concat_26_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_55_cast_uint16_to_int32 = cast(dtype = gather_55_cast_uint16_to_int32_dtype_0, x = gather_55_cast_uint16)[name = tensor<string, []>("cast_264")];
            tensor<int32, [3]> concat_26 = concat(axis = concat_26_axis_0, interleave = concat_26_interleave_0, values = (concat_26_values0_0, concat_26_values1_0, gather_55_cast_uint16_to_int32))[name = tensor<string, []>("concat_26")];
            tensor<int32, [3]> var_1158_begin_0 = const()[name = tensor<string, []>("op_1158_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1158_end_mask_0 = const()[name = tensor<string, []>("op_1158_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1158_cast_fp16 = slice_by_index(begin = var_1158_begin_0, end = concat_26, end_mask = var_1158_end_mask_0, x = seg_51_cast_fp16)[name = tensor<string, []>("op_1158_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_329_cast_fp16 = add(x = var_1144_cast_fp16, y = var_1158_cast_fp16)[name = tensor<string, []>("input_329_cast_fp16")];
            tensor<string, []> input_331_pad_type_0 = const()[name = tensor<string, []>("input_331_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_331_strides_0 = const()[name = tensor<string, []>("input_331_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_331_pad_0 = const()[name = tensor<string, []>("input_331_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_331_dilations_0 = const()[name = tensor<string, []>("input_331_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_331_groups_0 = const()[name = tensor<string, []>("input_331_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd1_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd1_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2459904)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd1_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd1_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2476352)))];
            tensor<fp16, [1, 64, ?]> input_331_cast_fp16 = conv(bias = net_xvector_block2_tdnnd1_cam_layer_linear1_bias_to_fp16, dilations = input_331_dilations_0, groups = input_331_groups_0, pad = input_331_pad_0, pad_type = input_331_pad_type_0, strides = input_331_strides_0, weight = net_xvector_block2_tdnnd1_cam_layer_linear1_weight_to_fp16, x = input_329_cast_fp16)[name = tensor<string, []>("input_331_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_333_cast_fp16 = relu(x = input_331_cast_fp16)[name = tensor<string, []>("input_333_cast_fp16")];
            tensor<string, []> input_335_pad_type_0 = const()[name = tensor<string, []>("input_335_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_335_strides_0 = const()[name = tensor<string, []>("input_335_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_335_pad_0 = const()[name = tensor<string, []>("input_335_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_335_dilations_0 = const()[name = tensor<string, []>("input_335_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_335_groups_0 = const()[name = tensor<string, []>("input_335_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd1_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd1_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2476544)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd1_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd1_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2480704)))];
            tensor<fp16, [1, 32, ?]> input_335_cast_fp16 = conv(bias = net_xvector_block2_tdnnd1_cam_layer_linear2_bias_to_fp16, dilations = input_335_dilations_0, groups = input_335_groups_0, pad = input_335_pad_0, pad_type = input_335_pad_type_0, strides = input_335_strides_0, weight = net_xvector_block2_tdnnd1_cam_layer_linear2_weight_to_fp16, x = input_333_cast_fp16)[name = tensor<string, []>("input_335_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_25_cast_fp16 = sigmoid(x = input_335_cast_fp16)[name = tensor<string, []>("m_25_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1176_cast_fp16 = mul(x = y_25_cast_fp16, y = m_25_cast_fp16)[name = tensor<string, []>("op_1176_cast_fp16")];
            tensor<bool, []> input_337_interleave_0 = const()[name = tensor<string, []>("input_337_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 288, ?]> input_337_cast_fp16 = concat(axis = var_11, interleave = input_337_interleave_0, values = (input_317_cast_fp16, var_1176_cast_fp16))[name = tensor<string, []>("input_337_cast_fp16")];
            tensor<fp16, [288]> net_xvector_block2_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [288]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2480832)))];
            tensor<fp16, [288]> net_xvector_block2_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [288]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2481472)))];
            tensor<fp16, [288]> net_xvector_block2_tdnnd2_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd2_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [288]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2482112)))];
            tensor<fp16, [288]> net_xvector_block2_tdnnd2_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd2_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [288]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2482752)))];
            tensor<fp16, [1, 288, ?]> input_339_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd2_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd2_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16, x = input_337_cast_fp16)[name = tensor<string, []>("input_339_cast_fp16")];
            tensor<fp16, [1, 288, ?]> input_341_cast_fp16 = relu(x = input_339_cast_fp16)[name = tensor<string, []>("input_341_cast_fp16")];
            tensor<string, []> input_343_pad_type_0 = const()[name = tensor<string, []>("input_343_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_343_strides_0 = const()[name = tensor<string, []>("input_343_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_343_pad_0 = const()[name = tensor<string, []>("input_343_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_343_dilations_0 = const()[name = tensor<string, []>("input_343_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_343_groups_0 = const()[name = tensor<string, []>("input_343_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 288, 1]> const_52_to_fp16 = const()[name = tensor<string, []>("const_52_to_fp16"), val = tensor<fp16, [128, 288, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2483392)))];
            tensor<fp16, [128]> const_53_to_fp16 = const()[name = tensor<string, []>("const_53_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2557184)))];
            tensor<fp16, [1, 128, ?]> input_345_cast_fp16 = conv(bias = const_53_to_fp16, dilations = input_343_dilations_0, groups = input_343_groups_0, pad = input_343_pad_0, pad_type = input_343_pad_type_0, strides = input_343_strides_0, weight = const_52_to_fp16, x = input_341_cast_fp16)[name = tensor<string, []>("input_345_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_347_cast_fp16 = relu(x = input_345_cast_fp16)[name = tensor<string, []>("input_347_cast_fp16")];
            tensor<string, []> y_27_pad_type_0 = const()[name = tensor<string, []>("y_27_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_27_pad_0 = const()[name = tensor<string, []>("y_27_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_27_dilations_0 = const()[name = tensor<string, []>("y_27_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_27_strides_0 = const()[name = tensor<string, []>("y_27_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_27_groups_0 = const()[name = tensor<string, []>("y_27_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd2_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd2_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2557504)))];
            tensor<fp16, [1, 32, ?]> y_27_cast_fp16 = conv(dilations = y_27_dilations_0, groups = y_27_groups_0, pad = y_27_pad_0, pad_type = y_27_pad_type_0, strides = y_27_strides_0, weight = net_xvector_block2_tdnnd2_cam_layer_linear_local_weight_to_fp16, x = input_347_cast_fp16)[name = tensor<string, []>("y_27_cast_fp16")];
            tensor<int32, [1]> var_1213_axes_0 = const()[name = tensor<string, []>("op_1213_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1213_keep_dims_0 = const()[name = tensor<string, []>("op_1213_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1213_cast_fp16 = reduce_mean(axes = var_1213_axes_0, keep_dims = var_1213_keep_dims_0, x = input_347_cast_fp16)[name = tensor<string, []>("op_1213_cast_fp16")];
            tensor<int32, [1]> var_1214 = const()[name = tensor<string, []>("op_1214"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1215 = const()[name = tensor<string, []>("op_1215"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_53_pad_type_0 = const()[name = tensor<string, []>("seg_53_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_53_pad_0 = const()[name = tensor<string, []>("seg_53_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_53_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_53_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_53_ceil_mode_0 = const()[name = tensor<string, []>("seg_53_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_53_cast_fp16 = avg_pool(ceil_mode = seg_53_ceil_mode_0, exclude_padding_from_average = seg_53_exclude_padding_from_average_0, kernel_sizes = var_1214, pad = seg_53_pad_0, pad_type = seg_53_pad_type_0, strides = var_1215, x = input_347_cast_fp16)[name = tensor<string, []>("seg_53_cast_fp16")];
            tensor<int32, [3]> var_1218_shape_cast_fp16 = shape(x = seg_53_cast_fp16)[name = tensor<string, []>("op_1218_shape_cast_fp16")];
            tensor<int32, []> gather_56 = const()[name = tensor<string, []>("gather_56"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_57 = const()[name = tensor<string, []>("gather_57"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_58_axis_0 = const()[name = tensor<string, []>("gather_58_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_58_batch_dims_0 = const()[name = tensor<string, []>("gather_58_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_58_validate_indices_0 = const()[name = tensor<string, []>("gather_58_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1218_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1218_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_58_to_uint16 = const()[name = tensor<string, []>("select_58_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1218_shape_cast_fp16_to_uint16 = cast(dtype = var_1218_shape_cast_fp16_to_uint16_dtype_0, x = var_1218_shape_cast_fp16)[name = tensor<string, []>("cast_263")];
            tensor<uint16, []> gather_58_cast_uint16 = gather(axis = gather_58_axis_0, batch_dims = gather_58_batch_dims_0, indices = select_58_to_uint16, validate_indices = gather_58_validate_indices_0, x = var_1218_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_58_cast_uint16")];
            tensor<string, []> gather_58_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_58_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1221_axes_0 = const()[name = tensor<string, []>("op_1221_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1221_cast_fp16 = expand_dims(axes = var_1221_axes_0, x = seg_53_cast_fp16)[name = tensor<string, []>("op_1221_cast_fp16")];
            tensor<int32, []> concat_27_axis_0 = const()[name = tensor<string, []>("concat_27_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_27_interleave_0 = const()[name = tensor<string, []>("concat_27_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_58_cast_uint16_to_int32 = cast(dtype = gather_58_cast_uint16_to_int32_dtype_0, x = gather_58_cast_uint16)[name = tensor<string, []>("cast_262")];
            tensor<int32, [4]> concat_27 = concat(axis = concat_27_axis_0, interleave = concat_27_interleave_0, values = (gather_56, gather_57, gather_58_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_27")];
            tensor<int32, [4]> shape_72_cast_fp16 = shape(x = var_1221_cast_fp16)[name = tensor<string, []>("shape_72_cast_fp16")];
            tensor<int32, [4]> real_div_13 = real_div(x = concat_27, y = shape_72_cast_fp16)[name = tensor<string, []>("real_div_13")];
            tensor<fp16, [?, ?, ?, ?]> var_1223_cast_fp16 = tile(reps = real_div_13, x = var_1221_cast_fp16)[name = tensor<string, []>("op_1223_cast_fp16")];
            tensor<int32, [3]> var_1224 = const()[name = tensor<string, []>("op_1224"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_55_cast_fp16 = reshape(shape = var_1224, x = var_1223_cast_fp16)[name = tensor<string, []>("seg_55_cast_fp16")];
            tensor<int32, [3]> var_1226_shape_cast_fp16 = shape(x = input_347_cast_fp16)[name = tensor<string, []>("op_1226_shape_cast_fp16")];
            tensor<int32, []> gather_59_axis_0 = const()[name = tensor<string, []>("gather_59_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_59_batch_dims_0 = const()[name = tensor<string, []>("gather_59_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_59_validate_indices_0 = const()[name = tensor<string, []>("gather_59_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1226_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1226_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_59_to_uint16 = const()[name = tensor<string, []>("select_59_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1226_shape_cast_fp16_to_uint16 = cast(dtype = var_1226_shape_cast_fp16_to_uint16_dtype_0, x = var_1226_shape_cast_fp16)[name = tensor<string, []>("cast_261")];
            tensor<uint16, []> gather_59_cast_uint16 = gather(axis = gather_59_axis_0, batch_dims = gather_59_batch_dims_0, indices = select_59_to_uint16, validate_indices = gather_59_validate_indices_0, x = var_1226_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_59_cast_uint16")];
            tensor<string, []> gather_59_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_59_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_28_values0_0 = const()[name = tensor<string, []>("concat_28_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_28_values1_0 = const()[name = tensor<string, []>("concat_28_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_28_axis_0 = const()[name = tensor<string, []>("concat_28_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_28_interleave_0 = const()[name = tensor<string, []>("concat_28_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_59_cast_uint16_to_int32 = cast(dtype = gather_59_cast_uint16_to_int32_dtype_0, x = gather_59_cast_uint16)[name = tensor<string, []>("cast_260")];
            tensor<int32, [3]> concat_28 = concat(axis = concat_28_axis_0, interleave = concat_28_interleave_0, values = (concat_28_values0_0, concat_28_values1_0, gather_59_cast_uint16_to_int32))[name = tensor<string, []>("concat_28")];
            tensor<int32, [3]> var_1227_begin_0 = const()[name = tensor<string, []>("op_1227_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1227_end_mask_0 = const()[name = tensor<string, []>("op_1227_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1227_cast_fp16 = slice_by_index(begin = var_1227_begin_0, end = concat_28, end_mask = var_1227_end_mask_0, x = seg_55_cast_fp16)[name = tensor<string, []>("op_1227_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_349_cast_fp16 = add(x = var_1213_cast_fp16, y = var_1227_cast_fp16)[name = tensor<string, []>("input_349_cast_fp16")];
            tensor<string, []> input_351_pad_type_0 = const()[name = tensor<string, []>("input_351_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_351_strides_0 = const()[name = tensor<string, []>("input_351_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_351_pad_0 = const()[name = tensor<string, []>("input_351_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_351_dilations_0 = const()[name = tensor<string, []>("input_351_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_351_groups_0 = const()[name = tensor<string, []>("input_351_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd2_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd2_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2582144)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd2_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd2_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2598592)))];
            tensor<fp16, [1, 64, ?]> input_351_cast_fp16 = conv(bias = net_xvector_block2_tdnnd2_cam_layer_linear1_bias_to_fp16, dilations = input_351_dilations_0, groups = input_351_groups_0, pad = input_351_pad_0, pad_type = input_351_pad_type_0, strides = input_351_strides_0, weight = net_xvector_block2_tdnnd2_cam_layer_linear1_weight_to_fp16, x = input_349_cast_fp16)[name = tensor<string, []>("input_351_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_353_cast_fp16 = relu(x = input_351_cast_fp16)[name = tensor<string, []>("input_353_cast_fp16")];
            tensor<string, []> input_355_pad_type_0 = const()[name = tensor<string, []>("input_355_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_355_strides_0 = const()[name = tensor<string, []>("input_355_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_355_pad_0 = const()[name = tensor<string, []>("input_355_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_355_dilations_0 = const()[name = tensor<string, []>("input_355_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_355_groups_0 = const()[name = tensor<string, []>("input_355_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd2_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd2_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2598784)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd2_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd2_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2602944)))];
            tensor<fp16, [1, 32, ?]> input_355_cast_fp16 = conv(bias = net_xvector_block2_tdnnd2_cam_layer_linear2_bias_to_fp16, dilations = input_355_dilations_0, groups = input_355_groups_0, pad = input_355_pad_0, pad_type = input_355_pad_type_0, strides = input_355_strides_0, weight = net_xvector_block2_tdnnd2_cam_layer_linear2_weight_to_fp16, x = input_353_cast_fp16)[name = tensor<string, []>("input_355_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_27_cast_fp16 = sigmoid(x = input_355_cast_fp16)[name = tensor<string, []>("m_27_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1245_cast_fp16 = mul(x = y_27_cast_fp16, y = m_27_cast_fp16)[name = tensor<string, []>("op_1245_cast_fp16")];
            tensor<bool, []> input_357_interleave_0 = const()[name = tensor<string, []>("input_357_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 320, ?]> input_357_cast_fp16 = concat(axis = var_11, interleave = input_357_interleave_0, values = (input_337_cast_fp16, var_1245_cast_fp16))[name = tensor<string, []>("input_357_cast_fp16")];
            tensor<fp16, [320]> net_xvector_block2_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2603072)))];
            tensor<fp16, [320]> net_xvector_block2_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2603776)))];
            tensor<fp16, [320]> net_xvector_block2_tdnnd3_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd3_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2604480)))];
            tensor<fp16, [320]> net_xvector_block2_tdnnd3_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd3_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [320]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2605184)))];
            tensor<fp16, [1, 320, ?]> input_359_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd3_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd3_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16, x = input_357_cast_fp16)[name = tensor<string, []>("input_359_cast_fp16")];
            tensor<fp16, [1, 320, ?]> input_361_cast_fp16 = relu(x = input_359_cast_fp16)[name = tensor<string, []>("input_361_cast_fp16")];
            tensor<string, []> input_363_pad_type_0 = const()[name = tensor<string, []>("input_363_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_363_strides_0 = const()[name = tensor<string, []>("input_363_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_363_pad_0 = const()[name = tensor<string, []>("input_363_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_363_dilations_0 = const()[name = tensor<string, []>("input_363_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_363_groups_0 = const()[name = tensor<string, []>("input_363_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 320, 1]> const_54_to_fp16 = const()[name = tensor<string, []>("const_54_to_fp16"), val = tensor<fp16, [128, 320, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2605888)))];
            tensor<fp16, [128]> const_55_to_fp16 = const()[name = tensor<string, []>("const_55_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2687872)))];
            tensor<fp16, [1, 128, ?]> input_365_cast_fp16 = conv(bias = const_55_to_fp16, dilations = input_363_dilations_0, groups = input_363_groups_0, pad = input_363_pad_0, pad_type = input_363_pad_type_0, strides = input_363_strides_0, weight = const_54_to_fp16, x = input_361_cast_fp16)[name = tensor<string, []>("input_365_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_367_cast_fp16 = relu(x = input_365_cast_fp16)[name = tensor<string, []>("input_367_cast_fp16")];
            tensor<string, []> y_29_pad_type_0 = const()[name = tensor<string, []>("y_29_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_29_pad_0 = const()[name = tensor<string, []>("y_29_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_29_dilations_0 = const()[name = tensor<string, []>("y_29_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_29_strides_0 = const()[name = tensor<string, []>("y_29_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_29_groups_0 = const()[name = tensor<string, []>("y_29_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd3_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd3_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2688192)))];
            tensor<fp16, [1, 32, ?]> y_29_cast_fp16 = conv(dilations = y_29_dilations_0, groups = y_29_groups_0, pad = y_29_pad_0, pad_type = y_29_pad_type_0, strides = y_29_strides_0, weight = net_xvector_block2_tdnnd3_cam_layer_linear_local_weight_to_fp16, x = input_367_cast_fp16)[name = tensor<string, []>("y_29_cast_fp16")];
            tensor<int32, [1]> var_1282_axes_0 = const()[name = tensor<string, []>("op_1282_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1282_keep_dims_0 = const()[name = tensor<string, []>("op_1282_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1282_cast_fp16 = reduce_mean(axes = var_1282_axes_0, keep_dims = var_1282_keep_dims_0, x = input_367_cast_fp16)[name = tensor<string, []>("op_1282_cast_fp16")];
            tensor<int32, [1]> var_1283 = const()[name = tensor<string, []>("op_1283"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1284 = const()[name = tensor<string, []>("op_1284"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_57_pad_type_0 = const()[name = tensor<string, []>("seg_57_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_57_pad_0 = const()[name = tensor<string, []>("seg_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_57_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_57_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_57_ceil_mode_0 = const()[name = tensor<string, []>("seg_57_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_57_cast_fp16 = avg_pool(ceil_mode = seg_57_ceil_mode_0, exclude_padding_from_average = seg_57_exclude_padding_from_average_0, kernel_sizes = var_1283, pad = seg_57_pad_0, pad_type = seg_57_pad_type_0, strides = var_1284, x = input_367_cast_fp16)[name = tensor<string, []>("seg_57_cast_fp16")];
            tensor<int32, [3]> var_1287_shape_cast_fp16 = shape(x = seg_57_cast_fp16)[name = tensor<string, []>("op_1287_shape_cast_fp16")];
            tensor<int32, []> gather_60 = const()[name = tensor<string, []>("gather_60"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_61 = const()[name = tensor<string, []>("gather_61"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_62_axis_0 = const()[name = tensor<string, []>("gather_62_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_62_batch_dims_0 = const()[name = tensor<string, []>("gather_62_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_62_validate_indices_0 = const()[name = tensor<string, []>("gather_62_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1287_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1287_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_62_to_uint16 = const()[name = tensor<string, []>("select_62_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1287_shape_cast_fp16_to_uint16 = cast(dtype = var_1287_shape_cast_fp16_to_uint16_dtype_0, x = var_1287_shape_cast_fp16)[name = tensor<string, []>("cast_259")];
            tensor<uint16, []> gather_62_cast_uint16 = gather(axis = gather_62_axis_0, batch_dims = gather_62_batch_dims_0, indices = select_62_to_uint16, validate_indices = gather_62_validate_indices_0, x = var_1287_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_62_cast_uint16")];
            tensor<string, []> gather_62_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_62_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1290_axes_0 = const()[name = tensor<string, []>("op_1290_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1290_cast_fp16 = expand_dims(axes = var_1290_axes_0, x = seg_57_cast_fp16)[name = tensor<string, []>("op_1290_cast_fp16")];
            tensor<int32, []> concat_29_axis_0 = const()[name = tensor<string, []>("concat_29_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_29_interleave_0 = const()[name = tensor<string, []>("concat_29_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_62_cast_uint16_to_int32 = cast(dtype = gather_62_cast_uint16_to_int32_dtype_0, x = gather_62_cast_uint16)[name = tensor<string, []>("cast_258")];
            tensor<int32, [4]> concat_29 = concat(axis = concat_29_axis_0, interleave = concat_29_interleave_0, values = (gather_60, gather_61, gather_62_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_29")];
            tensor<int32, [4]> shape_77_cast_fp16 = shape(x = var_1290_cast_fp16)[name = tensor<string, []>("shape_77_cast_fp16")];
            tensor<int32, [4]> real_div_14 = real_div(x = concat_29, y = shape_77_cast_fp16)[name = tensor<string, []>("real_div_14")];
            tensor<fp16, [?, ?, ?, ?]> var_1292_cast_fp16 = tile(reps = real_div_14, x = var_1290_cast_fp16)[name = tensor<string, []>("op_1292_cast_fp16")];
            tensor<int32, [3]> var_1293 = const()[name = tensor<string, []>("op_1293"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_59_cast_fp16 = reshape(shape = var_1293, x = var_1292_cast_fp16)[name = tensor<string, []>("seg_59_cast_fp16")];
            tensor<int32, [3]> var_1295_shape_cast_fp16 = shape(x = input_367_cast_fp16)[name = tensor<string, []>("op_1295_shape_cast_fp16")];
            tensor<int32, []> gather_63_axis_0 = const()[name = tensor<string, []>("gather_63_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_63_batch_dims_0 = const()[name = tensor<string, []>("gather_63_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_63_validate_indices_0 = const()[name = tensor<string, []>("gather_63_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1295_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1295_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_63_to_uint16 = const()[name = tensor<string, []>("select_63_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1295_shape_cast_fp16_to_uint16 = cast(dtype = var_1295_shape_cast_fp16_to_uint16_dtype_0, x = var_1295_shape_cast_fp16)[name = tensor<string, []>("cast_257")];
            tensor<uint16, []> gather_63_cast_uint16 = gather(axis = gather_63_axis_0, batch_dims = gather_63_batch_dims_0, indices = select_63_to_uint16, validate_indices = gather_63_validate_indices_0, x = var_1295_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_63_cast_uint16")];
            tensor<string, []> gather_63_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_63_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_30_values0_0 = const()[name = tensor<string, []>("concat_30_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_30_values1_0 = const()[name = tensor<string, []>("concat_30_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_30_axis_0 = const()[name = tensor<string, []>("concat_30_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_30_interleave_0 = const()[name = tensor<string, []>("concat_30_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_63_cast_uint16_to_int32 = cast(dtype = gather_63_cast_uint16_to_int32_dtype_0, x = gather_63_cast_uint16)[name = tensor<string, []>("cast_256")];
            tensor<int32, [3]> concat_30 = concat(axis = concat_30_axis_0, interleave = concat_30_interleave_0, values = (concat_30_values0_0, concat_30_values1_0, gather_63_cast_uint16_to_int32))[name = tensor<string, []>("concat_30")];
            tensor<int32, [3]> var_1296_begin_0 = const()[name = tensor<string, []>("op_1296_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1296_end_mask_0 = const()[name = tensor<string, []>("op_1296_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1296_cast_fp16 = slice_by_index(begin = var_1296_begin_0, end = concat_30, end_mask = var_1296_end_mask_0, x = seg_59_cast_fp16)[name = tensor<string, []>("op_1296_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_369_cast_fp16 = add(x = var_1282_cast_fp16, y = var_1296_cast_fp16)[name = tensor<string, []>("input_369_cast_fp16")];
            tensor<string, []> input_371_pad_type_0 = const()[name = tensor<string, []>("input_371_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_371_strides_0 = const()[name = tensor<string, []>("input_371_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_371_pad_0 = const()[name = tensor<string, []>("input_371_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_371_dilations_0 = const()[name = tensor<string, []>("input_371_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_371_groups_0 = const()[name = tensor<string, []>("input_371_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd3_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd3_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2712832)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd3_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd3_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2729280)))];
            tensor<fp16, [1, 64, ?]> input_371_cast_fp16 = conv(bias = net_xvector_block2_tdnnd3_cam_layer_linear1_bias_to_fp16, dilations = input_371_dilations_0, groups = input_371_groups_0, pad = input_371_pad_0, pad_type = input_371_pad_type_0, strides = input_371_strides_0, weight = net_xvector_block2_tdnnd3_cam_layer_linear1_weight_to_fp16, x = input_369_cast_fp16)[name = tensor<string, []>("input_371_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_373_cast_fp16 = relu(x = input_371_cast_fp16)[name = tensor<string, []>("input_373_cast_fp16")];
            tensor<string, []> input_375_pad_type_0 = const()[name = tensor<string, []>("input_375_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_375_strides_0 = const()[name = tensor<string, []>("input_375_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_375_pad_0 = const()[name = tensor<string, []>("input_375_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_375_dilations_0 = const()[name = tensor<string, []>("input_375_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_375_groups_0 = const()[name = tensor<string, []>("input_375_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd3_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd3_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2729472)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd3_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd3_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2733632)))];
            tensor<fp16, [1, 32, ?]> input_375_cast_fp16 = conv(bias = net_xvector_block2_tdnnd3_cam_layer_linear2_bias_to_fp16, dilations = input_375_dilations_0, groups = input_375_groups_0, pad = input_375_pad_0, pad_type = input_375_pad_type_0, strides = input_375_strides_0, weight = net_xvector_block2_tdnnd3_cam_layer_linear2_weight_to_fp16, x = input_373_cast_fp16)[name = tensor<string, []>("input_375_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_29_cast_fp16 = sigmoid(x = input_375_cast_fp16)[name = tensor<string, []>("m_29_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1314_cast_fp16 = mul(x = y_29_cast_fp16, y = m_29_cast_fp16)[name = tensor<string, []>("op_1314_cast_fp16")];
            tensor<bool, []> input_377_interleave_0 = const()[name = tensor<string, []>("input_377_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 352, ?]> input_377_cast_fp16 = concat(axis = var_11, interleave = input_377_interleave_0, values = (input_357_cast_fp16, var_1314_cast_fp16))[name = tensor<string, []>("input_377_cast_fp16")];
            tensor<fp16, [352]> net_xvector_block2_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [352]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2733760)))];
            tensor<fp16, [352]> net_xvector_block2_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [352]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2734528)))];
            tensor<fp16, [352]> net_xvector_block2_tdnnd4_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd4_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [352]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2735296)))];
            tensor<fp16, [352]> net_xvector_block2_tdnnd4_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd4_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [352]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2736064)))];
            tensor<fp16, [1, 352, ?]> input_379_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd4_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd4_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16, x = input_377_cast_fp16)[name = tensor<string, []>("input_379_cast_fp16")];
            tensor<fp16, [1, 352, ?]> input_381_cast_fp16 = relu(x = input_379_cast_fp16)[name = tensor<string, []>("input_381_cast_fp16")];
            tensor<string, []> input_383_pad_type_0 = const()[name = tensor<string, []>("input_383_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_383_strides_0 = const()[name = tensor<string, []>("input_383_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_383_pad_0 = const()[name = tensor<string, []>("input_383_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_383_dilations_0 = const()[name = tensor<string, []>("input_383_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_383_groups_0 = const()[name = tensor<string, []>("input_383_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 352, 1]> const_56_to_fp16 = const()[name = tensor<string, []>("const_56_to_fp16"), val = tensor<fp16, [128, 352, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2736832)))];
            tensor<fp16, [128]> const_57_to_fp16 = const()[name = tensor<string, []>("const_57_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2827008)))];
            tensor<fp16, [1, 128, ?]> input_385_cast_fp16 = conv(bias = const_57_to_fp16, dilations = input_383_dilations_0, groups = input_383_groups_0, pad = input_383_pad_0, pad_type = input_383_pad_type_0, strides = input_383_strides_0, weight = const_56_to_fp16, x = input_381_cast_fp16)[name = tensor<string, []>("input_385_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_387_cast_fp16 = relu(x = input_385_cast_fp16)[name = tensor<string, []>("input_387_cast_fp16")];
            tensor<string, []> y_31_pad_type_0 = const()[name = tensor<string, []>("y_31_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_31_pad_0 = const()[name = tensor<string, []>("y_31_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_31_dilations_0 = const()[name = tensor<string, []>("y_31_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_31_strides_0 = const()[name = tensor<string, []>("y_31_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_31_groups_0 = const()[name = tensor<string, []>("y_31_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd4_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd4_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2827328)))];
            tensor<fp16, [1, 32, ?]> y_31_cast_fp16 = conv(dilations = y_31_dilations_0, groups = y_31_groups_0, pad = y_31_pad_0, pad_type = y_31_pad_type_0, strides = y_31_strides_0, weight = net_xvector_block2_tdnnd4_cam_layer_linear_local_weight_to_fp16, x = input_387_cast_fp16)[name = tensor<string, []>("y_31_cast_fp16")];
            tensor<int32, [1]> var_1351_axes_0 = const()[name = tensor<string, []>("op_1351_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1351_keep_dims_0 = const()[name = tensor<string, []>("op_1351_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1351_cast_fp16 = reduce_mean(axes = var_1351_axes_0, keep_dims = var_1351_keep_dims_0, x = input_387_cast_fp16)[name = tensor<string, []>("op_1351_cast_fp16")];
            tensor<int32, [1]> var_1352 = const()[name = tensor<string, []>("op_1352"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1353 = const()[name = tensor<string, []>("op_1353"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_61_pad_type_0 = const()[name = tensor<string, []>("seg_61_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_61_pad_0 = const()[name = tensor<string, []>("seg_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_61_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_61_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_61_ceil_mode_0 = const()[name = tensor<string, []>("seg_61_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_61_cast_fp16 = avg_pool(ceil_mode = seg_61_ceil_mode_0, exclude_padding_from_average = seg_61_exclude_padding_from_average_0, kernel_sizes = var_1352, pad = seg_61_pad_0, pad_type = seg_61_pad_type_0, strides = var_1353, x = input_387_cast_fp16)[name = tensor<string, []>("seg_61_cast_fp16")];
            tensor<int32, [3]> var_1356_shape_cast_fp16 = shape(x = seg_61_cast_fp16)[name = tensor<string, []>("op_1356_shape_cast_fp16")];
            tensor<int32, []> gather_64 = const()[name = tensor<string, []>("gather_64"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_65 = const()[name = tensor<string, []>("gather_65"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_66_axis_0 = const()[name = tensor<string, []>("gather_66_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_66_batch_dims_0 = const()[name = tensor<string, []>("gather_66_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_66_validate_indices_0 = const()[name = tensor<string, []>("gather_66_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1356_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1356_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_66_to_uint16 = const()[name = tensor<string, []>("select_66_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1356_shape_cast_fp16_to_uint16 = cast(dtype = var_1356_shape_cast_fp16_to_uint16_dtype_0, x = var_1356_shape_cast_fp16)[name = tensor<string, []>("cast_255")];
            tensor<uint16, []> gather_66_cast_uint16 = gather(axis = gather_66_axis_0, batch_dims = gather_66_batch_dims_0, indices = select_66_to_uint16, validate_indices = gather_66_validate_indices_0, x = var_1356_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_66_cast_uint16")];
            tensor<string, []> gather_66_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_66_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1359_axes_0 = const()[name = tensor<string, []>("op_1359_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1359_cast_fp16 = expand_dims(axes = var_1359_axes_0, x = seg_61_cast_fp16)[name = tensor<string, []>("op_1359_cast_fp16")];
            tensor<int32, []> concat_31_axis_0 = const()[name = tensor<string, []>("concat_31_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_31_interleave_0 = const()[name = tensor<string, []>("concat_31_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_66_cast_uint16_to_int32 = cast(dtype = gather_66_cast_uint16_to_int32_dtype_0, x = gather_66_cast_uint16)[name = tensor<string, []>("cast_254")];
            tensor<int32, [4]> concat_31 = concat(axis = concat_31_axis_0, interleave = concat_31_interleave_0, values = (gather_64, gather_65, gather_66_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_31")];
            tensor<int32, [4]> shape_82_cast_fp16 = shape(x = var_1359_cast_fp16)[name = tensor<string, []>("shape_82_cast_fp16")];
            tensor<int32, [4]> real_div_15 = real_div(x = concat_31, y = shape_82_cast_fp16)[name = tensor<string, []>("real_div_15")];
            tensor<fp16, [?, ?, ?, ?]> var_1361_cast_fp16 = tile(reps = real_div_15, x = var_1359_cast_fp16)[name = tensor<string, []>("op_1361_cast_fp16")];
            tensor<int32, [3]> var_1362 = const()[name = tensor<string, []>("op_1362"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_63_cast_fp16 = reshape(shape = var_1362, x = var_1361_cast_fp16)[name = tensor<string, []>("seg_63_cast_fp16")];
            tensor<int32, [3]> var_1364_shape_cast_fp16 = shape(x = input_387_cast_fp16)[name = tensor<string, []>("op_1364_shape_cast_fp16")];
            tensor<int32, []> gather_67_axis_0 = const()[name = tensor<string, []>("gather_67_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_67_batch_dims_0 = const()[name = tensor<string, []>("gather_67_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_67_validate_indices_0 = const()[name = tensor<string, []>("gather_67_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1364_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1364_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_67_to_uint16 = const()[name = tensor<string, []>("select_67_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1364_shape_cast_fp16_to_uint16 = cast(dtype = var_1364_shape_cast_fp16_to_uint16_dtype_0, x = var_1364_shape_cast_fp16)[name = tensor<string, []>("cast_253")];
            tensor<uint16, []> gather_67_cast_uint16 = gather(axis = gather_67_axis_0, batch_dims = gather_67_batch_dims_0, indices = select_67_to_uint16, validate_indices = gather_67_validate_indices_0, x = var_1364_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_67_cast_uint16")];
            tensor<string, []> gather_67_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_67_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_32_values0_0 = const()[name = tensor<string, []>("concat_32_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_32_values1_0 = const()[name = tensor<string, []>("concat_32_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_32_axis_0 = const()[name = tensor<string, []>("concat_32_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_32_interleave_0 = const()[name = tensor<string, []>("concat_32_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_67_cast_uint16_to_int32 = cast(dtype = gather_67_cast_uint16_to_int32_dtype_0, x = gather_67_cast_uint16)[name = tensor<string, []>("cast_252")];
            tensor<int32, [3]> concat_32 = concat(axis = concat_32_axis_0, interleave = concat_32_interleave_0, values = (concat_32_values0_0, concat_32_values1_0, gather_67_cast_uint16_to_int32))[name = tensor<string, []>("concat_32")];
            tensor<int32, [3]> var_1365_begin_0 = const()[name = tensor<string, []>("op_1365_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1365_end_mask_0 = const()[name = tensor<string, []>("op_1365_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1365_cast_fp16 = slice_by_index(begin = var_1365_begin_0, end = concat_32, end_mask = var_1365_end_mask_0, x = seg_63_cast_fp16)[name = tensor<string, []>("op_1365_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_389_cast_fp16 = add(x = var_1351_cast_fp16, y = var_1365_cast_fp16)[name = tensor<string, []>("input_389_cast_fp16")];
            tensor<string, []> input_391_pad_type_0 = const()[name = tensor<string, []>("input_391_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_391_strides_0 = const()[name = tensor<string, []>("input_391_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_391_pad_0 = const()[name = tensor<string, []>("input_391_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_391_dilations_0 = const()[name = tensor<string, []>("input_391_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_391_groups_0 = const()[name = tensor<string, []>("input_391_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd4_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd4_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2851968)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd4_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd4_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2868416)))];
            tensor<fp16, [1, 64, ?]> input_391_cast_fp16 = conv(bias = net_xvector_block2_tdnnd4_cam_layer_linear1_bias_to_fp16, dilations = input_391_dilations_0, groups = input_391_groups_0, pad = input_391_pad_0, pad_type = input_391_pad_type_0, strides = input_391_strides_0, weight = net_xvector_block2_tdnnd4_cam_layer_linear1_weight_to_fp16, x = input_389_cast_fp16)[name = tensor<string, []>("input_391_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_393_cast_fp16 = relu(x = input_391_cast_fp16)[name = tensor<string, []>("input_393_cast_fp16")];
            tensor<string, []> input_395_pad_type_0 = const()[name = tensor<string, []>("input_395_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_395_strides_0 = const()[name = tensor<string, []>("input_395_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_395_pad_0 = const()[name = tensor<string, []>("input_395_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_395_dilations_0 = const()[name = tensor<string, []>("input_395_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_395_groups_0 = const()[name = tensor<string, []>("input_395_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd4_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd4_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2868608)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd4_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd4_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2872768)))];
            tensor<fp16, [1, 32, ?]> input_395_cast_fp16 = conv(bias = net_xvector_block2_tdnnd4_cam_layer_linear2_bias_to_fp16, dilations = input_395_dilations_0, groups = input_395_groups_0, pad = input_395_pad_0, pad_type = input_395_pad_type_0, strides = input_395_strides_0, weight = net_xvector_block2_tdnnd4_cam_layer_linear2_weight_to_fp16, x = input_393_cast_fp16)[name = tensor<string, []>("input_395_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_31_cast_fp16 = sigmoid(x = input_395_cast_fp16)[name = tensor<string, []>("m_31_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1383_cast_fp16 = mul(x = y_31_cast_fp16, y = m_31_cast_fp16)[name = tensor<string, []>("op_1383_cast_fp16")];
            tensor<bool, []> input_397_interleave_0 = const()[name = tensor<string, []>("input_397_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 384, ?]> input_397_cast_fp16 = concat(axis = var_11, interleave = input_397_interleave_0, values = (input_377_cast_fp16, var_1383_cast_fp16))[name = tensor<string, []>("input_397_cast_fp16")];
            tensor<fp16, [384]> net_xvector_block2_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2872896)))];
            tensor<fp16, [384]> net_xvector_block2_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2873728)))];
            tensor<fp16, [384]> net_xvector_block2_tdnnd5_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd5_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2874560)))];
            tensor<fp16, [384]> net_xvector_block2_tdnnd5_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd5_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2875392)))];
            tensor<fp16, [1, 384, ?]> input_399_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd5_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd5_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16, x = input_397_cast_fp16)[name = tensor<string, []>("input_399_cast_fp16")];
            tensor<fp16, [1, 384, ?]> input_401_cast_fp16 = relu(x = input_399_cast_fp16)[name = tensor<string, []>("input_401_cast_fp16")];
            tensor<string, []> input_403_pad_type_0 = const()[name = tensor<string, []>("input_403_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_403_strides_0 = const()[name = tensor<string, []>("input_403_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_403_pad_0 = const()[name = tensor<string, []>("input_403_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_403_dilations_0 = const()[name = tensor<string, []>("input_403_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_403_groups_0 = const()[name = tensor<string, []>("input_403_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 384, 1]> const_58_to_fp16 = const()[name = tensor<string, []>("const_58_to_fp16"), val = tensor<fp16, [128, 384, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2876224)))];
            tensor<fp16, [128]> const_59_to_fp16 = const()[name = tensor<string, []>("const_59_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2974592)))];
            tensor<fp16, [1, 128, ?]> input_405_cast_fp16 = conv(bias = const_59_to_fp16, dilations = input_403_dilations_0, groups = input_403_groups_0, pad = input_403_pad_0, pad_type = input_403_pad_type_0, strides = input_403_strides_0, weight = const_58_to_fp16, x = input_401_cast_fp16)[name = tensor<string, []>("input_405_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_407_cast_fp16 = relu(x = input_405_cast_fp16)[name = tensor<string, []>("input_407_cast_fp16")];
            tensor<string, []> y_33_pad_type_0 = const()[name = tensor<string, []>("y_33_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_33_pad_0 = const()[name = tensor<string, []>("y_33_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_33_dilations_0 = const()[name = tensor<string, []>("y_33_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_33_strides_0 = const()[name = tensor<string, []>("y_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_33_groups_0 = const()[name = tensor<string, []>("y_33_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd5_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd5_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2974912)))];
            tensor<fp16, [1, 32, ?]> y_33_cast_fp16 = conv(dilations = y_33_dilations_0, groups = y_33_groups_0, pad = y_33_pad_0, pad_type = y_33_pad_type_0, strides = y_33_strides_0, weight = net_xvector_block2_tdnnd5_cam_layer_linear_local_weight_to_fp16, x = input_407_cast_fp16)[name = tensor<string, []>("y_33_cast_fp16")];
            tensor<int32, [1]> var_1420_axes_0 = const()[name = tensor<string, []>("op_1420_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1420_keep_dims_0 = const()[name = tensor<string, []>("op_1420_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1420_cast_fp16 = reduce_mean(axes = var_1420_axes_0, keep_dims = var_1420_keep_dims_0, x = input_407_cast_fp16)[name = tensor<string, []>("op_1420_cast_fp16")];
            tensor<int32, [1]> var_1421 = const()[name = tensor<string, []>("op_1421"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1422 = const()[name = tensor<string, []>("op_1422"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_65_pad_type_0 = const()[name = tensor<string, []>("seg_65_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_65_pad_0 = const()[name = tensor<string, []>("seg_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_65_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_65_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_65_ceil_mode_0 = const()[name = tensor<string, []>("seg_65_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_65_cast_fp16 = avg_pool(ceil_mode = seg_65_ceil_mode_0, exclude_padding_from_average = seg_65_exclude_padding_from_average_0, kernel_sizes = var_1421, pad = seg_65_pad_0, pad_type = seg_65_pad_type_0, strides = var_1422, x = input_407_cast_fp16)[name = tensor<string, []>("seg_65_cast_fp16")];
            tensor<int32, [3]> var_1425_shape_cast_fp16 = shape(x = seg_65_cast_fp16)[name = tensor<string, []>("op_1425_shape_cast_fp16")];
            tensor<int32, []> gather_68 = const()[name = tensor<string, []>("gather_68"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_69 = const()[name = tensor<string, []>("gather_69"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_70_axis_0 = const()[name = tensor<string, []>("gather_70_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_70_batch_dims_0 = const()[name = tensor<string, []>("gather_70_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_70_validate_indices_0 = const()[name = tensor<string, []>("gather_70_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1425_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1425_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_70_to_uint16 = const()[name = tensor<string, []>("select_70_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1425_shape_cast_fp16_to_uint16 = cast(dtype = var_1425_shape_cast_fp16_to_uint16_dtype_0, x = var_1425_shape_cast_fp16)[name = tensor<string, []>("cast_251")];
            tensor<uint16, []> gather_70_cast_uint16 = gather(axis = gather_70_axis_0, batch_dims = gather_70_batch_dims_0, indices = select_70_to_uint16, validate_indices = gather_70_validate_indices_0, x = var_1425_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_70_cast_uint16")];
            tensor<string, []> gather_70_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_70_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1428_axes_0 = const()[name = tensor<string, []>("op_1428_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1428_cast_fp16 = expand_dims(axes = var_1428_axes_0, x = seg_65_cast_fp16)[name = tensor<string, []>("op_1428_cast_fp16")];
            tensor<int32, []> concat_33_axis_0 = const()[name = tensor<string, []>("concat_33_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_33_interleave_0 = const()[name = tensor<string, []>("concat_33_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_70_cast_uint16_to_int32 = cast(dtype = gather_70_cast_uint16_to_int32_dtype_0, x = gather_70_cast_uint16)[name = tensor<string, []>("cast_250")];
            tensor<int32, [4]> concat_33 = concat(axis = concat_33_axis_0, interleave = concat_33_interleave_0, values = (gather_68, gather_69, gather_70_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_33")];
            tensor<int32, [4]> shape_87_cast_fp16 = shape(x = var_1428_cast_fp16)[name = tensor<string, []>("shape_87_cast_fp16")];
            tensor<int32, [4]> real_div_16 = real_div(x = concat_33, y = shape_87_cast_fp16)[name = tensor<string, []>("real_div_16")];
            tensor<fp16, [?, ?, ?, ?]> var_1430_cast_fp16 = tile(reps = real_div_16, x = var_1428_cast_fp16)[name = tensor<string, []>("op_1430_cast_fp16")];
            tensor<int32, [3]> var_1431 = const()[name = tensor<string, []>("op_1431"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_67_cast_fp16 = reshape(shape = var_1431, x = var_1430_cast_fp16)[name = tensor<string, []>("seg_67_cast_fp16")];
            tensor<int32, [3]> var_1433_shape_cast_fp16 = shape(x = input_407_cast_fp16)[name = tensor<string, []>("op_1433_shape_cast_fp16")];
            tensor<int32, []> gather_71_axis_0 = const()[name = tensor<string, []>("gather_71_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_71_batch_dims_0 = const()[name = tensor<string, []>("gather_71_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_71_validate_indices_0 = const()[name = tensor<string, []>("gather_71_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1433_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1433_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_71_to_uint16 = const()[name = tensor<string, []>("select_71_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1433_shape_cast_fp16_to_uint16 = cast(dtype = var_1433_shape_cast_fp16_to_uint16_dtype_0, x = var_1433_shape_cast_fp16)[name = tensor<string, []>("cast_249")];
            tensor<uint16, []> gather_71_cast_uint16 = gather(axis = gather_71_axis_0, batch_dims = gather_71_batch_dims_0, indices = select_71_to_uint16, validate_indices = gather_71_validate_indices_0, x = var_1433_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_71_cast_uint16")];
            tensor<string, []> gather_71_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_71_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_34_values0_0 = const()[name = tensor<string, []>("concat_34_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_34_values1_0 = const()[name = tensor<string, []>("concat_34_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_34_axis_0 = const()[name = tensor<string, []>("concat_34_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_34_interleave_0 = const()[name = tensor<string, []>("concat_34_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_71_cast_uint16_to_int32 = cast(dtype = gather_71_cast_uint16_to_int32_dtype_0, x = gather_71_cast_uint16)[name = tensor<string, []>("cast_248")];
            tensor<int32, [3]> concat_34 = concat(axis = concat_34_axis_0, interleave = concat_34_interleave_0, values = (concat_34_values0_0, concat_34_values1_0, gather_71_cast_uint16_to_int32))[name = tensor<string, []>("concat_34")];
            tensor<int32, [3]> var_1434_begin_0 = const()[name = tensor<string, []>("op_1434_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1434_end_mask_0 = const()[name = tensor<string, []>("op_1434_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1434_cast_fp16 = slice_by_index(begin = var_1434_begin_0, end = concat_34, end_mask = var_1434_end_mask_0, x = seg_67_cast_fp16)[name = tensor<string, []>("op_1434_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_409_cast_fp16 = add(x = var_1420_cast_fp16, y = var_1434_cast_fp16)[name = tensor<string, []>("input_409_cast_fp16")];
            tensor<string, []> input_411_pad_type_0 = const()[name = tensor<string, []>("input_411_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_411_strides_0 = const()[name = tensor<string, []>("input_411_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_411_pad_0 = const()[name = tensor<string, []>("input_411_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_411_dilations_0 = const()[name = tensor<string, []>("input_411_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_411_groups_0 = const()[name = tensor<string, []>("input_411_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd5_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd5_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2999552)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd5_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd5_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3016000)))];
            tensor<fp16, [1, 64, ?]> input_411_cast_fp16 = conv(bias = net_xvector_block2_tdnnd5_cam_layer_linear1_bias_to_fp16, dilations = input_411_dilations_0, groups = input_411_groups_0, pad = input_411_pad_0, pad_type = input_411_pad_type_0, strides = input_411_strides_0, weight = net_xvector_block2_tdnnd5_cam_layer_linear1_weight_to_fp16, x = input_409_cast_fp16)[name = tensor<string, []>("input_411_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_413_cast_fp16 = relu(x = input_411_cast_fp16)[name = tensor<string, []>("input_413_cast_fp16")];
            tensor<string, []> input_415_pad_type_0 = const()[name = tensor<string, []>("input_415_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_415_strides_0 = const()[name = tensor<string, []>("input_415_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_415_pad_0 = const()[name = tensor<string, []>("input_415_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_415_dilations_0 = const()[name = tensor<string, []>("input_415_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_415_groups_0 = const()[name = tensor<string, []>("input_415_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd5_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd5_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3016192)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd5_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd5_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3020352)))];
            tensor<fp16, [1, 32, ?]> input_415_cast_fp16 = conv(bias = net_xvector_block2_tdnnd5_cam_layer_linear2_bias_to_fp16, dilations = input_415_dilations_0, groups = input_415_groups_0, pad = input_415_pad_0, pad_type = input_415_pad_type_0, strides = input_415_strides_0, weight = net_xvector_block2_tdnnd5_cam_layer_linear2_weight_to_fp16, x = input_413_cast_fp16)[name = tensor<string, []>("input_415_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_33_cast_fp16 = sigmoid(x = input_415_cast_fp16)[name = tensor<string, []>("m_33_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1452_cast_fp16 = mul(x = y_33_cast_fp16, y = m_33_cast_fp16)[name = tensor<string, []>("op_1452_cast_fp16")];
            tensor<bool, []> input_417_interleave_0 = const()[name = tensor<string, []>("input_417_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 416, ?]> input_417_cast_fp16 = concat(axis = var_11, interleave = input_417_interleave_0, values = (input_397_cast_fp16, var_1452_cast_fp16))[name = tensor<string, []>("input_417_cast_fp16")];
            tensor<fp16, [416]> net_xvector_block2_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [416]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3020480)))];
            tensor<fp16, [416]> net_xvector_block2_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [416]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3021376)))];
            tensor<fp16, [416]> net_xvector_block2_tdnnd6_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd6_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [416]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3022272)))];
            tensor<fp16, [416]> net_xvector_block2_tdnnd6_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd6_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [416]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3023168)))];
            tensor<fp16, [1, 416, ?]> input_419_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd6_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd6_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16, x = input_417_cast_fp16)[name = tensor<string, []>("input_419_cast_fp16")];
            tensor<fp16, [1, 416, ?]> input_421_cast_fp16 = relu(x = input_419_cast_fp16)[name = tensor<string, []>("input_421_cast_fp16")];
            tensor<string, []> input_423_pad_type_0 = const()[name = tensor<string, []>("input_423_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_423_strides_0 = const()[name = tensor<string, []>("input_423_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_423_pad_0 = const()[name = tensor<string, []>("input_423_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_423_dilations_0 = const()[name = tensor<string, []>("input_423_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_423_groups_0 = const()[name = tensor<string, []>("input_423_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 416, 1]> const_60_to_fp16 = const()[name = tensor<string, []>("const_60_to_fp16"), val = tensor<fp16, [128, 416, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3024064)))];
            tensor<fp16, [128]> const_61_to_fp16 = const()[name = tensor<string, []>("const_61_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3130624)))];
            tensor<fp16, [1, 128, ?]> input_425_cast_fp16 = conv(bias = const_61_to_fp16, dilations = input_423_dilations_0, groups = input_423_groups_0, pad = input_423_pad_0, pad_type = input_423_pad_type_0, strides = input_423_strides_0, weight = const_60_to_fp16, x = input_421_cast_fp16)[name = tensor<string, []>("input_425_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_427_cast_fp16 = relu(x = input_425_cast_fp16)[name = tensor<string, []>("input_427_cast_fp16")];
            tensor<string, []> y_35_pad_type_0 = const()[name = tensor<string, []>("y_35_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_35_pad_0 = const()[name = tensor<string, []>("y_35_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_35_dilations_0 = const()[name = tensor<string, []>("y_35_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_35_strides_0 = const()[name = tensor<string, []>("y_35_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_35_groups_0 = const()[name = tensor<string, []>("y_35_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd6_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd6_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3130944)))];
            tensor<fp16, [1, 32, ?]> y_35_cast_fp16 = conv(dilations = y_35_dilations_0, groups = y_35_groups_0, pad = y_35_pad_0, pad_type = y_35_pad_type_0, strides = y_35_strides_0, weight = net_xvector_block2_tdnnd6_cam_layer_linear_local_weight_to_fp16, x = input_427_cast_fp16)[name = tensor<string, []>("y_35_cast_fp16")];
            tensor<int32, [1]> var_1489_axes_0 = const()[name = tensor<string, []>("op_1489_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1489_keep_dims_0 = const()[name = tensor<string, []>("op_1489_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1489_cast_fp16 = reduce_mean(axes = var_1489_axes_0, keep_dims = var_1489_keep_dims_0, x = input_427_cast_fp16)[name = tensor<string, []>("op_1489_cast_fp16")];
            tensor<int32, [1]> var_1490 = const()[name = tensor<string, []>("op_1490"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1491 = const()[name = tensor<string, []>("op_1491"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_69_pad_type_0 = const()[name = tensor<string, []>("seg_69_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_69_pad_0 = const()[name = tensor<string, []>("seg_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_69_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_69_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_69_ceil_mode_0 = const()[name = tensor<string, []>("seg_69_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_69_cast_fp16 = avg_pool(ceil_mode = seg_69_ceil_mode_0, exclude_padding_from_average = seg_69_exclude_padding_from_average_0, kernel_sizes = var_1490, pad = seg_69_pad_0, pad_type = seg_69_pad_type_0, strides = var_1491, x = input_427_cast_fp16)[name = tensor<string, []>("seg_69_cast_fp16")];
            tensor<int32, [3]> var_1494_shape_cast_fp16 = shape(x = seg_69_cast_fp16)[name = tensor<string, []>("op_1494_shape_cast_fp16")];
            tensor<int32, []> gather_72 = const()[name = tensor<string, []>("gather_72"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_73 = const()[name = tensor<string, []>("gather_73"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_74_axis_0 = const()[name = tensor<string, []>("gather_74_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_74_batch_dims_0 = const()[name = tensor<string, []>("gather_74_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_74_validate_indices_0 = const()[name = tensor<string, []>("gather_74_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1494_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1494_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_74_to_uint16 = const()[name = tensor<string, []>("select_74_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1494_shape_cast_fp16_to_uint16 = cast(dtype = var_1494_shape_cast_fp16_to_uint16_dtype_0, x = var_1494_shape_cast_fp16)[name = tensor<string, []>("cast_247")];
            tensor<uint16, []> gather_74_cast_uint16 = gather(axis = gather_74_axis_0, batch_dims = gather_74_batch_dims_0, indices = select_74_to_uint16, validate_indices = gather_74_validate_indices_0, x = var_1494_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_74_cast_uint16")];
            tensor<string, []> gather_74_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_74_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1497_axes_0 = const()[name = tensor<string, []>("op_1497_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1497_cast_fp16 = expand_dims(axes = var_1497_axes_0, x = seg_69_cast_fp16)[name = tensor<string, []>("op_1497_cast_fp16")];
            tensor<int32, []> concat_35_axis_0 = const()[name = tensor<string, []>("concat_35_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_35_interleave_0 = const()[name = tensor<string, []>("concat_35_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_74_cast_uint16_to_int32 = cast(dtype = gather_74_cast_uint16_to_int32_dtype_0, x = gather_74_cast_uint16)[name = tensor<string, []>("cast_246")];
            tensor<int32, [4]> concat_35 = concat(axis = concat_35_axis_0, interleave = concat_35_interleave_0, values = (gather_72, gather_73, gather_74_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_35")];
            tensor<int32, [4]> shape_92_cast_fp16 = shape(x = var_1497_cast_fp16)[name = tensor<string, []>("shape_92_cast_fp16")];
            tensor<int32, [4]> real_div_17 = real_div(x = concat_35, y = shape_92_cast_fp16)[name = tensor<string, []>("real_div_17")];
            tensor<fp16, [?, ?, ?, ?]> var_1499_cast_fp16 = tile(reps = real_div_17, x = var_1497_cast_fp16)[name = tensor<string, []>("op_1499_cast_fp16")];
            tensor<int32, [3]> var_1500 = const()[name = tensor<string, []>("op_1500"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_71_cast_fp16 = reshape(shape = var_1500, x = var_1499_cast_fp16)[name = tensor<string, []>("seg_71_cast_fp16")];
            tensor<int32, [3]> var_1502_shape_cast_fp16 = shape(x = input_427_cast_fp16)[name = tensor<string, []>("op_1502_shape_cast_fp16")];
            tensor<int32, []> gather_75_axis_0 = const()[name = tensor<string, []>("gather_75_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_75_batch_dims_0 = const()[name = tensor<string, []>("gather_75_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_75_validate_indices_0 = const()[name = tensor<string, []>("gather_75_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1502_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1502_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_75_to_uint16 = const()[name = tensor<string, []>("select_75_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1502_shape_cast_fp16_to_uint16 = cast(dtype = var_1502_shape_cast_fp16_to_uint16_dtype_0, x = var_1502_shape_cast_fp16)[name = tensor<string, []>("cast_245")];
            tensor<uint16, []> gather_75_cast_uint16 = gather(axis = gather_75_axis_0, batch_dims = gather_75_batch_dims_0, indices = select_75_to_uint16, validate_indices = gather_75_validate_indices_0, x = var_1502_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_75_cast_uint16")];
            tensor<string, []> gather_75_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_75_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_36_values0_0 = const()[name = tensor<string, []>("concat_36_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_36_values1_0 = const()[name = tensor<string, []>("concat_36_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_36_axis_0 = const()[name = tensor<string, []>("concat_36_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_36_interleave_0 = const()[name = tensor<string, []>("concat_36_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_75_cast_uint16_to_int32 = cast(dtype = gather_75_cast_uint16_to_int32_dtype_0, x = gather_75_cast_uint16)[name = tensor<string, []>("cast_244")];
            tensor<int32, [3]> concat_36 = concat(axis = concat_36_axis_0, interleave = concat_36_interleave_0, values = (concat_36_values0_0, concat_36_values1_0, gather_75_cast_uint16_to_int32))[name = tensor<string, []>("concat_36")];
            tensor<int32, [3]> var_1503_begin_0 = const()[name = tensor<string, []>("op_1503_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1503_end_mask_0 = const()[name = tensor<string, []>("op_1503_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1503_cast_fp16 = slice_by_index(begin = var_1503_begin_0, end = concat_36, end_mask = var_1503_end_mask_0, x = seg_71_cast_fp16)[name = tensor<string, []>("op_1503_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_429_cast_fp16 = add(x = var_1489_cast_fp16, y = var_1503_cast_fp16)[name = tensor<string, []>("input_429_cast_fp16")];
            tensor<string, []> input_431_pad_type_0 = const()[name = tensor<string, []>("input_431_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_431_strides_0 = const()[name = tensor<string, []>("input_431_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_431_pad_0 = const()[name = tensor<string, []>("input_431_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_431_dilations_0 = const()[name = tensor<string, []>("input_431_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_431_groups_0 = const()[name = tensor<string, []>("input_431_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd6_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd6_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3155584)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd6_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd6_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3172032)))];
            tensor<fp16, [1, 64, ?]> input_431_cast_fp16 = conv(bias = net_xvector_block2_tdnnd6_cam_layer_linear1_bias_to_fp16, dilations = input_431_dilations_0, groups = input_431_groups_0, pad = input_431_pad_0, pad_type = input_431_pad_type_0, strides = input_431_strides_0, weight = net_xvector_block2_tdnnd6_cam_layer_linear1_weight_to_fp16, x = input_429_cast_fp16)[name = tensor<string, []>("input_431_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_433_cast_fp16 = relu(x = input_431_cast_fp16)[name = tensor<string, []>("input_433_cast_fp16")];
            tensor<string, []> input_435_pad_type_0 = const()[name = tensor<string, []>("input_435_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_435_strides_0 = const()[name = tensor<string, []>("input_435_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_435_pad_0 = const()[name = tensor<string, []>("input_435_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_435_dilations_0 = const()[name = tensor<string, []>("input_435_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_435_groups_0 = const()[name = tensor<string, []>("input_435_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd6_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd6_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3172224)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd6_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd6_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3176384)))];
            tensor<fp16, [1, 32, ?]> input_435_cast_fp16 = conv(bias = net_xvector_block2_tdnnd6_cam_layer_linear2_bias_to_fp16, dilations = input_435_dilations_0, groups = input_435_groups_0, pad = input_435_pad_0, pad_type = input_435_pad_type_0, strides = input_435_strides_0, weight = net_xvector_block2_tdnnd6_cam_layer_linear2_weight_to_fp16, x = input_433_cast_fp16)[name = tensor<string, []>("input_435_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_35_cast_fp16 = sigmoid(x = input_435_cast_fp16)[name = tensor<string, []>("m_35_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1521_cast_fp16 = mul(x = y_35_cast_fp16, y = m_35_cast_fp16)[name = tensor<string, []>("op_1521_cast_fp16")];
            tensor<bool, []> input_437_interleave_0 = const()[name = tensor<string, []>("input_437_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 448, ?]> input_437_cast_fp16 = concat(axis = var_11, interleave = input_437_interleave_0, values = (input_417_cast_fp16, var_1521_cast_fp16))[name = tensor<string, []>("input_437_cast_fp16")];
            tensor<fp16, [448]> net_xvector_block2_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [448]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3176512)))];
            tensor<fp16, [448]> net_xvector_block2_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [448]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3177472)))];
            tensor<fp16, [448]> net_xvector_block2_tdnnd7_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd7_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [448]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3178432)))];
            tensor<fp16, [448]> net_xvector_block2_tdnnd7_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd7_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [448]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3179392)))];
            tensor<fp16, [1, 448, ?]> input_439_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd7_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd7_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16, x = input_437_cast_fp16)[name = tensor<string, []>("input_439_cast_fp16")];
            tensor<fp16, [1, 448, ?]> input_441_cast_fp16 = relu(x = input_439_cast_fp16)[name = tensor<string, []>("input_441_cast_fp16")];
            tensor<string, []> input_443_pad_type_0 = const()[name = tensor<string, []>("input_443_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_443_strides_0 = const()[name = tensor<string, []>("input_443_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_443_pad_0 = const()[name = tensor<string, []>("input_443_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_443_dilations_0 = const()[name = tensor<string, []>("input_443_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_443_groups_0 = const()[name = tensor<string, []>("input_443_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 448, 1]> const_62_to_fp16 = const()[name = tensor<string, []>("const_62_to_fp16"), val = tensor<fp16, [128, 448, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3180352)))];
            tensor<fp16, [128]> const_63_to_fp16 = const()[name = tensor<string, []>("const_63_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3295104)))];
            tensor<fp16, [1, 128, ?]> input_445_cast_fp16 = conv(bias = const_63_to_fp16, dilations = input_443_dilations_0, groups = input_443_groups_0, pad = input_443_pad_0, pad_type = input_443_pad_type_0, strides = input_443_strides_0, weight = const_62_to_fp16, x = input_441_cast_fp16)[name = tensor<string, []>("input_445_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_447_cast_fp16 = relu(x = input_445_cast_fp16)[name = tensor<string, []>("input_447_cast_fp16")];
            tensor<string, []> y_37_pad_type_0 = const()[name = tensor<string, []>("y_37_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_37_pad_0 = const()[name = tensor<string, []>("y_37_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_37_dilations_0 = const()[name = tensor<string, []>("y_37_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_37_strides_0 = const()[name = tensor<string, []>("y_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_37_groups_0 = const()[name = tensor<string, []>("y_37_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd7_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd7_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3295424)))];
            tensor<fp16, [1, 32, ?]> y_37_cast_fp16 = conv(dilations = y_37_dilations_0, groups = y_37_groups_0, pad = y_37_pad_0, pad_type = y_37_pad_type_0, strides = y_37_strides_0, weight = net_xvector_block2_tdnnd7_cam_layer_linear_local_weight_to_fp16, x = input_447_cast_fp16)[name = tensor<string, []>("y_37_cast_fp16")];
            tensor<int32, [1]> var_1558_axes_0 = const()[name = tensor<string, []>("op_1558_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1558_keep_dims_0 = const()[name = tensor<string, []>("op_1558_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1558_cast_fp16 = reduce_mean(axes = var_1558_axes_0, keep_dims = var_1558_keep_dims_0, x = input_447_cast_fp16)[name = tensor<string, []>("op_1558_cast_fp16")];
            tensor<int32, [1]> var_1559 = const()[name = tensor<string, []>("op_1559"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1560 = const()[name = tensor<string, []>("op_1560"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_73_pad_type_0 = const()[name = tensor<string, []>("seg_73_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_73_pad_0 = const()[name = tensor<string, []>("seg_73_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_73_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_73_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_73_ceil_mode_0 = const()[name = tensor<string, []>("seg_73_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_73_cast_fp16 = avg_pool(ceil_mode = seg_73_ceil_mode_0, exclude_padding_from_average = seg_73_exclude_padding_from_average_0, kernel_sizes = var_1559, pad = seg_73_pad_0, pad_type = seg_73_pad_type_0, strides = var_1560, x = input_447_cast_fp16)[name = tensor<string, []>("seg_73_cast_fp16")];
            tensor<int32, [3]> var_1563_shape_cast_fp16 = shape(x = seg_73_cast_fp16)[name = tensor<string, []>("op_1563_shape_cast_fp16")];
            tensor<int32, []> gather_76 = const()[name = tensor<string, []>("gather_76"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_77 = const()[name = tensor<string, []>("gather_77"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_78_axis_0 = const()[name = tensor<string, []>("gather_78_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_78_batch_dims_0 = const()[name = tensor<string, []>("gather_78_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_78_validate_indices_0 = const()[name = tensor<string, []>("gather_78_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1563_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1563_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_78_to_uint16 = const()[name = tensor<string, []>("select_78_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1563_shape_cast_fp16_to_uint16 = cast(dtype = var_1563_shape_cast_fp16_to_uint16_dtype_0, x = var_1563_shape_cast_fp16)[name = tensor<string, []>("cast_243")];
            tensor<uint16, []> gather_78_cast_uint16 = gather(axis = gather_78_axis_0, batch_dims = gather_78_batch_dims_0, indices = select_78_to_uint16, validate_indices = gather_78_validate_indices_0, x = var_1563_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_78_cast_uint16")];
            tensor<string, []> gather_78_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_78_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1566_axes_0 = const()[name = tensor<string, []>("op_1566_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1566_cast_fp16 = expand_dims(axes = var_1566_axes_0, x = seg_73_cast_fp16)[name = tensor<string, []>("op_1566_cast_fp16")];
            tensor<int32, []> concat_37_axis_0 = const()[name = tensor<string, []>("concat_37_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_37_interleave_0 = const()[name = tensor<string, []>("concat_37_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_78_cast_uint16_to_int32 = cast(dtype = gather_78_cast_uint16_to_int32_dtype_0, x = gather_78_cast_uint16)[name = tensor<string, []>("cast_242")];
            tensor<int32, [4]> concat_37 = concat(axis = concat_37_axis_0, interleave = concat_37_interleave_0, values = (gather_76, gather_77, gather_78_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_37")];
            tensor<int32, [4]> shape_97_cast_fp16 = shape(x = var_1566_cast_fp16)[name = tensor<string, []>("shape_97_cast_fp16")];
            tensor<int32, [4]> real_div_18 = real_div(x = concat_37, y = shape_97_cast_fp16)[name = tensor<string, []>("real_div_18")];
            tensor<fp16, [?, ?, ?, ?]> var_1568_cast_fp16 = tile(reps = real_div_18, x = var_1566_cast_fp16)[name = tensor<string, []>("op_1568_cast_fp16")];
            tensor<int32, [3]> var_1569 = const()[name = tensor<string, []>("op_1569"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_75_cast_fp16 = reshape(shape = var_1569, x = var_1568_cast_fp16)[name = tensor<string, []>("seg_75_cast_fp16")];
            tensor<int32, [3]> var_1571_shape_cast_fp16 = shape(x = input_447_cast_fp16)[name = tensor<string, []>("op_1571_shape_cast_fp16")];
            tensor<int32, []> gather_79_axis_0 = const()[name = tensor<string, []>("gather_79_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_79_batch_dims_0 = const()[name = tensor<string, []>("gather_79_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_79_validate_indices_0 = const()[name = tensor<string, []>("gather_79_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1571_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1571_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_79_to_uint16 = const()[name = tensor<string, []>("select_79_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1571_shape_cast_fp16_to_uint16 = cast(dtype = var_1571_shape_cast_fp16_to_uint16_dtype_0, x = var_1571_shape_cast_fp16)[name = tensor<string, []>("cast_241")];
            tensor<uint16, []> gather_79_cast_uint16 = gather(axis = gather_79_axis_0, batch_dims = gather_79_batch_dims_0, indices = select_79_to_uint16, validate_indices = gather_79_validate_indices_0, x = var_1571_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_79_cast_uint16")];
            tensor<string, []> gather_79_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_79_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_38_values0_0 = const()[name = tensor<string, []>("concat_38_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_38_values1_0 = const()[name = tensor<string, []>("concat_38_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_38_axis_0 = const()[name = tensor<string, []>("concat_38_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_38_interleave_0 = const()[name = tensor<string, []>("concat_38_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_79_cast_uint16_to_int32 = cast(dtype = gather_79_cast_uint16_to_int32_dtype_0, x = gather_79_cast_uint16)[name = tensor<string, []>("cast_240")];
            tensor<int32, [3]> concat_38 = concat(axis = concat_38_axis_0, interleave = concat_38_interleave_0, values = (concat_38_values0_0, concat_38_values1_0, gather_79_cast_uint16_to_int32))[name = tensor<string, []>("concat_38")];
            tensor<int32, [3]> var_1572_begin_0 = const()[name = tensor<string, []>("op_1572_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1572_end_mask_0 = const()[name = tensor<string, []>("op_1572_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1572_cast_fp16 = slice_by_index(begin = var_1572_begin_0, end = concat_38, end_mask = var_1572_end_mask_0, x = seg_75_cast_fp16)[name = tensor<string, []>("op_1572_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_449_cast_fp16 = add(x = var_1558_cast_fp16, y = var_1572_cast_fp16)[name = tensor<string, []>("input_449_cast_fp16")];
            tensor<string, []> input_451_pad_type_0 = const()[name = tensor<string, []>("input_451_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_451_strides_0 = const()[name = tensor<string, []>("input_451_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_451_pad_0 = const()[name = tensor<string, []>("input_451_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_451_dilations_0 = const()[name = tensor<string, []>("input_451_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_451_groups_0 = const()[name = tensor<string, []>("input_451_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd7_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd7_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3320064)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd7_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd7_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3336512)))];
            tensor<fp16, [1, 64, ?]> input_451_cast_fp16 = conv(bias = net_xvector_block2_tdnnd7_cam_layer_linear1_bias_to_fp16, dilations = input_451_dilations_0, groups = input_451_groups_0, pad = input_451_pad_0, pad_type = input_451_pad_type_0, strides = input_451_strides_0, weight = net_xvector_block2_tdnnd7_cam_layer_linear1_weight_to_fp16, x = input_449_cast_fp16)[name = tensor<string, []>("input_451_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_453_cast_fp16 = relu(x = input_451_cast_fp16)[name = tensor<string, []>("input_453_cast_fp16")];
            tensor<string, []> input_455_pad_type_0 = const()[name = tensor<string, []>("input_455_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_455_strides_0 = const()[name = tensor<string, []>("input_455_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_455_pad_0 = const()[name = tensor<string, []>("input_455_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_455_dilations_0 = const()[name = tensor<string, []>("input_455_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_455_groups_0 = const()[name = tensor<string, []>("input_455_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd7_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd7_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3336704)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd7_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd7_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3340864)))];
            tensor<fp16, [1, 32, ?]> input_455_cast_fp16 = conv(bias = net_xvector_block2_tdnnd7_cam_layer_linear2_bias_to_fp16, dilations = input_455_dilations_0, groups = input_455_groups_0, pad = input_455_pad_0, pad_type = input_455_pad_type_0, strides = input_455_strides_0, weight = net_xvector_block2_tdnnd7_cam_layer_linear2_weight_to_fp16, x = input_453_cast_fp16)[name = tensor<string, []>("input_455_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_37_cast_fp16 = sigmoid(x = input_455_cast_fp16)[name = tensor<string, []>("m_37_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1590_cast_fp16 = mul(x = y_37_cast_fp16, y = m_37_cast_fp16)[name = tensor<string, []>("op_1590_cast_fp16")];
            tensor<bool, []> input_457_interleave_0 = const()[name = tensor<string, []>("input_457_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 480, ?]> input_457_cast_fp16 = concat(axis = var_11, interleave = input_457_interleave_0, values = (input_437_cast_fp16, var_1590_cast_fp16))[name = tensor<string, []>("input_457_cast_fp16")];
            tensor<fp16, [480]> net_xvector_block2_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3340992)))];
            tensor<fp16, [480]> net_xvector_block2_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3342016)))];
            tensor<fp16, [480]> net_xvector_block2_tdnnd8_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd8_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3343040)))];
            tensor<fp16, [480]> net_xvector_block2_tdnnd8_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd8_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [480]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3344064)))];
            tensor<fp16, [1, 480, ?]> input_459_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd8_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd8_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16, x = input_457_cast_fp16)[name = tensor<string, []>("input_459_cast_fp16")];
            tensor<fp16, [1, 480, ?]> input_461_cast_fp16 = relu(x = input_459_cast_fp16)[name = tensor<string, []>("input_461_cast_fp16")];
            tensor<string, []> input_463_pad_type_0 = const()[name = tensor<string, []>("input_463_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_463_strides_0 = const()[name = tensor<string, []>("input_463_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_463_pad_0 = const()[name = tensor<string, []>("input_463_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_463_dilations_0 = const()[name = tensor<string, []>("input_463_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_463_groups_0 = const()[name = tensor<string, []>("input_463_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 480, 1]> const_64_to_fp16 = const()[name = tensor<string, []>("const_64_to_fp16"), val = tensor<fp16, [128, 480, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3345088)))];
            tensor<fp16, [128]> const_65_to_fp16 = const()[name = tensor<string, []>("const_65_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3468032)))];
            tensor<fp16, [1, 128, ?]> input_465_cast_fp16 = conv(bias = const_65_to_fp16, dilations = input_463_dilations_0, groups = input_463_groups_0, pad = input_463_pad_0, pad_type = input_463_pad_type_0, strides = input_463_strides_0, weight = const_64_to_fp16, x = input_461_cast_fp16)[name = tensor<string, []>("input_465_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_467_cast_fp16 = relu(x = input_465_cast_fp16)[name = tensor<string, []>("input_467_cast_fp16")];
            tensor<string, []> y_39_pad_type_0 = const()[name = tensor<string, []>("y_39_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_39_pad_0 = const()[name = tensor<string, []>("y_39_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_39_dilations_0 = const()[name = tensor<string, []>("y_39_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_39_strides_0 = const()[name = tensor<string, []>("y_39_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_39_groups_0 = const()[name = tensor<string, []>("y_39_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd8_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd8_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3468352)))];
            tensor<fp16, [1, 32, ?]> y_39_cast_fp16 = conv(dilations = y_39_dilations_0, groups = y_39_groups_0, pad = y_39_pad_0, pad_type = y_39_pad_type_0, strides = y_39_strides_0, weight = net_xvector_block2_tdnnd8_cam_layer_linear_local_weight_to_fp16, x = input_467_cast_fp16)[name = tensor<string, []>("y_39_cast_fp16")];
            tensor<int32, [1]> var_1627_axes_0 = const()[name = tensor<string, []>("op_1627_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1627_keep_dims_0 = const()[name = tensor<string, []>("op_1627_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1627_cast_fp16 = reduce_mean(axes = var_1627_axes_0, keep_dims = var_1627_keep_dims_0, x = input_467_cast_fp16)[name = tensor<string, []>("op_1627_cast_fp16")];
            tensor<int32, [1]> var_1628 = const()[name = tensor<string, []>("op_1628"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1629 = const()[name = tensor<string, []>("op_1629"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_77_pad_type_0 = const()[name = tensor<string, []>("seg_77_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_77_pad_0 = const()[name = tensor<string, []>("seg_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_77_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_77_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_77_ceil_mode_0 = const()[name = tensor<string, []>("seg_77_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_77_cast_fp16 = avg_pool(ceil_mode = seg_77_ceil_mode_0, exclude_padding_from_average = seg_77_exclude_padding_from_average_0, kernel_sizes = var_1628, pad = seg_77_pad_0, pad_type = seg_77_pad_type_0, strides = var_1629, x = input_467_cast_fp16)[name = tensor<string, []>("seg_77_cast_fp16")];
            tensor<int32, [3]> var_1632_shape_cast_fp16 = shape(x = seg_77_cast_fp16)[name = tensor<string, []>("op_1632_shape_cast_fp16")];
            tensor<int32, []> gather_80 = const()[name = tensor<string, []>("gather_80"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_81 = const()[name = tensor<string, []>("gather_81"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_82_axis_0 = const()[name = tensor<string, []>("gather_82_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_82_batch_dims_0 = const()[name = tensor<string, []>("gather_82_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_82_validate_indices_0 = const()[name = tensor<string, []>("gather_82_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1632_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1632_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_82_to_uint16 = const()[name = tensor<string, []>("select_82_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1632_shape_cast_fp16_to_uint16 = cast(dtype = var_1632_shape_cast_fp16_to_uint16_dtype_0, x = var_1632_shape_cast_fp16)[name = tensor<string, []>("cast_239")];
            tensor<uint16, []> gather_82_cast_uint16 = gather(axis = gather_82_axis_0, batch_dims = gather_82_batch_dims_0, indices = select_82_to_uint16, validate_indices = gather_82_validate_indices_0, x = var_1632_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_82_cast_uint16")];
            tensor<string, []> gather_82_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_82_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1635_axes_0 = const()[name = tensor<string, []>("op_1635_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1635_cast_fp16 = expand_dims(axes = var_1635_axes_0, x = seg_77_cast_fp16)[name = tensor<string, []>("op_1635_cast_fp16")];
            tensor<int32, []> concat_39_axis_0 = const()[name = tensor<string, []>("concat_39_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_39_interleave_0 = const()[name = tensor<string, []>("concat_39_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_82_cast_uint16_to_int32 = cast(dtype = gather_82_cast_uint16_to_int32_dtype_0, x = gather_82_cast_uint16)[name = tensor<string, []>("cast_238")];
            tensor<int32, [4]> concat_39 = concat(axis = concat_39_axis_0, interleave = concat_39_interleave_0, values = (gather_80, gather_81, gather_82_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_39")];
            tensor<int32, [4]> shape_102_cast_fp16 = shape(x = var_1635_cast_fp16)[name = tensor<string, []>("shape_102_cast_fp16")];
            tensor<int32, [4]> real_div_19 = real_div(x = concat_39, y = shape_102_cast_fp16)[name = tensor<string, []>("real_div_19")];
            tensor<fp16, [?, ?, ?, ?]> var_1637_cast_fp16 = tile(reps = real_div_19, x = var_1635_cast_fp16)[name = tensor<string, []>("op_1637_cast_fp16")];
            tensor<int32, [3]> var_1638 = const()[name = tensor<string, []>("op_1638"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_79_cast_fp16 = reshape(shape = var_1638, x = var_1637_cast_fp16)[name = tensor<string, []>("seg_79_cast_fp16")];
            tensor<int32, [3]> var_1640_shape_cast_fp16 = shape(x = input_467_cast_fp16)[name = tensor<string, []>("op_1640_shape_cast_fp16")];
            tensor<int32, []> gather_83_axis_0 = const()[name = tensor<string, []>("gather_83_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_83_batch_dims_0 = const()[name = tensor<string, []>("gather_83_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_83_validate_indices_0 = const()[name = tensor<string, []>("gather_83_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1640_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1640_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_83_to_uint16 = const()[name = tensor<string, []>("select_83_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1640_shape_cast_fp16_to_uint16 = cast(dtype = var_1640_shape_cast_fp16_to_uint16_dtype_0, x = var_1640_shape_cast_fp16)[name = tensor<string, []>("cast_237")];
            tensor<uint16, []> gather_83_cast_uint16 = gather(axis = gather_83_axis_0, batch_dims = gather_83_batch_dims_0, indices = select_83_to_uint16, validate_indices = gather_83_validate_indices_0, x = var_1640_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_83_cast_uint16")];
            tensor<string, []> gather_83_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_83_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_40_values0_0 = const()[name = tensor<string, []>("concat_40_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_40_values1_0 = const()[name = tensor<string, []>("concat_40_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_40_axis_0 = const()[name = tensor<string, []>("concat_40_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_40_interleave_0 = const()[name = tensor<string, []>("concat_40_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_83_cast_uint16_to_int32 = cast(dtype = gather_83_cast_uint16_to_int32_dtype_0, x = gather_83_cast_uint16)[name = tensor<string, []>("cast_236")];
            tensor<int32, [3]> concat_40 = concat(axis = concat_40_axis_0, interleave = concat_40_interleave_0, values = (concat_40_values0_0, concat_40_values1_0, gather_83_cast_uint16_to_int32))[name = tensor<string, []>("concat_40")];
            tensor<int32, [3]> var_1641_begin_0 = const()[name = tensor<string, []>("op_1641_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1641_end_mask_0 = const()[name = tensor<string, []>("op_1641_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1641_cast_fp16 = slice_by_index(begin = var_1641_begin_0, end = concat_40, end_mask = var_1641_end_mask_0, x = seg_79_cast_fp16)[name = tensor<string, []>("op_1641_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_469_cast_fp16 = add(x = var_1627_cast_fp16, y = var_1641_cast_fp16)[name = tensor<string, []>("input_469_cast_fp16")];
            tensor<string, []> input_471_pad_type_0 = const()[name = tensor<string, []>("input_471_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_471_strides_0 = const()[name = tensor<string, []>("input_471_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_471_pad_0 = const()[name = tensor<string, []>("input_471_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_471_dilations_0 = const()[name = tensor<string, []>("input_471_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_471_groups_0 = const()[name = tensor<string, []>("input_471_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd8_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd8_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3492992)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd8_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd8_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3509440)))];
            tensor<fp16, [1, 64, ?]> input_471_cast_fp16 = conv(bias = net_xvector_block2_tdnnd8_cam_layer_linear1_bias_to_fp16, dilations = input_471_dilations_0, groups = input_471_groups_0, pad = input_471_pad_0, pad_type = input_471_pad_type_0, strides = input_471_strides_0, weight = net_xvector_block2_tdnnd8_cam_layer_linear1_weight_to_fp16, x = input_469_cast_fp16)[name = tensor<string, []>("input_471_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_473_cast_fp16 = relu(x = input_471_cast_fp16)[name = tensor<string, []>("input_473_cast_fp16")];
            tensor<string, []> input_475_pad_type_0 = const()[name = tensor<string, []>("input_475_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_475_strides_0 = const()[name = tensor<string, []>("input_475_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_475_pad_0 = const()[name = tensor<string, []>("input_475_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_475_dilations_0 = const()[name = tensor<string, []>("input_475_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_475_groups_0 = const()[name = tensor<string, []>("input_475_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd8_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd8_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3509632)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd8_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd8_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3513792)))];
            tensor<fp16, [1, 32, ?]> input_475_cast_fp16 = conv(bias = net_xvector_block2_tdnnd8_cam_layer_linear2_bias_to_fp16, dilations = input_475_dilations_0, groups = input_475_groups_0, pad = input_475_pad_0, pad_type = input_475_pad_type_0, strides = input_475_strides_0, weight = net_xvector_block2_tdnnd8_cam_layer_linear2_weight_to_fp16, x = input_473_cast_fp16)[name = tensor<string, []>("input_475_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_39_cast_fp16 = sigmoid(x = input_475_cast_fp16)[name = tensor<string, []>("m_39_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1659_cast_fp16 = mul(x = y_39_cast_fp16, y = m_39_cast_fp16)[name = tensor<string, []>("op_1659_cast_fp16")];
            tensor<bool, []> input_477_interleave_0 = const()[name = tensor<string, []>("input_477_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 512, ?]> input_477_cast_fp16 = concat(axis = var_11, interleave = input_477_interleave_0, values = (input_457_cast_fp16, var_1659_cast_fp16))[name = tensor<string, []>("input_477_cast_fp16")];
            tensor<fp16, [512]> net_xvector_block2_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3513920)))];
            tensor<fp16, [512]> net_xvector_block2_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3515008)))];
            tensor<fp16, [512]> net_xvector_block2_tdnnd9_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd9_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3516096)))];
            tensor<fp16, [512]> net_xvector_block2_tdnnd9_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd9_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3517184)))];
            tensor<fp16, [1, 512, ?]> input_479_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd9_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd9_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16, x = input_477_cast_fp16)[name = tensor<string, []>("input_479_cast_fp16")];
            tensor<fp16, [1, 512, ?]> input_481_cast_fp16 = relu(x = input_479_cast_fp16)[name = tensor<string, []>("input_481_cast_fp16")];
            tensor<string, []> input_483_pad_type_0 = const()[name = tensor<string, []>("input_483_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_483_strides_0 = const()[name = tensor<string, []>("input_483_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_483_pad_0 = const()[name = tensor<string, []>("input_483_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_483_dilations_0 = const()[name = tensor<string, []>("input_483_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_483_groups_0 = const()[name = tensor<string, []>("input_483_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 512, 1]> const_66_to_fp16 = const()[name = tensor<string, []>("const_66_to_fp16"), val = tensor<fp16, [128, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3518272)))];
            tensor<fp16, [128]> const_67_to_fp16 = const()[name = tensor<string, []>("const_67_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3649408)))];
            tensor<fp16, [1, 128, ?]> input_485_cast_fp16 = conv(bias = const_67_to_fp16, dilations = input_483_dilations_0, groups = input_483_groups_0, pad = input_483_pad_0, pad_type = input_483_pad_type_0, strides = input_483_strides_0, weight = const_66_to_fp16, x = input_481_cast_fp16)[name = tensor<string, []>("input_485_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_487_cast_fp16 = relu(x = input_485_cast_fp16)[name = tensor<string, []>("input_487_cast_fp16")];
            tensor<string, []> y_41_pad_type_0 = const()[name = tensor<string, []>("y_41_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_41_pad_0 = const()[name = tensor<string, []>("y_41_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_41_dilations_0 = const()[name = tensor<string, []>("y_41_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_41_strides_0 = const()[name = tensor<string, []>("y_41_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_41_groups_0 = const()[name = tensor<string, []>("y_41_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd9_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd9_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3649728)))];
            tensor<fp16, [1, 32, ?]> y_41_cast_fp16 = conv(dilations = y_41_dilations_0, groups = y_41_groups_0, pad = y_41_pad_0, pad_type = y_41_pad_type_0, strides = y_41_strides_0, weight = net_xvector_block2_tdnnd9_cam_layer_linear_local_weight_to_fp16, x = input_487_cast_fp16)[name = tensor<string, []>("y_41_cast_fp16")];
            tensor<int32, [1]> var_1696_axes_0 = const()[name = tensor<string, []>("op_1696_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1696_keep_dims_0 = const()[name = tensor<string, []>("op_1696_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1696_cast_fp16 = reduce_mean(axes = var_1696_axes_0, keep_dims = var_1696_keep_dims_0, x = input_487_cast_fp16)[name = tensor<string, []>("op_1696_cast_fp16")];
            tensor<int32, [1]> var_1697 = const()[name = tensor<string, []>("op_1697"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1698 = const()[name = tensor<string, []>("op_1698"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_81_pad_type_0 = const()[name = tensor<string, []>("seg_81_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_81_pad_0 = const()[name = tensor<string, []>("seg_81_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_81_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_81_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_81_ceil_mode_0 = const()[name = tensor<string, []>("seg_81_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_81_cast_fp16 = avg_pool(ceil_mode = seg_81_ceil_mode_0, exclude_padding_from_average = seg_81_exclude_padding_from_average_0, kernel_sizes = var_1697, pad = seg_81_pad_0, pad_type = seg_81_pad_type_0, strides = var_1698, x = input_487_cast_fp16)[name = tensor<string, []>("seg_81_cast_fp16")];
            tensor<int32, [3]> var_1701_shape_cast_fp16 = shape(x = seg_81_cast_fp16)[name = tensor<string, []>("op_1701_shape_cast_fp16")];
            tensor<int32, []> gather_84 = const()[name = tensor<string, []>("gather_84"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_85 = const()[name = tensor<string, []>("gather_85"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_86_axis_0 = const()[name = tensor<string, []>("gather_86_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_86_batch_dims_0 = const()[name = tensor<string, []>("gather_86_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_86_validate_indices_0 = const()[name = tensor<string, []>("gather_86_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1701_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1701_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_86_to_uint16 = const()[name = tensor<string, []>("select_86_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1701_shape_cast_fp16_to_uint16 = cast(dtype = var_1701_shape_cast_fp16_to_uint16_dtype_0, x = var_1701_shape_cast_fp16)[name = tensor<string, []>("cast_235")];
            tensor<uint16, []> gather_86_cast_uint16 = gather(axis = gather_86_axis_0, batch_dims = gather_86_batch_dims_0, indices = select_86_to_uint16, validate_indices = gather_86_validate_indices_0, x = var_1701_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_86_cast_uint16")];
            tensor<string, []> gather_86_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_86_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1704_axes_0 = const()[name = tensor<string, []>("op_1704_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1704_cast_fp16 = expand_dims(axes = var_1704_axes_0, x = seg_81_cast_fp16)[name = tensor<string, []>("op_1704_cast_fp16")];
            tensor<int32, []> concat_41_axis_0 = const()[name = tensor<string, []>("concat_41_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_41_interleave_0 = const()[name = tensor<string, []>("concat_41_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_86_cast_uint16_to_int32 = cast(dtype = gather_86_cast_uint16_to_int32_dtype_0, x = gather_86_cast_uint16)[name = tensor<string, []>("cast_234")];
            tensor<int32, [4]> concat_41 = concat(axis = concat_41_axis_0, interleave = concat_41_interleave_0, values = (gather_84, gather_85, gather_86_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_41")];
            tensor<int32, [4]> shape_107_cast_fp16 = shape(x = var_1704_cast_fp16)[name = tensor<string, []>("shape_107_cast_fp16")];
            tensor<int32, [4]> real_div_20 = real_div(x = concat_41, y = shape_107_cast_fp16)[name = tensor<string, []>("real_div_20")];
            tensor<fp16, [?, ?, ?, ?]> var_1706_cast_fp16 = tile(reps = real_div_20, x = var_1704_cast_fp16)[name = tensor<string, []>("op_1706_cast_fp16")];
            tensor<int32, [3]> var_1707 = const()[name = tensor<string, []>("op_1707"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_83_cast_fp16 = reshape(shape = var_1707, x = var_1706_cast_fp16)[name = tensor<string, []>("seg_83_cast_fp16")];
            tensor<int32, [3]> var_1709_shape_cast_fp16 = shape(x = input_487_cast_fp16)[name = tensor<string, []>("op_1709_shape_cast_fp16")];
            tensor<int32, []> gather_87_axis_0 = const()[name = tensor<string, []>("gather_87_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_87_batch_dims_0 = const()[name = tensor<string, []>("gather_87_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_87_validate_indices_0 = const()[name = tensor<string, []>("gather_87_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1709_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1709_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_87_to_uint16 = const()[name = tensor<string, []>("select_87_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1709_shape_cast_fp16_to_uint16 = cast(dtype = var_1709_shape_cast_fp16_to_uint16_dtype_0, x = var_1709_shape_cast_fp16)[name = tensor<string, []>("cast_233")];
            tensor<uint16, []> gather_87_cast_uint16 = gather(axis = gather_87_axis_0, batch_dims = gather_87_batch_dims_0, indices = select_87_to_uint16, validate_indices = gather_87_validate_indices_0, x = var_1709_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_87_cast_uint16")];
            tensor<string, []> gather_87_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_87_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_42_values0_0 = const()[name = tensor<string, []>("concat_42_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_42_values1_0 = const()[name = tensor<string, []>("concat_42_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_42_axis_0 = const()[name = tensor<string, []>("concat_42_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_42_interleave_0 = const()[name = tensor<string, []>("concat_42_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_87_cast_uint16_to_int32 = cast(dtype = gather_87_cast_uint16_to_int32_dtype_0, x = gather_87_cast_uint16)[name = tensor<string, []>("cast_232")];
            tensor<int32, [3]> concat_42 = concat(axis = concat_42_axis_0, interleave = concat_42_interleave_0, values = (concat_42_values0_0, concat_42_values1_0, gather_87_cast_uint16_to_int32))[name = tensor<string, []>("concat_42")];
            tensor<int32, [3]> var_1710_begin_0 = const()[name = tensor<string, []>("op_1710_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1710_end_mask_0 = const()[name = tensor<string, []>("op_1710_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1710_cast_fp16 = slice_by_index(begin = var_1710_begin_0, end = concat_42, end_mask = var_1710_end_mask_0, x = seg_83_cast_fp16)[name = tensor<string, []>("op_1710_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_489_cast_fp16 = add(x = var_1696_cast_fp16, y = var_1710_cast_fp16)[name = tensor<string, []>("input_489_cast_fp16")];
            tensor<string, []> input_491_pad_type_0 = const()[name = tensor<string, []>("input_491_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_491_strides_0 = const()[name = tensor<string, []>("input_491_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_491_pad_0 = const()[name = tensor<string, []>("input_491_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_491_dilations_0 = const()[name = tensor<string, []>("input_491_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_491_groups_0 = const()[name = tensor<string, []>("input_491_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd9_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd9_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3674368)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd9_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd9_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3690816)))];
            tensor<fp16, [1, 64, ?]> input_491_cast_fp16 = conv(bias = net_xvector_block2_tdnnd9_cam_layer_linear1_bias_to_fp16, dilations = input_491_dilations_0, groups = input_491_groups_0, pad = input_491_pad_0, pad_type = input_491_pad_type_0, strides = input_491_strides_0, weight = net_xvector_block2_tdnnd9_cam_layer_linear1_weight_to_fp16, x = input_489_cast_fp16)[name = tensor<string, []>("input_491_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_493_cast_fp16 = relu(x = input_491_cast_fp16)[name = tensor<string, []>("input_493_cast_fp16")];
            tensor<string, []> input_495_pad_type_0 = const()[name = tensor<string, []>("input_495_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_495_strides_0 = const()[name = tensor<string, []>("input_495_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_495_pad_0 = const()[name = tensor<string, []>("input_495_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_495_dilations_0 = const()[name = tensor<string, []>("input_495_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_495_groups_0 = const()[name = tensor<string, []>("input_495_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd9_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd9_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3691008)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd9_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd9_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3695168)))];
            tensor<fp16, [1, 32, ?]> input_495_cast_fp16 = conv(bias = net_xvector_block2_tdnnd9_cam_layer_linear2_bias_to_fp16, dilations = input_495_dilations_0, groups = input_495_groups_0, pad = input_495_pad_0, pad_type = input_495_pad_type_0, strides = input_495_strides_0, weight = net_xvector_block2_tdnnd9_cam_layer_linear2_weight_to_fp16, x = input_493_cast_fp16)[name = tensor<string, []>("input_495_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_41_cast_fp16 = sigmoid(x = input_495_cast_fp16)[name = tensor<string, []>("m_41_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1728_cast_fp16 = mul(x = y_41_cast_fp16, y = m_41_cast_fp16)[name = tensor<string, []>("op_1728_cast_fp16")];
            tensor<bool, []> input_497_interleave_0 = const()[name = tensor<string, []>("input_497_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 544, ?]> input_497_cast_fp16 = concat(axis = var_11, interleave = input_497_interleave_0, values = (input_477_cast_fp16, var_1728_cast_fp16))[name = tensor<string, []>("input_497_cast_fp16")];
            tensor<fp16, [544]> net_xvector_block2_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [544]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3695296)))];
            tensor<fp16, [544]> net_xvector_block2_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [544]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3696448)))];
            tensor<fp16, [544]> net_xvector_block2_tdnnd10_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd10_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [544]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3697600)))];
            tensor<fp16, [544]> net_xvector_block2_tdnnd10_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd10_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [544]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3698752)))];
            tensor<fp16, [1, 544, ?]> input_499_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd10_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd10_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16, x = input_497_cast_fp16)[name = tensor<string, []>("input_499_cast_fp16")];
            tensor<fp16, [1, 544, ?]> input_501_cast_fp16 = relu(x = input_499_cast_fp16)[name = tensor<string, []>("input_501_cast_fp16")];
            tensor<string, []> input_503_pad_type_0 = const()[name = tensor<string, []>("input_503_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_503_strides_0 = const()[name = tensor<string, []>("input_503_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_503_pad_0 = const()[name = tensor<string, []>("input_503_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_503_dilations_0 = const()[name = tensor<string, []>("input_503_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_503_groups_0 = const()[name = tensor<string, []>("input_503_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 544, 1]> const_68_to_fp16 = const()[name = tensor<string, []>("const_68_to_fp16"), val = tensor<fp16, [128, 544, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3699904)))];
            tensor<fp16, [128]> const_69_to_fp16 = const()[name = tensor<string, []>("const_69_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3839232)))];
            tensor<fp16, [1, 128, ?]> input_505_cast_fp16 = conv(bias = const_69_to_fp16, dilations = input_503_dilations_0, groups = input_503_groups_0, pad = input_503_pad_0, pad_type = input_503_pad_type_0, strides = input_503_strides_0, weight = const_68_to_fp16, x = input_501_cast_fp16)[name = tensor<string, []>("input_505_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_507_cast_fp16 = relu(x = input_505_cast_fp16)[name = tensor<string, []>("input_507_cast_fp16")];
            tensor<string, []> y_43_pad_type_0 = const()[name = tensor<string, []>("y_43_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_43_pad_0 = const()[name = tensor<string, []>("y_43_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_43_dilations_0 = const()[name = tensor<string, []>("y_43_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_43_strides_0 = const()[name = tensor<string, []>("y_43_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_43_groups_0 = const()[name = tensor<string, []>("y_43_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd10_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd10_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3839552)))];
            tensor<fp16, [1, 32, ?]> y_43_cast_fp16 = conv(dilations = y_43_dilations_0, groups = y_43_groups_0, pad = y_43_pad_0, pad_type = y_43_pad_type_0, strides = y_43_strides_0, weight = net_xvector_block2_tdnnd10_cam_layer_linear_local_weight_to_fp16, x = input_507_cast_fp16)[name = tensor<string, []>("y_43_cast_fp16")];
            tensor<int32, [1]> var_1765_axes_0 = const()[name = tensor<string, []>("op_1765_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1765_keep_dims_0 = const()[name = tensor<string, []>("op_1765_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1765_cast_fp16 = reduce_mean(axes = var_1765_axes_0, keep_dims = var_1765_keep_dims_0, x = input_507_cast_fp16)[name = tensor<string, []>("op_1765_cast_fp16")];
            tensor<int32, [1]> var_1766 = const()[name = tensor<string, []>("op_1766"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1767 = const()[name = tensor<string, []>("op_1767"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_85_pad_type_0 = const()[name = tensor<string, []>("seg_85_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_85_pad_0 = const()[name = tensor<string, []>("seg_85_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_85_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_85_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_85_ceil_mode_0 = const()[name = tensor<string, []>("seg_85_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_85_cast_fp16 = avg_pool(ceil_mode = seg_85_ceil_mode_0, exclude_padding_from_average = seg_85_exclude_padding_from_average_0, kernel_sizes = var_1766, pad = seg_85_pad_0, pad_type = seg_85_pad_type_0, strides = var_1767, x = input_507_cast_fp16)[name = tensor<string, []>("seg_85_cast_fp16")];
            tensor<int32, [3]> var_1770_shape_cast_fp16 = shape(x = seg_85_cast_fp16)[name = tensor<string, []>("op_1770_shape_cast_fp16")];
            tensor<int32, []> gather_88 = const()[name = tensor<string, []>("gather_88"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_89 = const()[name = tensor<string, []>("gather_89"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_90_axis_0 = const()[name = tensor<string, []>("gather_90_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_90_batch_dims_0 = const()[name = tensor<string, []>("gather_90_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_90_validate_indices_0 = const()[name = tensor<string, []>("gather_90_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1770_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1770_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_90_to_uint16 = const()[name = tensor<string, []>("select_90_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1770_shape_cast_fp16_to_uint16 = cast(dtype = var_1770_shape_cast_fp16_to_uint16_dtype_0, x = var_1770_shape_cast_fp16)[name = tensor<string, []>("cast_231")];
            tensor<uint16, []> gather_90_cast_uint16 = gather(axis = gather_90_axis_0, batch_dims = gather_90_batch_dims_0, indices = select_90_to_uint16, validate_indices = gather_90_validate_indices_0, x = var_1770_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_90_cast_uint16")];
            tensor<string, []> gather_90_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_90_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1773_axes_0 = const()[name = tensor<string, []>("op_1773_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1773_cast_fp16 = expand_dims(axes = var_1773_axes_0, x = seg_85_cast_fp16)[name = tensor<string, []>("op_1773_cast_fp16")];
            tensor<int32, []> concat_43_axis_0 = const()[name = tensor<string, []>("concat_43_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_43_interleave_0 = const()[name = tensor<string, []>("concat_43_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_90_cast_uint16_to_int32 = cast(dtype = gather_90_cast_uint16_to_int32_dtype_0, x = gather_90_cast_uint16)[name = tensor<string, []>("cast_230")];
            tensor<int32, [4]> concat_43 = concat(axis = concat_43_axis_0, interleave = concat_43_interleave_0, values = (gather_88, gather_89, gather_90_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_43")];
            tensor<int32, [4]> shape_112_cast_fp16 = shape(x = var_1773_cast_fp16)[name = tensor<string, []>("shape_112_cast_fp16")];
            tensor<int32, [4]> real_div_21 = real_div(x = concat_43, y = shape_112_cast_fp16)[name = tensor<string, []>("real_div_21")];
            tensor<fp16, [?, ?, ?, ?]> var_1775_cast_fp16 = tile(reps = real_div_21, x = var_1773_cast_fp16)[name = tensor<string, []>("op_1775_cast_fp16")];
            tensor<int32, [3]> var_1776 = const()[name = tensor<string, []>("op_1776"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_87_cast_fp16 = reshape(shape = var_1776, x = var_1775_cast_fp16)[name = tensor<string, []>("seg_87_cast_fp16")];
            tensor<int32, [3]> var_1778_shape_cast_fp16 = shape(x = input_507_cast_fp16)[name = tensor<string, []>("op_1778_shape_cast_fp16")];
            tensor<int32, []> gather_91_axis_0 = const()[name = tensor<string, []>("gather_91_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_91_batch_dims_0 = const()[name = tensor<string, []>("gather_91_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_91_validate_indices_0 = const()[name = tensor<string, []>("gather_91_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1778_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1778_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_91_to_uint16 = const()[name = tensor<string, []>("select_91_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1778_shape_cast_fp16_to_uint16 = cast(dtype = var_1778_shape_cast_fp16_to_uint16_dtype_0, x = var_1778_shape_cast_fp16)[name = tensor<string, []>("cast_229")];
            tensor<uint16, []> gather_91_cast_uint16 = gather(axis = gather_91_axis_0, batch_dims = gather_91_batch_dims_0, indices = select_91_to_uint16, validate_indices = gather_91_validate_indices_0, x = var_1778_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_91_cast_uint16")];
            tensor<string, []> gather_91_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_91_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_44_values0_0 = const()[name = tensor<string, []>("concat_44_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_44_values1_0 = const()[name = tensor<string, []>("concat_44_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_44_axis_0 = const()[name = tensor<string, []>("concat_44_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_44_interleave_0 = const()[name = tensor<string, []>("concat_44_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_91_cast_uint16_to_int32 = cast(dtype = gather_91_cast_uint16_to_int32_dtype_0, x = gather_91_cast_uint16)[name = tensor<string, []>("cast_228")];
            tensor<int32, [3]> concat_44 = concat(axis = concat_44_axis_0, interleave = concat_44_interleave_0, values = (concat_44_values0_0, concat_44_values1_0, gather_91_cast_uint16_to_int32))[name = tensor<string, []>("concat_44")];
            tensor<int32, [3]> var_1779_begin_0 = const()[name = tensor<string, []>("op_1779_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1779_end_mask_0 = const()[name = tensor<string, []>("op_1779_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1779_cast_fp16 = slice_by_index(begin = var_1779_begin_0, end = concat_44, end_mask = var_1779_end_mask_0, x = seg_87_cast_fp16)[name = tensor<string, []>("op_1779_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_509_cast_fp16 = add(x = var_1765_cast_fp16, y = var_1779_cast_fp16)[name = tensor<string, []>("input_509_cast_fp16")];
            tensor<string, []> input_511_pad_type_0 = const()[name = tensor<string, []>("input_511_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_511_strides_0 = const()[name = tensor<string, []>("input_511_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_511_pad_0 = const()[name = tensor<string, []>("input_511_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_511_dilations_0 = const()[name = tensor<string, []>("input_511_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_511_groups_0 = const()[name = tensor<string, []>("input_511_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd10_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd10_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3864192)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd10_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd10_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3880640)))];
            tensor<fp16, [1, 64, ?]> input_511_cast_fp16 = conv(bias = net_xvector_block2_tdnnd10_cam_layer_linear1_bias_to_fp16, dilations = input_511_dilations_0, groups = input_511_groups_0, pad = input_511_pad_0, pad_type = input_511_pad_type_0, strides = input_511_strides_0, weight = net_xvector_block2_tdnnd10_cam_layer_linear1_weight_to_fp16, x = input_509_cast_fp16)[name = tensor<string, []>("input_511_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_513_cast_fp16 = relu(x = input_511_cast_fp16)[name = tensor<string, []>("input_513_cast_fp16")];
            tensor<string, []> input_515_pad_type_0 = const()[name = tensor<string, []>("input_515_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_515_strides_0 = const()[name = tensor<string, []>("input_515_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_515_pad_0 = const()[name = tensor<string, []>("input_515_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_515_dilations_0 = const()[name = tensor<string, []>("input_515_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_515_groups_0 = const()[name = tensor<string, []>("input_515_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd10_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd10_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3880832)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd10_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd10_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3884992)))];
            tensor<fp16, [1, 32, ?]> input_515_cast_fp16 = conv(bias = net_xvector_block2_tdnnd10_cam_layer_linear2_bias_to_fp16, dilations = input_515_dilations_0, groups = input_515_groups_0, pad = input_515_pad_0, pad_type = input_515_pad_type_0, strides = input_515_strides_0, weight = net_xvector_block2_tdnnd10_cam_layer_linear2_weight_to_fp16, x = input_513_cast_fp16)[name = tensor<string, []>("input_515_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_43_cast_fp16 = sigmoid(x = input_515_cast_fp16)[name = tensor<string, []>("m_43_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1797_cast_fp16 = mul(x = y_43_cast_fp16, y = m_43_cast_fp16)[name = tensor<string, []>("op_1797_cast_fp16")];
            tensor<bool, []> input_517_interleave_0 = const()[name = tensor<string, []>("input_517_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 576, ?]> input_517_cast_fp16 = concat(axis = var_11, interleave = input_517_interleave_0, values = (input_497_cast_fp16, var_1797_cast_fp16))[name = tensor<string, []>("input_517_cast_fp16")];
            tensor<fp16, [576]> net_xvector_block2_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [576]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3885120)))];
            tensor<fp16, [576]> net_xvector_block2_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [576]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3886336)))];
            tensor<fp16, [576]> net_xvector_block2_tdnnd11_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd11_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [576]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3887552)))];
            tensor<fp16, [576]> net_xvector_block2_tdnnd11_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd11_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [576]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3888768)))];
            tensor<fp16, [1, 576, ?]> input_519_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd11_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd11_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16, x = input_517_cast_fp16)[name = tensor<string, []>("input_519_cast_fp16")];
            tensor<fp16, [1, 576, ?]> input_521_cast_fp16 = relu(x = input_519_cast_fp16)[name = tensor<string, []>("input_521_cast_fp16")];
            tensor<string, []> input_523_pad_type_0 = const()[name = tensor<string, []>("input_523_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_523_strides_0 = const()[name = tensor<string, []>("input_523_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_523_pad_0 = const()[name = tensor<string, []>("input_523_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_523_dilations_0 = const()[name = tensor<string, []>("input_523_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_523_groups_0 = const()[name = tensor<string, []>("input_523_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 576, 1]> const_70_to_fp16 = const()[name = tensor<string, []>("const_70_to_fp16"), val = tensor<fp16, [128, 576, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3889984)))];
            tensor<fp16, [128]> const_71_to_fp16 = const()[name = tensor<string, []>("const_71_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4037504)))];
            tensor<fp16, [1, 128, ?]> input_525_cast_fp16 = conv(bias = const_71_to_fp16, dilations = input_523_dilations_0, groups = input_523_groups_0, pad = input_523_pad_0, pad_type = input_523_pad_type_0, strides = input_523_strides_0, weight = const_70_to_fp16, x = input_521_cast_fp16)[name = tensor<string, []>("input_525_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_527_cast_fp16 = relu(x = input_525_cast_fp16)[name = tensor<string, []>("input_527_cast_fp16")];
            tensor<string, []> y_45_pad_type_0 = const()[name = tensor<string, []>("y_45_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_45_pad_0 = const()[name = tensor<string, []>("y_45_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_45_dilations_0 = const()[name = tensor<string, []>("y_45_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_45_strides_0 = const()[name = tensor<string, []>("y_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_45_groups_0 = const()[name = tensor<string, []>("y_45_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd11_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd11_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4037824)))];
            tensor<fp16, [1, 32, ?]> y_45_cast_fp16 = conv(dilations = y_45_dilations_0, groups = y_45_groups_0, pad = y_45_pad_0, pad_type = y_45_pad_type_0, strides = y_45_strides_0, weight = net_xvector_block2_tdnnd11_cam_layer_linear_local_weight_to_fp16, x = input_527_cast_fp16)[name = tensor<string, []>("y_45_cast_fp16")];
            tensor<int32, [1]> var_1834_axes_0 = const()[name = tensor<string, []>("op_1834_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1834_keep_dims_0 = const()[name = tensor<string, []>("op_1834_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1834_cast_fp16 = reduce_mean(axes = var_1834_axes_0, keep_dims = var_1834_keep_dims_0, x = input_527_cast_fp16)[name = tensor<string, []>("op_1834_cast_fp16")];
            tensor<int32, [1]> var_1835 = const()[name = tensor<string, []>("op_1835"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1836 = const()[name = tensor<string, []>("op_1836"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_89_pad_type_0 = const()[name = tensor<string, []>("seg_89_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_89_pad_0 = const()[name = tensor<string, []>("seg_89_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_89_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_89_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_89_ceil_mode_0 = const()[name = tensor<string, []>("seg_89_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_89_cast_fp16 = avg_pool(ceil_mode = seg_89_ceil_mode_0, exclude_padding_from_average = seg_89_exclude_padding_from_average_0, kernel_sizes = var_1835, pad = seg_89_pad_0, pad_type = seg_89_pad_type_0, strides = var_1836, x = input_527_cast_fp16)[name = tensor<string, []>("seg_89_cast_fp16")];
            tensor<int32, [3]> var_1839_shape_cast_fp16 = shape(x = seg_89_cast_fp16)[name = tensor<string, []>("op_1839_shape_cast_fp16")];
            tensor<int32, []> gather_92 = const()[name = tensor<string, []>("gather_92"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_93 = const()[name = tensor<string, []>("gather_93"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_94_axis_0 = const()[name = tensor<string, []>("gather_94_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_94_batch_dims_0 = const()[name = tensor<string, []>("gather_94_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_94_validate_indices_0 = const()[name = tensor<string, []>("gather_94_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1839_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1839_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_94_to_uint16 = const()[name = tensor<string, []>("select_94_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1839_shape_cast_fp16_to_uint16 = cast(dtype = var_1839_shape_cast_fp16_to_uint16_dtype_0, x = var_1839_shape_cast_fp16)[name = tensor<string, []>("cast_227")];
            tensor<uint16, []> gather_94_cast_uint16 = gather(axis = gather_94_axis_0, batch_dims = gather_94_batch_dims_0, indices = select_94_to_uint16, validate_indices = gather_94_validate_indices_0, x = var_1839_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_94_cast_uint16")];
            tensor<string, []> gather_94_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_94_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1842_axes_0 = const()[name = tensor<string, []>("op_1842_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1842_cast_fp16 = expand_dims(axes = var_1842_axes_0, x = seg_89_cast_fp16)[name = tensor<string, []>("op_1842_cast_fp16")];
            tensor<int32, []> concat_45_axis_0 = const()[name = tensor<string, []>("concat_45_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_45_interleave_0 = const()[name = tensor<string, []>("concat_45_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_94_cast_uint16_to_int32 = cast(dtype = gather_94_cast_uint16_to_int32_dtype_0, x = gather_94_cast_uint16)[name = tensor<string, []>("cast_226")];
            tensor<int32, [4]> concat_45 = concat(axis = concat_45_axis_0, interleave = concat_45_interleave_0, values = (gather_92, gather_93, gather_94_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_45")];
            tensor<int32, [4]> shape_117_cast_fp16 = shape(x = var_1842_cast_fp16)[name = tensor<string, []>("shape_117_cast_fp16")];
            tensor<int32, [4]> real_div_22 = real_div(x = concat_45, y = shape_117_cast_fp16)[name = tensor<string, []>("real_div_22")];
            tensor<fp16, [?, ?, ?, ?]> var_1844_cast_fp16 = tile(reps = real_div_22, x = var_1842_cast_fp16)[name = tensor<string, []>("op_1844_cast_fp16")];
            tensor<int32, [3]> var_1845 = const()[name = tensor<string, []>("op_1845"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_91_cast_fp16 = reshape(shape = var_1845, x = var_1844_cast_fp16)[name = tensor<string, []>("seg_91_cast_fp16")];
            tensor<int32, [3]> var_1847_shape_cast_fp16 = shape(x = input_527_cast_fp16)[name = tensor<string, []>("op_1847_shape_cast_fp16")];
            tensor<int32, []> gather_95_axis_0 = const()[name = tensor<string, []>("gather_95_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_95_batch_dims_0 = const()[name = tensor<string, []>("gather_95_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_95_validate_indices_0 = const()[name = tensor<string, []>("gather_95_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1847_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1847_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_95_to_uint16 = const()[name = tensor<string, []>("select_95_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1847_shape_cast_fp16_to_uint16 = cast(dtype = var_1847_shape_cast_fp16_to_uint16_dtype_0, x = var_1847_shape_cast_fp16)[name = tensor<string, []>("cast_225")];
            tensor<uint16, []> gather_95_cast_uint16 = gather(axis = gather_95_axis_0, batch_dims = gather_95_batch_dims_0, indices = select_95_to_uint16, validate_indices = gather_95_validate_indices_0, x = var_1847_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_95_cast_uint16")];
            tensor<string, []> gather_95_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_95_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_46_values0_0 = const()[name = tensor<string, []>("concat_46_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_46_values1_0 = const()[name = tensor<string, []>("concat_46_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_46_axis_0 = const()[name = tensor<string, []>("concat_46_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_46_interleave_0 = const()[name = tensor<string, []>("concat_46_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_95_cast_uint16_to_int32 = cast(dtype = gather_95_cast_uint16_to_int32_dtype_0, x = gather_95_cast_uint16)[name = tensor<string, []>("cast_224")];
            tensor<int32, [3]> concat_46 = concat(axis = concat_46_axis_0, interleave = concat_46_interleave_0, values = (concat_46_values0_0, concat_46_values1_0, gather_95_cast_uint16_to_int32))[name = tensor<string, []>("concat_46")];
            tensor<int32, [3]> var_1848_begin_0 = const()[name = tensor<string, []>("op_1848_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1848_end_mask_0 = const()[name = tensor<string, []>("op_1848_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1848_cast_fp16 = slice_by_index(begin = var_1848_begin_0, end = concat_46, end_mask = var_1848_end_mask_0, x = seg_91_cast_fp16)[name = tensor<string, []>("op_1848_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_529_cast_fp16 = add(x = var_1834_cast_fp16, y = var_1848_cast_fp16)[name = tensor<string, []>("input_529_cast_fp16")];
            tensor<string, []> input_531_pad_type_0 = const()[name = tensor<string, []>("input_531_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_531_strides_0 = const()[name = tensor<string, []>("input_531_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_531_pad_0 = const()[name = tensor<string, []>("input_531_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_531_dilations_0 = const()[name = tensor<string, []>("input_531_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_531_groups_0 = const()[name = tensor<string, []>("input_531_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd11_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd11_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4062464)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd11_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd11_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4078912)))];
            tensor<fp16, [1, 64, ?]> input_531_cast_fp16 = conv(bias = net_xvector_block2_tdnnd11_cam_layer_linear1_bias_to_fp16, dilations = input_531_dilations_0, groups = input_531_groups_0, pad = input_531_pad_0, pad_type = input_531_pad_type_0, strides = input_531_strides_0, weight = net_xvector_block2_tdnnd11_cam_layer_linear1_weight_to_fp16, x = input_529_cast_fp16)[name = tensor<string, []>("input_531_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_533_cast_fp16 = relu(x = input_531_cast_fp16)[name = tensor<string, []>("input_533_cast_fp16")];
            tensor<string, []> input_535_pad_type_0 = const()[name = tensor<string, []>("input_535_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_535_strides_0 = const()[name = tensor<string, []>("input_535_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_535_pad_0 = const()[name = tensor<string, []>("input_535_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_535_dilations_0 = const()[name = tensor<string, []>("input_535_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_535_groups_0 = const()[name = tensor<string, []>("input_535_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd11_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd11_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4079104)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd11_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd11_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4083264)))];
            tensor<fp16, [1, 32, ?]> input_535_cast_fp16 = conv(bias = net_xvector_block2_tdnnd11_cam_layer_linear2_bias_to_fp16, dilations = input_535_dilations_0, groups = input_535_groups_0, pad = input_535_pad_0, pad_type = input_535_pad_type_0, strides = input_535_strides_0, weight = net_xvector_block2_tdnnd11_cam_layer_linear2_weight_to_fp16, x = input_533_cast_fp16)[name = tensor<string, []>("input_535_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_45_cast_fp16 = sigmoid(x = input_535_cast_fp16)[name = tensor<string, []>("m_45_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1866_cast_fp16 = mul(x = y_45_cast_fp16, y = m_45_cast_fp16)[name = tensor<string, []>("op_1866_cast_fp16")];
            tensor<bool, []> input_537_interleave_0 = const()[name = tensor<string, []>("input_537_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 608, ?]> input_537_cast_fp16 = concat(axis = var_11, interleave = input_537_interleave_0, values = (input_517_cast_fp16, var_1866_cast_fp16))[name = tensor<string, []>("input_537_cast_fp16")];
            tensor<fp16, [608]> net_xvector_block2_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4083392)))];
            tensor<fp16, [608]> net_xvector_block2_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4084672)))];
            tensor<fp16, [608]> net_xvector_block2_tdnnd12_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd12_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4085952)))];
            tensor<fp16, [608]> net_xvector_block2_tdnnd12_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd12_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4087232)))];
            tensor<fp16, [1, 608, ?]> input_539_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd12_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd12_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16, x = input_537_cast_fp16)[name = tensor<string, []>("input_539_cast_fp16")];
            tensor<fp16, [1, 608, ?]> input_541_cast_fp16 = relu(x = input_539_cast_fp16)[name = tensor<string, []>("input_541_cast_fp16")];
            tensor<string, []> input_543_pad_type_0 = const()[name = tensor<string, []>("input_543_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_543_strides_0 = const()[name = tensor<string, []>("input_543_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_543_pad_0 = const()[name = tensor<string, []>("input_543_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_543_dilations_0 = const()[name = tensor<string, []>("input_543_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_543_groups_0 = const()[name = tensor<string, []>("input_543_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 608, 1]> const_72_to_fp16 = const()[name = tensor<string, []>("const_72_to_fp16"), val = tensor<fp16, [128, 608, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4088512)))];
            tensor<fp16, [128]> const_73_to_fp16 = const()[name = tensor<string, []>("const_73_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4244224)))];
            tensor<fp16, [1, 128, ?]> input_545_cast_fp16 = conv(bias = const_73_to_fp16, dilations = input_543_dilations_0, groups = input_543_groups_0, pad = input_543_pad_0, pad_type = input_543_pad_type_0, strides = input_543_strides_0, weight = const_72_to_fp16, x = input_541_cast_fp16)[name = tensor<string, []>("input_545_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_547_cast_fp16 = relu(x = input_545_cast_fp16)[name = tensor<string, []>("input_547_cast_fp16")];
            tensor<string, []> y_47_pad_type_0 = const()[name = tensor<string, []>("y_47_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_47_pad_0 = const()[name = tensor<string, []>("y_47_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_47_dilations_0 = const()[name = tensor<string, []>("y_47_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_47_strides_0 = const()[name = tensor<string, []>("y_47_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_47_groups_0 = const()[name = tensor<string, []>("y_47_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd12_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd12_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4244544)))];
            tensor<fp16, [1, 32, ?]> y_47_cast_fp16 = conv(dilations = y_47_dilations_0, groups = y_47_groups_0, pad = y_47_pad_0, pad_type = y_47_pad_type_0, strides = y_47_strides_0, weight = net_xvector_block2_tdnnd12_cam_layer_linear_local_weight_to_fp16, x = input_547_cast_fp16)[name = tensor<string, []>("y_47_cast_fp16")];
            tensor<int32, [1]> var_1903_axes_0 = const()[name = tensor<string, []>("op_1903_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1903_keep_dims_0 = const()[name = tensor<string, []>("op_1903_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1903_cast_fp16 = reduce_mean(axes = var_1903_axes_0, keep_dims = var_1903_keep_dims_0, x = input_547_cast_fp16)[name = tensor<string, []>("op_1903_cast_fp16")];
            tensor<int32, [1]> var_1904 = const()[name = tensor<string, []>("op_1904"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1905 = const()[name = tensor<string, []>("op_1905"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_93_pad_type_0 = const()[name = tensor<string, []>("seg_93_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_93_pad_0 = const()[name = tensor<string, []>("seg_93_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_93_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_93_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_93_ceil_mode_0 = const()[name = tensor<string, []>("seg_93_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_93_cast_fp16 = avg_pool(ceil_mode = seg_93_ceil_mode_0, exclude_padding_from_average = seg_93_exclude_padding_from_average_0, kernel_sizes = var_1904, pad = seg_93_pad_0, pad_type = seg_93_pad_type_0, strides = var_1905, x = input_547_cast_fp16)[name = tensor<string, []>("seg_93_cast_fp16")];
            tensor<int32, [3]> var_1908_shape_cast_fp16 = shape(x = seg_93_cast_fp16)[name = tensor<string, []>("op_1908_shape_cast_fp16")];
            tensor<int32, []> gather_96 = const()[name = tensor<string, []>("gather_96"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_97 = const()[name = tensor<string, []>("gather_97"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_98_axis_0 = const()[name = tensor<string, []>("gather_98_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_98_batch_dims_0 = const()[name = tensor<string, []>("gather_98_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_98_validate_indices_0 = const()[name = tensor<string, []>("gather_98_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1908_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1908_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_98_to_uint16 = const()[name = tensor<string, []>("select_98_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1908_shape_cast_fp16_to_uint16 = cast(dtype = var_1908_shape_cast_fp16_to_uint16_dtype_0, x = var_1908_shape_cast_fp16)[name = tensor<string, []>("cast_223")];
            tensor<uint16, []> gather_98_cast_uint16 = gather(axis = gather_98_axis_0, batch_dims = gather_98_batch_dims_0, indices = select_98_to_uint16, validate_indices = gather_98_validate_indices_0, x = var_1908_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_98_cast_uint16")];
            tensor<string, []> gather_98_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_98_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1911_axes_0 = const()[name = tensor<string, []>("op_1911_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1911_cast_fp16 = expand_dims(axes = var_1911_axes_0, x = seg_93_cast_fp16)[name = tensor<string, []>("op_1911_cast_fp16")];
            tensor<int32, []> concat_47_axis_0 = const()[name = tensor<string, []>("concat_47_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_47_interleave_0 = const()[name = tensor<string, []>("concat_47_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_98_cast_uint16_to_int32 = cast(dtype = gather_98_cast_uint16_to_int32_dtype_0, x = gather_98_cast_uint16)[name = tensor<string, []>("cast_222")];
            tensor<int32, [4]> concat_47 = concat(axis = concat_47_axis_0, interleave = concat_47_interleave_0, values = (gather_96, gather_97, gather_98_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_47")];
            tensor<int32, [4]> shape_122_cast_fp16 = shape(x = var_1911_cast_fp16)[name = tensor<string, []>("shape_122_cast_fp16")];
            tensor<int32, [4]> real_div_23 = real_div(x = concat_47, y = shape_122_cast_fp16)[name = tensor<string, []>("real_div_23")];
            tensor<fp16, [?, ?, ?, ?]> var_1913_cast_fp16 = tile(reps = real_div_23, x = var_1911_cast_fp16)[name = tensor<string, []>("op_1913_cast_fp16")];
            tensor<int32, [3]> var_1914 = const()[name = tensor<string, []>("op_1914"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_95_cast_fp16 = reshape(shape = var_1914, x = var_1913_cast_fp16)[name = tensor<string, []>("seg_95_cast_fp16")];
            tensor<int32, [3]> var_1916_shape_cast_fp16 = shape(x = input_547_cast_fp16)[name = tensor<string, []>("op_1916_shape_cast_fp16")];
            tensor<int32, []> gather_99_axis_0 = const()[name = tensor<string, []>("gather_99_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_99_batch_dims_0 = const()[name = tensor<string, []>("gather_99_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_99_validate_indices_0 = const()[name = tensor<string, []>("gather_99_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1916_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1916_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_99_to_uint16 = const()[name = tensor<string, []>("select_99_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1916_shape_cast_fp16_to_uint16 = cast(dtype = var_1916_shape_cast_fp16_to_uint16_dtype_0, x = var_1916_shape_cast_fp16)[name = tensor<string, []>("cast_221")];
            tensor<uint16, []> gather_99_cast_uint16 = gather(axis = gather_99_axis_0, batch_dims = gather_99_batch_dims_0, indices = select_99_to_uint16, validate_indices = gather_99_validate_indices_0, x = var_1916_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_99_cast_uint16")];
            tensor<string, []> gather_99_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_99_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_48_values0_0 = const()[name = tensor<string, []>("concat_48_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_48_values1_0 = const()[name = tensor<string, []>("concat_48_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_48_axis_0 = const()[name = tensor<string, []>("concat_48_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_48_interleave_0 = const()[name = tensor<string, []>("concat_48_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_99_cast_uint16_to_int32 = cast(dtype = gather_99_cast_uint16_to_int32_dtype_0, x = gather_99_cast_uint16)[name = tensor<string, []>("cast_220")];
            tensor<int32, [3]> concat_48 = concat(axis = concat_48_axis_0, interleave = concat_48_interleave_0, values = (concat_48_values0_0, concat_48_values1_0, gather_99_cast_uint16_to_int32))[name = tensor<string, []>("concat_48")];
            tensor<int32, [3]> var_1917_begin_0 = const()[name = tensor<string, []>("op_1917_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1917_end_mask_0 = const()[name = tensor<string, []>("op_1917_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1917_cast_fp16 = slice_by_index(begin = var_1917_begin_0, end = concat_48, end_mask = var_1917_end_mask_0, x = seg_95_cast_fp16)[name = tensor<string, []>("op_1917_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_549_cast_fp16 = add(x = var_1903_cast_fp16, y = var_1917_cast_fp16)[name = tensor<string, []>("input_549_cast_fp16")];
            tensor<string, []> input_551_pad_type_0 = const()[name = tensor<string, []>("input_551_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_551_strides_0 = const()[name = tensor<string, []>("input_551_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_551_pad_0 = const()[name = tensor<string, []>("input_551_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_551_dilations_0 = const()[name = tensor<string, []>("input_551_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_551_groups_0 = const()[name = tensor<string, []>("input_551_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd12_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd12_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4269184)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd12_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd12_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4285632)))];
            tensor<fp16, [1, 64, ?]> input_551_cast_fp16 = conv(bias = net_xvector_block2_tdnnd12_cam_layer_linear1_bias_to_fp16, dilations = input_551_dilations_0, groups = input_551_groups_0, pad = input_551_pad_0, pad_type = input_551_pad_type_0, strides = input_551_strides_0, weight = net_xvector_block2_tdnnd12_cam_layer_linear1_weight_to_fp16, x = input_549_cast_fp16)[name = tensor<string, []>("input_551_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_553_cast_fp16 = relu(x = input_551_cast_fp16)[name = tensor<string, []>("input_553_cast_fp16")];
            tensor<string, []> input_555_pad_type_0 = const()[name = tensor<string, []>("input_555_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_555_strides_0 = const()[name = tensor<string, []>("input_555_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_555_pad_0 = const()[name = tensor<string, []>("input_555_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_555_dilations_0 = const()[name = tensor<string, []>("input_555_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_555_groups_0 = const()[name = tensor<string, []>("input_555_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd12_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd12_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4285824)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd12_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd12_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4289984)))];
            tensor<fp16, [1, 32, ?]> input_555_cast_fp16 = conv(bias = net_xvector_block2_tdnnd12_cam_layer_linear2_bias_to_fp16, dilations = input_555_dilations_0, groups = input_555_groups_0, pad = input_555_pad_0, pad_type = input_555_pad_type_0, strides = input_555_strides_0, weight = net_xvector_block2_tdnnd12_cam_layer_linear2_weight_to_fp16, x = input_553_cast_fp16)[name = tensor<string, []>("input_555_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_47_cast_fp16 = sigmoid(x = input_555_cast_fp16)[name = tensor<string, []>("m_47_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_1935_cast_fp16 = mul(x = y_47_cast_fp16, y = m_47_cast_fp16)[name = tensor<string, []>("op_1935_cast_fp16")];
            tensor<bool, []> input_557_interleave_0 = const()[name = tensor<string, []>("input_557_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 640, ?]> input_557_cast_fp16 = concat(axis = var_11, interleave = input_557_interleave_0, values = (input_537_cast_fp16, var_1935_cast_fp16))[name = tensor<string, []>("input_557_cast_fp16")];
            tensor<fp16, [640]> net_xvector_block2_tdnnd13_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd13_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4290112)))];
            tensor<fp16, [640]> net_xvector_block2_tdnnd13_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd13_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4291456)))];
            tensor<fp16, [640]> net_xvector_block2_tdnnd13_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd13_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4292800)))];
            tensor<fp16, [640]> net_xvector_block2_tdnnd13_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd13_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4294144)))];
            tensor<fp16, [1, 640, ?]> input_559_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd13_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd13_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd13_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd13_nonlinear1_batchnorm_running_var_to_fp16, x = input_557_cast_fp16)[name = tensor<string, []>("input_559_cast_fp16")];
            tensor<fp16, [1, 640, ?]> input_561_cast_fp16 = relu(x = input_559_cast_fp16)[name = tensor<string, []>("input_561_cast_fp16")];
            tensor<string, []> input_563_pad_type_0 = const()[name = tensor<string, []>("input_563_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_563_strides_0 = const()[name = tensor<string, []>("input_563_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_563_pad_0 = const()[name = tensor<string, []>("input_563_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_563_dilations_0 = const()[name = tensor<string, []>("input_563_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_563_groups_0 = const()[name = tensor<string, []>("input_563_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 640, 1]> const_74_to_fp16 = const()[name = tensor<string, []>("const_74_to_fp16"), val = tensor<fp16, [128, 640, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4295488)))];
            tensor<fp16, [128]> const_75_to_fp16 = const()[name = tensor<string, []>("const_75_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4459392)))];
            tensor<fp16, [1, 128, ?]> input_565_cast_fp16 = conv(bias = const_75_to_fp16, dilations = input_563_dilations_0, groups = input_563_groups_0, pad = input_563_pad_0, pad_type = input_563_pad_type_0, strides = input_563_strides_0, weight = const_74_to_fp16, x = input_561_cast_fp16)[name = tensor<string, []>("input_565_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_567_cast_fp16 = relu(x = input_565_cast_fp16)[name = tensor<string, []>("input_567_cast_fp16")];
            tensor<string, []> y_49_pad_type_0 = const()[name = tensor<string, []>("y_49_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_49_pad_0 = const()[name = tensor<string, []>("y_49_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_49_dilations_0 = const()[name = tensor<string, []>("y_49_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_49_strides_0 = const()[name = tensor<string, []>("y_49_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_49_groups_0 = const()[name = tensor<string, []>("y_49_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd13_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd13_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4459712)))];
            tensor<fp16, [1, 32, ?]> y_49_cast_fp16 = conv(dilations = y_49_dilations_0, groups = y_49_groups_0, pad = y_49_pad_0, pad_type = y_49_pad_type_0, strides = y_49_strides_0, weight = net_xvector_block2_tdnnd13_cam_layer_linear_local_weight_to_fp16, x = input_567_cast_fp16)[name = tensor<string, []>("y_49_cast_fp16")];
            tensor<int32, [1]> var_1972_axes_0 = const()[name = tensor<string, []>("op_1972_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_1972_keep_dims_0 = const()[name = tensor<string, []>("op_1972_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_1972_cast_fp16 = reduce_mean(axes = var_1972_axes_0, keep_dims = var_1972_keep_dims_0, x = input_567_cast_fp16)[name = tensor<string, []>("op_1972_cast_fp16")];
            tensor<int32, [1]> var_1973 = const()[name = tensor<string, []>("op_1973"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_1974 = const()[name = tensor<string, []>("op_1974"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_97_pad_type_0 = const()[name = tensor<string, []>("seg_97_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_97_pad_0 = const()[name = tensor<string, []>("seg_97_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_97_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_97_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_97_ceil_mode_0 = const()[name = tensor<string, []>("seg_97_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_97_cast_fp16 = avg_pool(ceil_mode = seg_97_ceil_mode_0, exclude_padding_from_average = seg_97_exclude_padding_from_average_0, kernel_sizes = var_1973, pad = seg_97_pad_0, pad_type = seg_97_pad_type_0, strides = var_1974, x = input_567_cast_fp16)[name = tensor<string, []>("seg_97_cast_fp16")];
            tensor<int32, [3]> var_1977_shape_cast_fp16 = shape(x = seg_97_cast_fp16)[name = tensor<string, []>("op_1977_shape_cast_fp16")];
            tensor<int32, []> gather_100 = const()[name = tensor<string, []>("gather_100"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_101 = const()[name = tensor<string, []>("gather_101"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_102_axis_0 = const()[name = tensor<string, []>("gather_102_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_102_batch_dims_0 = const()[name = tensor<string, []>("gather_102_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_102_validate_indices_0 = const()[name = tensor<string, []>("gather_102_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1977_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1977_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_102_to_uint16 = const()[name = tensor<string, []>("select_102_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1977_shape_cast_fp16_to_uint16 = cast(dtype = var_1977_shape_cast_fp16_to_uint16_dtype_0, x = var_1977_shape_cast_fp16)[name = tensor<string, []>("cast_219")];
            tensor<uint16, []> gather_102_cast_uint16 = gather(axis = gather_102_axis_0, batch_dims = gather_102_batch_dims_0, indices = select_102_to_uint16, validate_indices = gather_102_validate_indices_0, x = var_1977_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_102_cast_uint16")];
            tensor<string, []> gather_102_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_102_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_1980_axes_0 = const()[name = tensor<string, []>("op_1980_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_1980_cast_fp16 = expand_dims(axes = var_1980_axes_0, x = seg_97_cast_fp16)[name = tensor<string, []>("op_1980_cast_fp16")];
            tensor<int32, []> concat_49_axis_0 = const()[name = tensor<string, []>("concat_49_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_49_interleave_0 = const()[name = tensor<string, []>("concat_49_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_102_cast_uint16_to_int32 = cast(dtype = gather_102_cast_uint16_to_int32_dtype_0, x = gather_102_cast_uint16)[name = tensor<string, []>("cast_218")];
            tensor<int32, [4]> concat_49 = concat(axis = concat_49_axis_0, interleave = concat_49_interleave_0, values = (gather_100, gather_101, gather_102_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_49")];
            tensor<int32, [4]> shape_127_cast_fp16 = shape(x = var_1980_cast_fp16)[name = tensor<string, []>("shape_127_cast_fp16")];
            tensor<int32, [4]> real_div_24 = real_div(x = concat_49, y = shape_127_cast_fp16)[name = tensor<string, []>("real_div_24")];
            tensor<fp16, [?, ?, ?, ?]> var_1982_cast_fp16 = tile(reps = real_div_24, x = var_1980_cast_fp16)[name = tensor<string, []>("op_1982_cast_fp16")];
            tensor<int32, [3]> var_1983 = const()[name = tensor<string, []>("op_1983"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_99_cast_fp16 = reshape(shape = var_1983, x = var_1982_cast_fp16)[name = tensor<string, []>("seg_99_cast_fp16")];
            tensor<int32, [3]> var_1985_shape_cast_fp16 = shape(x = input_567_cast_fp16)[name = tensor<string, []>("op_1985_shape_cast_fp16")];
            tensor<int32, []> gather_103_axis_0 = const()[name = tensor<string, []>("gather_103_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_103_batch_dims_0 = const()[name = tensor<string, []>("gather_103_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_103_validate_indices_0 = const()[name = tensor<string, []>("gather_103_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_1985_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_1985_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_103_to_uint16 = const()[name = tensor<string, []>("select_103_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_1985_shape_cast_fp16_to_uint16 = cast(dtype = var_1985_shape_cast_fp16_to_uint16_dtype_0, x = var_1985_shape_cast_fp16)[name = tensor<string, []>("cast_217")];
            tensor<uint16, []> gather_103_cast_uint16 = gather(axis = gather_103_axis_0, batch_dims = gather_103_batch_dims_0, indices = select_103_to_uint16, validate_indices = gather_103_validate_indices_0, x = var_1985_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_103_cast_uint16")];
            tensor<string, []> gather_103_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_103_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_50_values0_0 = const()[name = tensor<string, []>("concat_50_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_50_values1_0 = const()[name = tensor<string, []>("concat_50_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_50_axis_0 = const()[name = tensor<string, []>("concat_50_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_50_interleave_0 = const()[name = tensor<string, []>("concat_50_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_103_cast_uint16_to_int32 = cast(dtype = gather_103_cast_uint16_to_int32_dtype_0, x = gather_103_cast_uint16)[name = tensor<string, []>("cast_216")];
            tensor<int32, [3]> concat_50 = concat(axis = concat_50_axis_0, interleave = concat_50_interleave_0, values = (concat_50_values0_0, concat_50_values1_0, gather_103_cast_uint16_to_int32))[name = tensor<string, []>("concat_50")];
            tensor<int32, [3]> var_1986_begin_0 = const()[name = tensor<string, []>("op_1986_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_1986_end_mask_0 = const()[name = tensor<string, []>("op_1986_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_1986_cast_fp16 = slice_by_index(begin = var_1986_begin_0, end = concat_50, end_mask = var_1986_end_mask_0, x = seg_99_cast_fp16)[name = tensor<string, []>("op_1986_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_569_cast_fp16 = add(x = var_1972_cast_fp16, y = var_1986_cast_fp16)[name = tensor<string, []>("input_569_cast_fp16")];
            tensor<string, []> input_571_pad_type_0 = const()[name = tensor<string, []>("input_571_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_571_strides_0 = const()[name = tensor<string, []>("input_571_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_571_pad_0 = const()[name = tensor<string, []>("input_571_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_571_dilations_0 = const()[name = tensor<string, []>("input_571_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_571_groups_0 = const()[name = tensor<string, []>("input_571_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd13_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd13_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4484352)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd13_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd13_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4500800)))];
            tensor<fp16, [1, 64, ?]> input_571_cast_fp16 = conv(bias = net_xvector_block2_tdnnd13_cam_layer_linear1_bias_to_fp16, dilations = input_571_dilations_0, groups = input_571_groups_0, pad = input_571_pad_0, pad_type = input_571_pad_type_0, strides = input_571_strides_0, weight = net_xvector_block2_tdnnd13_cam_layer_linear1_weight_to_fp16, x = input_569_cast_fp16)[name = tensor<string, []>("input_571_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_573_cast_fp16 = relu(x = input_571_cast_fp16)[name = tensor<string, []>("input_573_cast_fp16")];
            tensor<string, []> input_575_pad_type_0 = const()[name = tensor<string, []>("input_575_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_575_strides_0 = const()[name = tensor<string, []>("input_575_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_575_pad_0 = const()[name = tensor<string, []>("input_575_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_575_dilations_0 = const()[name = tensor<string, []>("input_575_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_575_groups_0 = const()[name = tensor<string, []>("input_575_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd13_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd13_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4500992)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd13_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd13_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4505152)))];
            tensor<fp16, [1, 32, ?]> input_575_cast_fp16 = conv(bias = net_xvector_block2_tdnnd13_cam_layer_linear2_bias_to_fp16, dilations = input_575_dilations_0, groups = input_575_groups_0, pad = input_575_pad_0, pad_type = input_575_pad_type_0, strides = input_575_strides_0, weight = net_xvector_block2_tdnnd13_cam_layer_linear2_weight_to_fp16, x = input_573_cast_fp16)[name = tensor<string, []>("input_575_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_49_cast_fp16 = sigmoid(x = input_575_cast_fp16)[name = tensor<string, []>("m_49_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2004_cast_fp16 = mul(x = y_49_cast_fp16, y = m_49_cast_fp16)[name = tensor<string, []>("op_2004_cast_fp16")];
            tensor<bool, []> input_577_interleave_0 = const()[name = tensor<string, []>("input_577_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 672, ?]> input_577_cast_fp16 = concat(axis = var_11, interleave = input_577_interleave_0, values = (input_557_cast_fp16, var_2004_cast_fp16))[name = tensor<string, []>("input_577_cast_fp16")];
            tensor<fp16, [672]> net_xvector_block2_tdnnd14_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd14_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [672]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4505280)))];
            tensor<fp16, [672]> net_xvector_block2_tdnnd14_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd14_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [672]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4506688)))];
            tensor<fp16, [672]> net_xvector_block2_tdnnd14_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd14_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [672]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4508096)))];
            tensor<fp16, [672]> net_xvector_block2_tdnnd14_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd14_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [672]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4509504)))];
            tensor<fp16, [1, 672, ?]> input_579_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd14_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd14_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd14_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd14_nonlinear1_batchnorm_running_var_to_fp16, x = input_577_cast_fp16)[name = tensor<string, []>("input_579_cast_fp16")];
            tensor<fp16, [1, 672, ?]> input_581_cast_fp16 = relu(x = input_579_cast_fp16)[name = tensor<string, []>("input_581_cast_fp16")];
            tensor<string, []> input_583_pad_type_0 = const()[name = tensor<string, []>("input_583_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_583_strides_0 = const()[name = tensor<string, []>("input_583_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_583_pad_0 = const()[name = tensor<string, []>("input_583_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_583_dilations_0 = const()[name = tensor<string, []>("input_583_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_583_groups_0 = const()[name = tensor<string, []>("input_583_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 672, 1]> const_76_to_fp16 = const()[name = tensor<string, []>("const_76_to_fp16"), val = tensor<fp16, [128, 672, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4510912)))];
            tensor<fp16, [128]> const_77_to_fp16 = const()[name = tensor<string, []>("const_77_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4683008)))];
            tensor<fp16, [1, 128, ?]> input_585_cast_fp16 = conv(bias = const_77_to_fp16, dilations = input_583_dilations_0, groups = input_583_groups_0, pad = input_583_pad_0, pad_type = input_583_pad_type_0, strides = input_583_strides_0, weight = const_76_to_fp16, x = input_581_cast_fp16)[name = tensor<string, []>("input_585_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_587_cast_fp16 = relu(x = input_585_cast_fp16)[name = tensor<string, []>("input_587_cast_fp16")];
            tensor<string, []> y_51_pad_type_0 = const()[name = tensor<string, []>("y_51_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_51_pad_0 = const()[name = tensor<string, []>("y_51_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_51_dilations_0 = const()[name = tensor<string, []>("y_51_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_51_strides_0 = const()[name = tensor<string, []>("y_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_51_groups_0 = const()[name = tensor<string, []>("y_51_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd14_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd14_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4683328)))];
            tensor<fp16, [1, 32, ?]> y_51_cast_fp16 = conv(dilations = y_51_dilations_0, groups = y_51_groups_0, pad = y_51_pad_0, pad_type = y_51_pad_type_0, strides = y_51_strides_0, weight = net_xvector_block2_tdnnd14_cam_layer_linear_local_weight_to_fp16, x = input_587_cast_fp16)[name = tensor<string, []>("y_51_cast_fp16")];
            tensor<int32, [1]> var_2041_axes_0 = const()[name = tensor<string, []>("op_2041_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2041_keep_dims_0 = const()[name = tensor<string, []>("op_2041_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2041_cast_fp16 = reduce_mean(axes = var_2041_axes_0, keep_dims = var_2041_keep_dims_0, x = input_587_cast_fp16)[name = tensor<string, []>("op_2041_cast_fp16")];
            tensor<int32, [1]> var_2042 = const()[name = tensor<string, []>("op_2042"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2043 = const()[name = tensor<string, []>("op_2043"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_101_pad_type_0 = const()[name = tensor<string, []>("seg_101_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_101_pad_0 = const()[name = tensor<string, []>("seg_101_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_101_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_101_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_101_ceil_mode_0 = const()[name = tensor<string, []>("seg_101_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_101_cast_fp16 = avg_pool(ceil_mode = seg_101_ceil_mode_0, exclude_padding_from_average = seg_101_exclude_padding_from_average_0, kernel_sizes = var_2042, pad = seg_101_pad_0, pad_type = seg_101_pad_type_0, strides = var_2043, x = input_587_cast_fp16)[name = tensor<string, []>("seg_101_cast_fp16")];
            tensor<int32, [3]> var_2046_shape_cast_fp16 = shape(x = seg_101_cast_fp16)[name = tensor<string, []>("op_2046_shape_cast_fp16")];
            tensor<int32, []> gather_104 = const()[name = tensor<string, []>("gather_104"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_105 = const()[name = tensor<string, []>("gather_105"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_106_axis_0 = const()[name = tensor<string, []>("gather_106_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_106_batch_dims_0 = const()[name = tensor<string, []>("gather_106_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_106_validate_indices_0 = const()[name = tensor<string, []>("gather_106_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2046_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2046_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_106_to_uint16 = const()[name = tensor<string, []>("select_106_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2046_shape_cast_fp16_to_uint16 = cast(dtype = var_2046_shape_cast_fp16_to_uint16_dtype_0, x = var_2046_shape_cast_fp16)[name = tensor<string, []>("cast_215")];
            tensor<uint16, []> gather_106_cast_uint16 = gather(axis = gather_106_axis_0, batch_dims = gather_106_batch_dims_0, indices = select_106_to_uint16, validate_indices = gather_106_validate_indices_0, x = var_2046_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_106_cast_uint16")];
            tensor<string, []> gather_106_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_106_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2049_axes_0 = const()[name = tensor<string, []>("op_2049_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2049_cast_fp16 = expand_dims(axes = var_2049_axes_0, x = seg_101_cast_fp16)[name = tensor<string, []>("op_2049_cast_fp16")];
            tensor<int32, []> concat_51_axis_0 = const()[name = tensor<string, []>("concat_51_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_51_interleave_0 = const()[name = tensor<string, []>("concat_51_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_106_cast_uint16_to_int32 = cast(dtype = gather_106_cast_uint16_to_int32_dtype_0, x = gather_106_cast_uint16)[name = tensor<string, []>("cast_214")];
            tensor<int32, [4]> concat_51 = concat(axis = concat_51_axis_0, interleave = concat_51_interleave_0, values = (gather_104, gather_105, gather_106_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_51")];
            tensor<int32, [4]> shape_132_cast_fp16 = shape(x = var_2049_cast_fp16)[name = tensor<string, []>("shape_132_cast_fp16")];
            tensor<int32, [4]> real_div_25 = real_div(x = concat_51, y = shape_132_cast_fp16)[name = tensor<string, []>("real_div_25")];
            tensor<fp16, [?, ?, ?, ?]> var_2051_cast_fp16 = tile(reps = real_div_25, x = var_2049_cast_fp16)[name = tensor<string, []>("op_2051_cast_fp16")];
            tensor<int32, [3]> var_2052 = const()[name = tensor<string, []>("op_2052"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_103_cast_fp16 = reshape(shape = var_2052, x = var_2051_cast_fp16)[name = tensor<string, []>("seg_103_cast_fp16")];
            tensor<int32, [3]> var_2054_shape_cast_fp16 = shape(x = input_587_cast_fp16)[name = tensor<string, []>("op_2054_shape_cast_fp16")];
            tensor<int32, []> gather_107_axis_0 = const()[name = tensor<string, []>("gather_107_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_107_batch_dims_0 = const()[name = tensor<string, []>("gather_107_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_107_validate_indices_0 = const()[name = tensor<string, []>("gather_107_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2054_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2054_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_107_to_uint16 = const()[name = tensor<string, []>("select_107_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2054_shape_cast_fp16_to_uint16 = cast(dtype = var_2054_shape_cast_fp16_to_uint16_dtype_0, x = var_2054_shape_cast_fp16)[name = tensor<string, []>("cast_213")];
            tensor<uint16, []> gather_107_cast_uint16 = gather(axis = gather_107_axis_0, batch_dims = gather_107_batch_dims_0, indices = select_107_to_uint16, validate_indices = gather_107_validate_indices_0, x = var_2054_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_107_cast_uint16")];
            tensor<string, []> gather_107_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_107_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_52_values0_0 = const()[name = tensor<string, []>("concat_52_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_52_values1_0 = const()[name = tensor<string, []>("concat_52_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_52_axis_0 = const()[name = tensor<string, []>("concat_52_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_52_interleave_0 = const()[name = tensor<string, []>("concat_52_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_107_cast_uint16_to_int32 = cast(dtype = gather_107_cast_uint16_to_int32_dtype_0, x = gather_107_cast_uint16)[name = tensor<string, []>("cast_212")];
            tensor<int32, [3]> concat_52 = concat(axis = concat_52_axis_0, interleave = concat_52_interleave_0, values = (concat_52_values0_0, concat_52_values1_0, gather_107_cast_uint16_to_int32))[name = tensor<string, []>("concat_52")];
            tensor<int32, [3]> var_2055_begin_0 = const()[name = tensor<string, []>("op_2055_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2055_end_mask_0 = const()[name = tensor<string, []>("op_2055_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2055_cast_fp16 = slice_by_index(begin = var_2055_begin_0, end = concat_52, end_mask = var_2055_end_mask_0, x = seg_103_cast_fp16)[name = tensor<string, []>("op_2055_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_589_cast_fp16 = add(x = var_2041_cast_fp16, y = var_2055_cast_fp16)[name = tensor<string, []>("input_589_cast_fp16")];
            tensor<string, []> input_591_pad_type_0 = const()[name = tensor<string, []>("input_591_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_591_strides_0 = const()[name = tensor<string, []>("input_591_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_591_pad_0 = const()[name = tensor<string, []>("input_591_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_591_dilations_0 = const()[name = tensor<string, []>("input_591_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_591_groups_0 = const()[name = tensor<string, []>("input_591_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd14_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd14_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4707968)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd14_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd14_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4724416)))];
            tensor<fp16, [1, 64, ?]> input_591_cast_fp16 = conv(bias = net_xvector_block2_tdnnd14_cam_layer_linear1_bias_to_fp16, dilations = input_591_dilations_0, groups = input_591_groups_0, pad = input_591_pad_0, pad_type = input_591_pad_type_0, strides = input_591_strides_0, weight = net_xvector_block2_tdnnd14_cam_layer_linear1_weight_to_fp16, x = input_589_cast_fp16)[name = tensor<string, []>("input_591_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_593_cast_fp16 = relu(x = input_591_cast_fp16)[name = tensor<string, []>("input_593_cast_fp16")];
            tensor<string, []> input_595_pad_type_0 = const()[name = tensor<string, []>("input_595_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_595_strides_0 = const()[name = tensor<string, []>("input_595_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_595_pad_0 = const()[name = tensor<string, []>("input_595_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_595_dilations_0 = const()[name = tensor<string, []>("input_595_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_595_groups_0 = const()[name = tensor<string, []>("input_595_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd14_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd14_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4724608)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd14_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd14_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4728768)))];
            tensor<fp16, [1, 32, ?]> input_595_cast_fp16 = conv(bias = net_xvector_block2_tdnnd14_cam_layer_linear2_bias_to_fp16, dilations = input_595_dilations_0, groups = input_595_groups_0, pad = input_595_pad_0, pad_type = input_595_pad_type_0, strides = input_595_strides_0, weight = net_xvector_block2_tdnnd14_cam_layer_linear2_weight_to_fp16, x = input_593_cast_fp16)[name = tensor<string, []>("input_595_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_51_cast_fp16 = sigmoid(x = input_595_cast_fp16)[name = tensor<string, []>("m_51_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2073_cast_fp16 = mul(x = y_51_cast_fp16, y = m_51_cast_fp16)[name = tensor<string, []>("op_2073_cast_fp16")];
            tensor<bool, []> input_597_interleave_0 = const()[name = tensor<string, []>("input_597_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 704, ?]> input_597_cast_fp16 = concat(axis = var_11, interleave = input_597_interleave_0, values = (input_577_cast_fp16, var_2073_cast_fp16))[name = tensor<string, []>("input_597_cast_fp16")];
            tensor<fp16, [704]> net_xvector_block2_tdnnd15_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd15_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [704]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4728896)))];
            tensor<fp16, [704]> net_xvector_block2_tdnnd15_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd15_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [704]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4730368)))];
            tensor<fp16, [704]> net_xvector_block2_tdnnd15_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd15_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [704]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4731840)))];
            tensor<fp16, [704]> net_xvector_block2_tdnnd15_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd15_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [704]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4733312)))];
            tensor<fp16, [1, 704, ?]> input_599_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd15_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd15_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd15_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd15_nonlinear1_batchnorm_running_var_to_fp16, x = input_597_cast_fp16)[name = tensor<string, []>("input_599_cast_fp16")];
            tensor<fp16, [1, 704, ?]> input_601_cast_fp16 = relu(x = input_599_cast_fp16)[name = tensor<string, []>("input_601_cast_fp16")];
            tensor<string, []> input_603_pad_type_0 = const()[name = tensor<string, []>("input_603_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_603_strides_0 = const()[name = tensor<string, []>("input_603_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_603_pad_0 = const()[name = tensor<string, []>("input_603_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_603_dilations_0 = const()[name = tensor<string, []>("input_603_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_603_groups_0 = const()[name = tensor<string, []>("input_603_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 704, 1]> const_78_to_fp16 = const()[name = tensor<string, []>("const_78_to_fp16"), val = tensor<fp16, [128, 704, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4734784)))];
            tensor<fp16, [128]> const_79_to_fp16 = const()[name = tensor<string, []>("const_79_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4915072)))];
            tensor<fp16, [1, 128, ?]> input_605_cast_fp16 = conv(bias = const_79_to_fp16, dilations = input_603_dilations_0, groups = input_603_groups_0, pad = input_603_pad_0, pad_type = input_603_pad_type_0, strides = input_603_strides_0, weight = const_78_to_fp16, x = input_601_cast_fp16)[name = tensor<string, []>("input_605_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_607_cast_fp16 = relu(x = input_605_cast_fp16)[name = tensor<string, []>("input_607_cast_fp16")];
            tensor<string, []> y_53_pad_type_0 = const()[name = tensor<string, []>("y_53_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_53_pad_0 = const()[name = tensor<string, []>("y_53_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_53_dilations_0 = const()[name = tensor<string, []>("y_53_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_53_strides_0 = const()[name = tensor<string, []>("y_53_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_53_groups_0 = const()[name = tensor<string, []>("y_53_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd15_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd15_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4915392)))];
            tensor<fp16, [1, 32, ?]> y_53_cast_fp16 = conv(dilations = y_53_dilations_0, groups = y_53_groups_0, pad = y_53_pad_0, pad_type = y_53_pad_type_0, strides = y_53_strides_0, weight = net_xvector_block2_tdnnd15_cam_layer_linear_local_weight_to_fp16, x = input_607_cast_fp16)[name = tensor<string, []>("y_53_cast_fp16")];
            tensor<int32, [1]> var_2110_axes_0 = const()[name = tensor<string, []>("op_2110_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2110_keep_dims_0 = const()[name = tensor<string, []>("op_2110_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2110_cast_fp16 = reduce_mean(axes = var_2110_axes_0, keep_dims = var_2110_keep_dims_0, x = input_607_cast_fp16)[name = tensor<string, []>("op_2110_cast_fp16")];
            tensor<int32, [1]> var_2111 = const()[name = tensor<string, []>("op_2111"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2112 = const()[name = tensor<string, []>("op_2112"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_105_pad_type_0 = const()[name = tensor<string, []>("seg_105_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_105_pad_0 = const()[name = tensor<string, []>("seg_105_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_105_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_105_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_105_ceil_mode_0 = const()[name = tensor<string, []>("seg_105_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_105_cast_fp16 = avg_pool(ceil_mode = seg_105_ceil_mode_0, exclude_padding_from_average = seg_105_exclude_padding_from_average_0, kernel_sizes = var_2111, pad = seg_105_pad_0, pad_type = seg_105_pad_type_0, strides = var_2112, x = input_607_cast_fp16)[name = tensor<string, []>("seg_105_cast_fp16")];
            tensor<int32, [3]> var_2115_shape_cast_fp16 = shape(x = seg_105_cast_fp16)[name = tensor<string, []>("op_2115_shape_cast_fp16")];
            tensor<int32, []> gather_108 = const()[name = tensor<string, []>("gather_108"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_109 = const()[name = tensor<string, []>("gather_109"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_110_axis_0 = const()[name = tensor<string, []>("gather_110_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_110_batch_dims_0 = const()[name = tensor<string, []>("gather_110_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_110_validate_indices_0 = const()[name = tensor<string, []>("gather_110_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2115_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2115_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_110_to_uint16 = const()[name = tensor<string, []>("select_110_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2115_shape_cast_fp16_to_uint16 = cast(dtype = var_2115_shape_cast_fp16_to_uint16_dtype_0, x = var_2115_shape_cast_fp16)[name = tensor<string, []>("cast_211")];
            tensor<uint16, []> gather_110_cast_uint16 = gather(axis = gather_110_axis_0, batch_dims = gather_110_batch_dims_0, indices = select_110_to_uint16, validate_indices = gather_110_validate_indices_0, x = var_2115_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_110_cast_uint16")];
            tensor<string, []> gather_110_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_110_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2118_axes_0 = const()[name = tensor<string, []>("op_2118_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2118_cast_fp16 = expand_dims(axes = var_2118_axes_0, x = seg_105_cast_fp16)[name = tensor<string, []>("op_2118_cast_fp16")];
            tensor<int32, []> concat_53_axis_0 = const()[name = tensor<string, []>("concat_53_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_53_interleave_0 = const()[name = tensor<string, []>("concat_53_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_110_cast_uint16_to_int32 = cast(dtype = gather_110_cast_uint16_to_int32_dtype_0, x = gather_110_cast_uint16)[name = tensor<string, []>("cast_210")];
            tensor<int32, [4]> concat_53 = concat(axis = concat_53_axis_0, interleave = concat_53_interleave_0, values = (gather_108, gather_109, gather_110_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_53")];
            tensor<int32, [4]> shape_137_cast_fp16 = shape(x = var_2118_cast_fp16)[name = tensor<string, []>("shape_137_cast_fp16")];
            tensor<int32, [4]> real_div_26 = real_div(x = concat_53, y = shape_137_cast_fp16)[name = tensor<string, []>("real_div_26")];
            tensor<fp16, [?, ?, ?, ?]> var_2120_cast_fp16 = tile(reps = real_div_26, x = var_2118_cast_fp16)[name = tensor<string, []>("op_2120_cast_fp16")];
            tensor<int32, [3]> var_2121 = const()[name = tensor<string, []>("op_2121"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_107_cast_fp16 = reshape(shape = var_2121, x = var_2120_cast_fp16)[name = tensor<string, []>("seg_107_cast_fp16")];
            tensor<int32, [3]> var_2123_shape_cast_fp16 = shape(x = input_607_cast_fp16)[name = tensor<string, []>("op_2123_shape_cast_fp16")];
            tensor<int32, []> gather_111_axis_0 = const()[name = tensor<string, []>("gather_111_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_111_batch_dims_0 = const()[name = tensor<string, []>("gather_111_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_111_validate_indices_0 = const()[name = tensor<string, []>("gather_111_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2123_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2123_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_111_to_uint16 = const()[name = tensor<string, []>("select_111_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2123_shape_cast_fp16_to_uint16 = cast(dtype = var_2123_shape_cast_fp16_to_uint16_dtype_0, x = var_2123_shape_cast_fp16)[name = tensor<string, []>("cast_209")];
            tensor<uint16, []> gather_111_cast_uint16 = gather(axis = gather_111_axis_0, batch_dims = gather_111_batch_dims_0, indices = select_111_to_uint16, validate_indices = gather_111_validate_indices_0, x = var_2123_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_111_cast_uint16")];
            tensor<string, []> gather_111_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_111_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_54_values0_0 = const()[name = tensor<string, []>("concat_54_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_54_values1_0 = const()[name = tensor<string, []>("concat_54_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_54_axis_0 = const()[name = tensor<string, []>("concat_54_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_54_interleave_0 = const()[name = tensor<string, []>("concat_54_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_111_cast_uint16_to_int32 = cast(dtype = gather_111_cast_uint16_to_int32_dtype_0, x = gather_111_cast_uint16)[name = tensor<string, []>("cast_208")];
            tensor<int32, [3]> concat_54 = concat(axis = concat_54_axis_0, interleave = concat_54_interleave_0, values = (concat_54_values0_0, concat_54_values1_0, gather_111_cast_uint16_to_int32))[name = tensor<string, []>("concat_54")];
            tensor<int32, [3]> var_2124_begin_0 = const()[name = tensor<string, []>("op_2124_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2124_end_mask_0 = const()[name = tensor<string, []>("op_2124_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2124_cast_fp16 = slice_by_index(begin = var_2124_begin_0, end = concat_54, end_mask = var_2124_end_mask_0, x = seg_107_cast_fp16)[name = tensor<string, []>("op_2124_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_609_cast_fp16 = add(x = var_2110_cast_fp16, y = var_2124_cast_fp16)[name = tensor<string, []>("input_609_cast_fp16")];
            tensor<string, []> input_611_pad_type_0 = const()[name = tensor<string, []>("input_611_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_611_strides_0 = const()[name = tensor<string, []>("input_611_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_611_pad_0 = const()[name = tensor<string, []>("input_611_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_611_dilations_0 = const()[name = tensor<string, []>("input_611_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_611_groups_0 = const()[name = tensor<string, []>("input_611_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd15_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd15_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4940032)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd15_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd15_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4956480)))];
            tensor<fp16, [1, 64, ?]> input_611_cast_fp16 = conv(bias = net_xvector_block2_tdnnd15_cam_layer_linear1_bias_to_fp16, dilations = input_611_dilations_0, groups = input_611_groups_0, pad = input_611_pad_0, pad_type = input_611_pad_type_0, strides = input_611_strides_0, weight = net_xvector_block2_tdnnd15_cam_layer_linear1_weight_to_fp16, x = input_609_cast_fp16)[name = tensor<string, []>("input_611_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_613_cast_fp16 = relu(x = input_611_cast_fp16)[name = tensor<string, []>("input_613_cast_fp16")];
            tensor<string, []> input_615_pad_type_0 = const()[name = tensor<string, []>("input_615_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_615_strides_0 = const()[name = tensor<string, []>("input_615_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_615_pad_0 = const()[name = tensor<string, []>("input_615_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_615_dilations_0 = const()[name = tensor<string, []>("input_615_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_615_groups_0 = const()[name = tensor<string, []>("input_615_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd15_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd15_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4956672)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd15_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd15_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4960832)))];
            tensor<fp16, [1, 32, ?]> input_615_cast_fp16 = conv(bias = net_xvector_block2_tdnnd15_cam_layer_linear2_bias_to_fp16, dilations = input_615_dilations_0, groups = input_615_groups_0, pad = input_615_pad_0, pad_type = input_615_pad_type_0, strides = input_615_strides_0, weight = net_xvector_block2_tdnnd15_cam_layer_linear2_weight_to_fp16, x = input_613_cast_fp16)[name = tensor<string, []>("input_615_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_53_cast_fp16 = sigmoid(x = input_615_cast_fp16)[name = tensor<string, []>("m_53_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2142_cast_fp16 = mul(x = y_53_cast_fp16, y = m_53_cast_fp16)[name = tensor<string, []>("op_2142_cast_fp16")];
            tensor<bool, []> input_617_interleave_0 = const()[name = tensor<string, []>("input_617_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 736, ?]> input_617_cast_fp16 = concat(axis = var_11, interleave = input_617_interleave_0, values = (input_597_cast_fp16, var_2142_cast_fp16))[name = tensor<string, []>("input_617_cast_fp16")];
            tensor<fp16, [736]> net_xvector_block2_tdnnd16_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd16_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [736]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4960960)))];
            tensor<fp16, [736]> net_xvector_block2_tdnnd16_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd16_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [736]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4962496)))];
            tensor<fp16, [736]> net_xvector_block2_tdnnd16_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd16_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [736]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4964032)))];
            tensor<fp16, [736]> net_xvector_block2_tdnnd16_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd16_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [736]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4965568)))];
            tensor<fp16, [1, 736, ?]> input_619_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd16_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd16_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd16_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd16_nonlinear1_batchnorm_running_var_to_fp16, x = input_617_cast_fp16)[name = tensor<string, []>("input_619_cast_fp16")];
            tensor<fp16, [1, 736, ?]> input_621_cast_fp16 = relu(x = input_619_cast_fp16)[name = tensor<string, []>("input_621_cast_fp16")];
            tensor<string, []> input_623_pad_type_0 = const()[name = tensor<string, []>("input_623_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_623_strides_0 = const()[name = tensor<string, []>("input_623_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_623_pad_0 = const()[name = tensor<string, []>("input_623_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_623_dilations_0 = const()[name = tensor<string, []>("input_623_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_623_groups_0 = const()[name = tensor<string, []>("input_623_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 736, 1]> const_80_to_fp16 = const()[name = tensor<string, []>("const_80_to_fp16"), val = tensor<fp16, [128, 736, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4967104)))];
            tensor<fp16, [128]> const_81_to_fp16 = const()[name = tensor<string, []>("const_81_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5155584)))];
            tensor<fp16, [1, 128, ?]> input_625_cast_fp16 = conv(bias = const_81_to_fp16, dilations = input_623_dilations_0, groups = input_623_groups_0, pad = input_623_pad_0, pad_type = input_623_pad_type_0, strides = input_623_strides_0, weight = const_80_to_fp16, x = input_621_cast_fp16)[name = tensor<string, []>("input_625_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_627_cast_fp16 = relu(x = input_625_cast_fp16)[name = tensor<string, []>("input_627_cast_fp16")];
            tensor<string, []> y_55_pad_type_0 = const()[name = tensor<string, []>("y_55_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_55_pad_0 = const()[name = tensor<string, []>("y_55_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_55_dilations_0 = const()[name = tensor<string, []>("y_55_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_55_strides_0 = const()[name = tensor<string, []>("y_55_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_55_groups_0 = const()[name = tensor<string, []>("y_55_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd16_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd16_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5155904)))];
            tensor<fp16, [1, 32, ?]> y_55_cast_fp16 = conv(dilations = y_55_dilations_0, groups = y_55_groups_0, pad = y_55_pad_0, pad_type = y_55_pad_type_0, strides = y_55_strides_0, weight = net_xvector_block2_tdnnd16_cam_layer_linear_local_weight_to_fp16, x = input_627_cast_fp16)[name = tensor<string, []>("y_55_cast_fp16")];
            tensor<int32, [1]> var_2179_axes_0 = const()[name = tensor<string, []>("op_2179_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2179_keep_dims_0 = const()[name = tensor<string, []>("op_2179_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2179_cast_fp16 = reduce_mean(axes = var_2179_axes_0, keep_dims = var_2179_keep_dims_0, x = input_627_cast_fp16)[name = tensor<string, []>("op_2179_cast_fp16")];
            tensor<int32, [1]> var_2180 = const()[name = tensor<string, []>("op_2180"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2181 = const()[name = tensor<string, []>("op_2181"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_109_pad_type_0 = const()[name = tensor<string, []>("seg_109_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_109_pad_0 = const()[name = tensor<string, []>("seg_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_109_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_109_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_109_ceil_mode_0 = const()[name = tensor<string, []>("seg_109_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_109_cast_fp16 = avg_pool(ceil_mode = seg_109_ceil_mode_0, exclude_padding_from_average = seg_109_exclude_padding_from_average_0, kernel_sizes = var_2180, pad = seg_109_pad_0, pad_type = seg_109_pad_type_0, strides = var_2181, x = input_627_cast_fp16)[name = tensor<string, []>("seg_109_cast_fp16")];
            tensor<int32, [3]> var_2184_shape_cast_fp16 = shape(x = seg_109_cast_fp16)[name = tensor<string, []>("op_2184_shape_cast_fp16")];
            tensor<int32, []> gather_112 = const()[name = tensor<string, []>("gather_112"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_113 = const()[name = tensor<string, []>("gather_113"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_114_axis_0 = const()[name = tensor<string, []>("gather_114_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_114_batch_dims_0 = const()[name = tensor<string, []>("gather_114_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_114_validate_indices_0 = const()[name = tensor<string, []>("gather_114_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2184_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2184_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_114_to_uint16 = const()[name = tensor<string, []>("select_114_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2184_shape_cast_fp16_to_uint16 = cast(dtype = var_2184_shape_cast_fp16_to_uint16_dtype_0, x = var_2184_shape_cast_fp16)[name = tensor<string, []>("cast_207")];
            tensor<uint16, []> gather_114_cast_uint16 = gather(axis = gather_114_axis_0, batch_dims = gather_114_batch_dims_0, indices = select_114_to_uint16, validate_indices = gather_114_validate_indices_0, x = var_2184_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_114_cast_uint16")];
            tensor<string, []> gather_114_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_114_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2187_axes_0 = const()[name = tensor<string, []>("op_2187_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2187_cast_fp16 = expand_dims(axes = var_2187_axes_0, x = seg_109_cast_fp16)[name = tensor<string, []>("op_2187_cast_fp16")];
            tensor<int32, []> concat_55_axis_0 = const()[name = tensor<string, []>("concat_55_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_55_interleave_0 = const()[name = tensor<string, []>("concat_55_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_114_cast_uint16_to_int32 = cast(dtype = gather_114_cast_uint16_to_int32_dtype_0, x = gather_114_cast_uint16)[name = tensor<string, []>("cast_206")];
            tensor<int32, [4]> concat_55 = concat(axis = concat_55_axis_0, interleave = concat_55_interleave_0, values = (gather_112, gather_113, gather_114_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_55")];
            tensor<int32, [4]> shape_142_cast_fp16 = shape(x = var_2187_cast_fp16)[name = tensor<string, []>("shape_142_cast_fp16")];
            tensor<int32, [4]> real_div_27 = real_div(x = concat_55, y = shape_142_cast_fp16)[name = tensor<string, []>("real_div_27")];
            tensor<fp16, [?, ?, ?, ?]> var_2189_cast_fp16 = tile(reps = real_div_27, x = var_2187_cast_fp16)[name = tensor<string, []>("op_2189_cast_fp16")];
            tensor<int32, [3]> var_2190 = const()[name = tensor<string, []>("op_2190"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_111_cast_fp16 = reshape(shape = var_2190, x = var_2189_cast_fp16)[name = tensor<string, []>("seg_111_cast_fp16")];
            tensor<int32, [3]> var_2192_shape_cast_fp16 = shape(x = input_627_cast_fp16)[name = tensor<string, []>("op_2192_shape_cast_fp16")];
            tensor<int32, []> gather_115_axis_0 = const()[name = tensor<string, []>("gather_115_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_115_batch_dims_0 = const()[name = tensor<string, []>("gather_115_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_115_validate_indices_0 = const()[name = tensor<string, []>("gather_115_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2192_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2192_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_115_to_uint16 = const()[name = tensor<string, []>("select_115_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2192_shape_cast_fp16_to_uint16 = cast(dtype = var_2192_shape_cast_fp16_to_uint16_dtype_0, x = var_2192_shape_cast_fp16)[name = tensor<string, []>("cast_205")];
            tensor<uint16, []> gather_115_cast_uint16 = gather(axis = gather_115_axis_0, batch_dims = gather_115_batch_dims_0, indices = select_115_to_uint16, validate_indices = gather_115_validate_indices_0, x = var_2192_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_115_cast_uint16")];
            tensor<string, []> gather_115_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_115_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_56_values0_0 = const()[name = tensor<string, []>("concat_56_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_56_values1_0 = const()[name = tensor<string, []>("concat_56_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_56_axis_0 = const()[name = tensor<string, []>("concat_56_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_56_interleave_0 = const()[name = tensor<string, []>("concat_56_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_115_cast_uint16_to_int32 = cast(dtype = gather_115_cast_uint16_to_int32_dtype_0, x = gather_115_cast_uint16)[name = tensor<string, []>("cast_204")];
            tensor<int32, [3]> concat_56 = concat(axis = concat_56_axis_0, interleave = concat_56_interleave_0, values = (concat_56_values0_0, concat_56_values1_0, gather_115_cast_uint16_to_int32))[name = tensor<string, []>("concat_56")];
            tensor<int32, [3]> var_2193_begin_0 = const()[name = tensor<string, []>("op_2193_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2193_end_mask_0 = const()[name = tensor<string, []>("op_2193_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2193_cast_fp16 = slice_by_index(begin = var_2193_begin_0, end = concat_56, end_mask = var_2193_end_mask_0, x = seg_111_cast_fp16)[name = tensor<string, []>("op_2193_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_629_cast_fp16 = add(x = var_2179_cast_fp16, y = var_2193_cast_fp16)[name = tensor<string, []>("input_629_cast_fp16")];
            tensor<string, []> input_631_pad_type_0 = const()[name = tensor<string, []>("input_631_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_631_strides_0 = const()[name = tensor<string, []>("input_631_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_631_pad_0 = const()[name = tensor<string, []>("input_631_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_631_dilations_0 = const()[name = tensor<string, []>("input_631_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_631_groups_0 = const()[name = tensor<string, []>("input_631_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd16_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd16_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5180544)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd16_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd16_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5196992)))];
            tensor<fp16, [1, 64, ?]> input_631_cast_fp16 = conv(bias = net_xvector_block2_tdnnd16_cam_layer_linear1_bias_to_fp16, dilations = input_631_dilations_0, groups = input_631_groups_0, pad = input_631_pad_0, pad_type = input_631_pad_type_0, strides = input_631_strides_0, weight = net_xvector_block2_tdnnd16_cam_layer_linear1_weight_to_fp16, x = input_629_cast_fp16)[name = tensor<string, []>("input_631_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_633_cast_fp16 = relu(x = input_631_cast_fp16)[name = tensor<string, []>("input_633_cast_fp16")];
            tensor<string, []> input_635_pad_type_0 = const()[name = tensor<string, []>("input_635_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_635_strides_0 = const()[name = tensor<string, []>("input_635_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_635_pad_0 = const()[name = tensor<string, []>("input_635_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_635_dilations_0 = const()[name = tensor<string, []>("input_635_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_635_groups_0 = const()[name = tensor<string, []>("input_635_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd16_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd16_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5197184)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd16_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd16_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5201344)))];
            tensor<fp16, [1, 32, ?]> input_635_cast_fp16 = conv(bias = net_xvector_block2_tdnnd16_cam_layer_linear2_bias_to_fp16, dilations = input_635_dilations_0, groups = input_635_groups_0, pad = input_635_pad_0, pad_type = input_635_pad_type_0, strides = input_635_strides_0, weight = net_xvector_block2_tdnnd16_cam_layer_linear2_weight_to_fp16, x = input_633_cast_fp16)[name = tensor<string, []>("input_635_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_55_cast_fp16 = sigmoid(x = input_635_cast_fp16)[name = tensor<string, []>("m_55_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2211_cast_fp16 = mul(x = y_55_cast_fp16, y = m_55_cast_fp16)[name = tensor<string, []>("op_2211_cast_fp16")];
            tensor<bool, []> input_637_interleave_0 = const()[name = tensor<string, []>("input_637_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 768, ?]> input_637_cast_fp16 = concat(axis = var_11, interleave = input_637_interleave_0, values = (input_617_cast_fp16, var_2211_cast_fp16))[name = tensor<string, []>("input_637_cast_fp16")];
            tensor<fp16, [768]> net_xvector_block2_tdnnd17_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd17_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5201472)))];
            tensor<fp16, [768]> net_xvector_block2_tdnnd17_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd17_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5203072)))];
            tensor<fp16, [768]> net_xvector_block2_tdnnd17_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd17_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5204672)))];
            tensor<fp16, [768]> net_xvector_block2_tdnnd17_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd17_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5206272)))];
            tensor<fp16, [1, 768, ?]> input_639_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd17_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd17_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd17_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd17_nonlinear1_batchnorm_running_var_to_fp16, x = input_637_cast_fp16)[name = tensor<string, []>("input_639_cast_fp16")];
            tensor<fp16, [1, 768, ?]> input_641_cast_fp16 = relu(x = input_639_cast_fp16)[name = tensor<string, []>("input_641_cast_fp16")];
            tensor<string, []> input_643_pad_type_0 = const()[name = tensor<string, []>("input_643_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_643_strides_0 = const()[name = tensor<string, []>("input_643_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_643_pad_0 = const()[name = tensor<string, []>("input_643_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_643_dilations_0 = const()[name = tensor<string, []>("input_643_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_643_groups_0 = const()[name = tensor<string, []>("input_643_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 768, 1]> const_82_to_fp16 = const()[name = tensor<string, []>("const_82_to_fp16"), val = tensor<fp16, [128, 768, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5207872)))];
            tensor<fp16, [128]> const_83_to_fp16 = const()[name = tensor<string, []>("const_83_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5404544)))];
            tensor<fp16, [1, 128, ?]> input_645_cast_fp16 = conv(bias = const_83_to_fp16, dilations = input_643_dilations_0, groups = input_643_groups_0, pad = input_643_pad_0, pad_type = input_643_pad_type_0, strides = input_643_strides_0, weight = const_82_to_fp16, x = input_641_cast_fp16)[name = tensor<string, []>("input_645_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_647_cast_fp16 = relu(x = input_645_cast_fp16)[name = tensor<string, []>("input_647_cast_fp16")];
            tensor<string, []> y_57_pad_type_0 = const()[name = tensor<string, []>("y_57_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_57_pad_0 = const()[name = tensor<string, []>("y_57_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_57_dilations_0 = const()[name = tensor<string, []>("y_57_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_57_strides_0 = const()[name = tensor<string, []>("y_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_57_groups_0 = const()[name = tensor<string, []>("y_57_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd17_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd17_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5404864)))];
            tensor<fp16, [1, 32, ?]> y_57_cast_fp16 = conv(dilations = y_57_dilations_0, groups = y_57_groups_0, pad = y_57_pad_0, pad_type = y_57_pad_type_0, strides = y_57_strides_0, weight = net_xvector_block2_tdnnd17_cam_layer_linear_local_weight_to_fp16, x = input_647_cast_fp16)[name = tensor<string, []>("y_57_cast_fp16")];
            tensor<int32, [1]> var_2248_axes_0 = const()[name = tensor<string, []>("op_2248_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2248_keep_dims_0 = const()[name = tensor<string, []>("op_2248_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2248_cast_fp16 = reduce_mean(axes = var_2248_axes_0, keep_dims = var_2248_keep_dims_0, x = input_647_cast_fp16)[name = tensor<string, []>("op_2248_cast_fp16")];
            tensor<int32, [1]> var_2249 = const()[name = tensor<string, []>("op_2249"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2250 = const()[name = tensor<string, []>("op_2250"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_113_pad_type_0 = const()[name = tensor<string, []>("seg_113_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_113_pad_0 = const()[name = tensor<string, []>("seg_113_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_113_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_113_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_113_ceil_mode_0 = const()[name = tensor<string, []>("seg_113_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_113_cast_fp16 = avg_pool(ceil_mode = seg_113_ceil_mode_0, exclude_padding_from_average = seg_113_exclude_padding_from_average_0, kernel_sizes = var_2249, pad = seg_113_pad_0, pad_type = seg_113_pad_type_0, strides = var_2250, x = input_647_cast_fp16)[name = tensor<string, []>("seg_113_cast_fp16")];
            tensor<int32, [3]> var_2253_shape_cast_fp16 = shape(x = seg_113_cast_fp16)[name = tensor<string, []>("op_2253_shape_cast_fp16")];
            tensor<int32, []> gather_116 = const()[name = tensor<string, []>("gather_116"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_117 = const()[name = tensor<string, []>("gather_117"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_118_axis_0 = const()[name = tensor<string, []>("gather_118_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_118_batch_dims_0 = const()[name = tensor<string, []>("gather_118_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_118_validate_indices_0 = const()[name = tensor<string, []>("gather_118_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2253_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2253_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_118_to_uint16 = const()[name = tensor<string, []>("select_118_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2253_shape_cast_fp16_to_uint16 = cast(dtype = var_2253_shape_cast_fp16_to_uint16_dtype_0, x = var_2253_shape_cast_fp16)[name = tensor<string, []>("cast_203")];
            tensor<uint16, []> gather_118_cast_uint16 = gather(axis = gather_118_axis_0, batch_dims = gather_118_batch_dims_0, indices = select_118_to_uint16, validate_indices = gather_118_validate_indices_0, x = var_2253_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_118_cast_uint16")];
            tensor<string, []> gather_118_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_118_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2256_axes_0 = const()[name = tensor<string, []>("op_2256_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2256_cast_fp16 = expand_dims(axes = var_2256_axes_0, x = seg_113_cast_fp16)[name = tensor<string, []>("op_2256_cast_fp16")];
            tensor<int32, []> concat_57_axis_0 = const()[name = tensor<string, []>("concat_57_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_57_interleave_0 = const()[name = tensor<string, []>("concat_57_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_118_cast_uint16_to_int32 = cast(dtype = gather_118_cast_uint16_to_int32_dtype_0, x = gather_118_cast_uint16)[name = tensor<string, []>("cast_202")];
            tensor<int32, [4]> concat_57 = concat(axis = concat_57_axis_0, interleave = concat_57_interleave_0, values = (gather_116, gather_117, gather_118_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_57")];
            tensor<int32, [4]> shape_147_cast_fp16 = shape(x = var_2256_cast_fp16)[name = tensor<string, []>("shape_147_cast_fp16")];
            tensor<int32, [4]> real_div_28 = real_div(x = concat_57, y = shape_147_cast_fp16)[name = tensor<string, []>("real_div_28")];
            tensor<fp16, [?, ?, ?, ?]> var_2258_cast_fp16 = tile(reps = real_div_28, x = var_2256_cast_fp16)[name = tensor<string, []>("op_2258_cast_fp16")];
            tensor<int32, [3]> var_2259 = const()[name = tensor<string, []>("op_2259"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_115_cast_fp16 = reshape(shape = var_2259, x = var_2258_cast_fp16)[name = tensor<string, []>("seg_115_cast_fp16")];
            tensor<int32, [3]> var_2261_shape_cast_fp16 = shape(x = input_647_cast_fp16)[name = tensor<string, []>("op_2261_shape_cast_fp16")];
            tensor<int32, []> gather_119_axis_0 = const()[name = tensor<string, []>("gather_119_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_119_batch_dims_0 = const()[name = tensor<string, []>("gather_119_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_119_validate_indices_0 = const()[name = tensor<string, []>("gather_119_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2261_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2261_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_119_to_uint16 = const()[name = tensor<string, []>("select_119_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2261_shape_cast_fp16_to_uint16 = cast(dtype = var_2261_shape_cast_fp16_to_uint16_dtype_0, x = var_2261_shape_cast_fp16)[name = tensor<string, []>("cast_201")];
            tensor<uint16, []> gather_119_cast_uint16 = gather(axis = gather_119_axis_0, batch_dims = gather_119_batch_dims_0, indices = select_119_to_uint16, validate_indices = gather_119_validate_indices_0, x = var_2261_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_119_cast_uint16")];
            tensor<string, []> gather_119_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_119_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_58_values0_0 = const()[name = tensor<string, []>("concat_58_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_58_values1_0 = const()[name = tensor<string, []>("concat_58_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_58_axis_0 = const()[name = tensor<string, []>("concat_58_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_58_interleave_0 = const()[name = tensor<string, []>("concat_58_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_119_cast_uint16_to_int32 = cast(dtype = gather_119_cast_uint16_to_int32_dtype_0, x = gather_119_cast_uint16)[name = tensor<string, []>("cast_200")];
            tensor<int32, [3]> concat_58 = concat(axis = concat_58_axis_0, interleave = concat_58_interleave_0, values = (concat_58_values0_0, concat_58_values1_0, gather_119_cast_uint16_to_int32))[name = tensor<string, []>("concat_58")];
            tensor<int32, [3]> var_2262_begin_0 = const()[name = tensor<string, []>("op_2262_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2262_end_mask_0 = const()[name = tensor<string, []>("op_2262_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2262_cast_fp16 = slice_by_index(begin = var_2262_begin_0, end = concat_58, end_mask = var_2262_end_mask_0, x = seg_115_cast_fp16)[name = tensor<string, []>("op_2262_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_649_cast_fp16 = add(x = var_2248_cast_fp16, y = var_2262_cast_fp16)[name = tensor<string, []>("input_649_cast_fp16")];
            tensor<string, []> input_651_pad_type_0 = const()[name = tensor<string, []>("input_651_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_651_strides_0 = const()[name = tensor<string, []>("input_651_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_651_pad_0 = const()[name = tensor<string, []>("input_651_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_651_dilations_0 = const()[name = tensor<string, []>("input_651_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_651_groups_0 = const()[name = tensor<string, []>("input_651_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd17_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd17_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5429504)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd17_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd17_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5445952)))];
            tensor<fp16, [1, 64, ?]> input_651_cast_fp16 = conv(bias = net_xvector_block2_tdnnd17_cam_layer_linear1_bias_to_fp16, dilations = input_651_dilations_0, groups = input_651_groups_0, pad = input_651_pad_0, pad_type = input_651_pad_type_0, strides = input_651_strides_0, weight = net_xvector_block2_tdnnd17_cam_layer_linear1_weight_to_fp16, x = input_649_cast_fp16)[name = tensor<string, []>("input_651_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_653_cast_fp16 = relu(x = input_651_cast_fp16)[name = tensor<string, []>("input_653_cast_fp16")];
            tensor<string, []> input_655_pad_type_0 = const()[name = tensor<string, []>("input_655_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_655_strides_0 = const()[name = tensor<string, []>("input_655_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_655_pad_0 = const()[name = tensor<string, []>("input_655_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_655_dilations_0 = const()[name = tensor<string, []>("input_655_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_655_groups_0 = const()[name = tensor<string, []>("input_655_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd17_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd17_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5446144)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd17_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd17_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5450304)))];
            tensor<fp16, [1, 32, ?]> input_655_cast_fp16 = conv(bias = net_xvector_block2_tdnnd17_cam_layer_linear2_bias_to_fp16, dilations = input_655_dilations_0, groups = input_655_groups_0, pad = input_655_pad_0, pad_type = input_655_pad_type_0, strides = input_655_strides_0, weight = net_xvector_block2_tdnnd17_cam_layer_linear2_weight_to_fp16, x = input_653_cast_fp16)[name = tensor<string, []>("input_655_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_57_cast_fp16 = sigmoid(x = input_655_cast_fp16)[name = tensor<string, []>("m_57_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2280_cast_fp16 = mul(x = y_57_cast_fp16, y = m_57_cast_fp16)[name = tensor<string, []>("op_2280_cast_fp16")];
            tensor<bool, []> input_657_interleave_0 = const()[name = tensor<string, []>("input_657_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 800, ?]> input_657_cast_fp16 = concat(axis = var_11, interleave = input_657_interleave_0, values = (input_637_cast_fp16, var_2280_cast_fp16))[name = tensor<string, []>("input_657_cast_fp16")];
            tensor<fp16, [800]> net_xvector_block2_tdnnd18_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd18_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5450432)))];
            tensor<fp16, [800]> net_xvector_block2_tdnnd18_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd18_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5452096)))];
            tensor<fp16, [800]> net_xvector_block2_tdnnd18_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd18_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5453760)))];
            tensor<fp16, [800]> net_xvector_block2_tdnnd18_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd18_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5455424)))];
            tensor<fp16, [1, 800, ?]> input_659_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd18_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd18_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd18_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd18_nonlinear1_batchnorm_running_var_to_fp16, x = input_657_cast_fp16)[name = tensor<string, []>("input_659_cast_fp16")];
            tensor<fp16, [1, 800, ?]> input_661_cast_fp16 = relu(x = input_659_cast_fp16)[name = tensor<string, []>("input_661_cast_fp16")];
            tensor<string, []> input_663_pad_type_0 = const()[name = tensor<string, []>("input_663_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_663_strides_0 = const()[name = tensor<string, []>("input_663_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_663_pad_0 = const()[name = tensor<string, []>("input_663_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_663_dilations_0 = const()[name = tensor<string, []>("input_663_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_663_groups_0 = const()[name = tensor<string, []>("input_663_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 800, 1]> const_84_to_fp16 = const()[name = tensor<string, []>("const_84_to_fp16"), val = tensor<fp16, [128, 800, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5457088)))];
            tensor<fp16, [128]> const_85_to_fp16 = const()[name = tensor<string, []>("const_85_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5661952)))];
            tensor<fp16, [1, 128, ?]> input_665_cast_fp16 = conv(bias = const_85_to_fp16, dilations = input_663_dilations_0, groups = input_663_groups_0, pad = input_663_pad_0, pad_type = input_663_pad_type_0, strides = input_663_strides_0, weight = const_84_to_fp16, x = input_661_cast_fp16)[name = tensor<string, []>("input_665_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_667_cast_fp16 = relu(x = input_665_cast_fp16)[name = tensor<string, []>("input_667_cast_fp16")];
            tensor<string, []> y_59_pad_type_0 = const()[name = tensor<string, []>("y_59_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_59_pad_0 = const()[name = tensor<string, []>("y_59_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_59_dilations_0 = const()[name = tensor<string, []>("y_59_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_59_strides_0 = const()[name = tensor<string, []>("y_59_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_59_groups_0 = const()[name = tensor<string, []>("y_59_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd18_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd18_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5662272)))];
            tensor<fp16, [1, 32, ?]> y_59_cast_fp16 = conv(dilations = y_59_dilations_0, groups = y_59_groups_0, pad = y_59_pad_0, pad_type = y_59_pad_type_0, strides = y_59_strides_0, weight = net_xvector_block2_tdnnd18_cam_layer_linear_local_weight_to_fp16, x = input_667_cast_fp16)[name = tensor<string, []>("y_59_cast_fp16")];
            tensor<int32, [1]> var_2317_axes_0 = const()[name = tensor<string, []>("op_2317_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2317_keep_dims_0 = const()[name = tensor<string, []>("op_2317_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2317_cast_fp16 = reduce_mean(axes = var_2317_axes_0, keep_dims = var_2317_keep_dims_0, x = input_667_cast_fp16)[name = tensor<string, []>("op_2317_cast_fp16")];
            tensor<int32, [1]> var_2318 = const()[name = tensor<string, []>("op_2318"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2319 = const()[name = tensor<string, []>("op_2319"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_117_pad_type_0 = const()[name = tensor<string, []>("seg_117_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_117_pad_0 = const()[name = tensor<string, []>("seg_117_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_117_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_117_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_117_ceil_mode_0 = const()[name = tensor<string, []>("seg_117_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_117_cast_fp16 = avg_pool(ceil_mode = seg_117_ceil_mode_0, exclude_padding_from_average = seg_117_exclude_padding_from_average_0, kernel_sizes = var_2318, pad = seg_117_pad_0, pad_type = seg_117_pad_type_0, strides = var_2319, x = input_667_cast_fp16)[name = tensor<string, []>("seg_117_cast_fp16")];
            tensor<int32, [3]> var_2322_shape_cast_fp16 = shape(x = seg_117_cast_fp16)[name = tensor<string, []>("op_2322_shape_cast_fp16")];
            tensor<int32, []> gather_120 = const()[name = tensor<string, []>("gather_120"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_121 = const()[name = tensor<string, []>("gather_121"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_122_axis_0 = const()[name = tensor<string, []>("gather_122_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_122_batch_dims_0 = const()[name = tensor<string, []>("gather_122_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_122_validate_indices_0 = const()[name = tensor<string, []>("gather_122_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2322_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2322_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_122_to_uint16 = const()[name = tensor<string, []>("select_122_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2322_shape_cast_fp16_to_uint16 = cast(dtype = var_2322_shape_cast_fp16_to_uint16_dtype_0, x = var_2322_shape_cast_fp16)[name = tensor<string, []>("cast_199")];
            tensor<uint16, []> gather_122_cast_uint16 = gather(axis = gather_122_axis_0, batch_dims = gather_122_batch_dims_0, indices = select_122_to_uint16, validate_indices = gather_122_validate_indices_0, x = var_2322_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_122_cast_uint16")];
            tensor<string, []> gather_122_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_122_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2325_axes_0 = const()[name = tensor<string, []>("op_2325_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2325_cast_fp16 = expand_dims(axes = var_2325_axes_0, x = seg_117_cast_fp16)[name = tensor<string, []>("op_2325_cast_fp16")];
            tensor<int32, []> concat_59_axis_0 = const()[name = tensor<string, []>("concat_59_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_59_interleave_0 = const()[name = tensor<string, []>("concat_59_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_122_cast_uint16_to_int32 = cast(dtype = gather_122_cast_uint16_to_int32_dtype_0, x = gather_122_cast_uint16)[name = tensor<string, []>("cast_198")];
            tensor<int32, [4]> concat_59 = concat(axis = concat_59_axis_0, interleave = concat_59_interleave_0, values = (gather_120, gather_121, gather_122_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_59")];
            tensor<int32, [4]> shape_152_cast_fp16 = shape(x = var_2325_cast_fp16)[name = tensor<string, []>("shape_152_cast_fp16")];
            tensor<int32, [4]> real_div_29 = real_div(x = concat_59, y = shape_152_cast_fp16)[name = tensor<string, []>("real_div_29")];
            tensor<fp16, [?, ?, ?, ?]> var_2327_cast_fp16 = tile(reps = real_div_29, x = var_2325_cast_fp16)[name = tensor<string, []>("op_2327_cast_fp16")];
            tensor<int32, [3]> var_2328 = const()[name = tensor<string, []>("op_2328"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_119_cast_fp16 = reshape(shape = var_2328, x = var_2327_cast_fp16)[name = tensor<string, []>("seg_119_cast_fp16")];
            tensor<int32, [3]> var_2330_shape_cast_fp16 = shape(x = input_667_cast_fp16)[name = tensor<string, []>("op_2330_shape_cast_fp16")];
            tensor<int32, []> gather_123_axis_0 = const()[name = tensor<string, []>("gather_123_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_123_batch_dims_0 = const()[name = tensor<string, []>("gather_123_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_123_validate_indices_0 = const()[name = tensor<string, []>("gather_123_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2330_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2330_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_123_to_uint16 = const()[name = tensor<string, []>("select_123_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2330_shape_cast_fp16_to_uint16 = cast(dtype = var_2330_shape_cast_fp16_to_uint16_dtype_0, x = var_2330_shape_cast_fp16)[name = tensor<string, []>("cast_197")];
            tensor<uint16, []> gather_123_cast_uint16 = gather(axis = gather_123_axis_0, batch_dims = gather_123_batch_dims_0, indices = select_123_to_uint16, validate_indices = gather_123_validate_indices_0, x = var_2330_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_123_cast_uint16")];
            tensor<string, []> gather_123_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_123_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_60_values0_0 = const()[name = tensor<string, []>("concat_60_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_60_values1_0 = const()[name = tensor<string, []>("concat_60_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_60_axis_0 = const()[name = tensor<string, []>("concat_60_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_60_interleave_0 = const()[name = tensor<string, []>("concat_60_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_123_cast_uint16_to_int32 = cast(dtype = gather_123_cast_uint16_to_int32_dtype_0, x = gather_123_cast_uint16)[name = tensor<string, []>("cast_196")];
            tensor<int32, [3]> concat_60 = concat(axis = concat_60_axis_0, interleave = concat_60_interleave_0, values = (concat_60_values0_0, concat_60_values1_0, gather_123_cast_uint16_to_int32))[name = tensor<string, []>("concat_60")];
            tensor<int32, [3]> var_2331_begin_0 = const()[name = tensor<string, []>("op_2331_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2331_end_mask_0 = const()[name = tensor<string, []>("op_2331_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2331_cast_fp16 = slice_by_index(begin = var_2331_begin_0, end = concat_60, end_mask = var_2331_end_mask_0, x = seg_119_cast_fp16)[name = tensor<string, []>("op_2331_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_669_cast_fp16 = add(x = var_2317_cast_fp16, y = var_2331_cast_fp16)[name = tensor<string, []>("input_669_cast_fp16")];
            tensor<string, []> input_671_pad_type_0 = const()[name = tensor<string, []>("input_671_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_671_strides_0 = const()[name = tensor<string, []>("input_671_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_671_pad_0 = const()[name = tensor<string, []>("input_671_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_671_dilations_0 = const()[name = tensor<string, []>("input_671_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_671_groups_0 = const()[name = tensor<string, []>("input_671_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd18_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd18_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5686912)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd18_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd18_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5703360)))];
            tensor<fp16, [1, 64, ?]> input_671_cast_fp16 = conv(bias = net_xvector_block2_tdnnd18_cam_layer_linear1_bias_to_fp16, dilations = input_671_dilations_0, groups = input_671_groups_0, pad = input_671_pad_0, pad_type = input_671_pad_type_0, strides = input_671_strides_0, weight = net_xvector_block2_tdnnd18_cam_layer_linear1_weight_to_fp16, x = input_669_cast_fp16)[name = tensor<string, []>("input_671_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_673_cast_fp16 = relu(x = input_671_cast_fp16)[name = tensor<string, []>("input_673_cast_fp16")];
            tensor<string, []> input_675_pad_type_0 = const()[name = tensor<string, []>("input_675_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_675_strides_0 = const()[name = tensor<string, []>("input_675_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_675_pad_0 = const()[name = tensor<string, []>("input_675_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_675_dilations_0 = const()[name = tensor<string, []>("input_675_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_675_groups_0 = const()[name = tensor<string, []>("input_675_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd18_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd18_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5703552)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd18_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd18_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5707712)))];
            tensor<fp16, [1, 32, ?]> input_675_cast_fp16 = conv(bias = net_xvector_block2_tdnnd18_cam_layer_linear2_bias_to_fp16, dilations = input_675_dilations_0, groups = input_675_groups_0, pad = input_675_pad_0, pad_type = input_675_pad_type_0, strides = input_675_strides_0, weight = net_xvector_block2_tdnnd18_cam_layer_linear2_weight_to_fp16, x = input_673_cast_fp16)[name = tensor<string, []>("input_675_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_59_cast_fp16 = sigmoid(x = input_675_cast_fp16)[name = tensor<string, []>("m_59_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2349_cast_fp16 = mul(x = y_59_cast_fp16, y = m_59_cast_fp16)[name = tensor<string, []>("op_2349_cast_fp16")];
            tensor<bool, []> input_677_interleave_0 = const()[name = tensor<string, []>("input_677_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 832, ?]> input_677_cast_fp16 = concat(axis = var_11, interleave = input_677_interleave_0, values = (input_657_cast_fp16, var_2349_cast_fp16))[name = tensor<string, []>("input_677_cast_fp16")];
            tensor<fp16, [832]> net_xvector_block2_tdnnd19_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd19_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [832]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5707840)))];
            tensor<fp16, [832]> net_xvector_block2_tdnnd19_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd19_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [832]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5709568)))];
            tensor<fp16, [832]> net_xvector_block2_tdnnd19_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd19_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [832]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5711296)))];
            tensor<fp16, [832]> net_xvector_block2_tdnnd19_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd19_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [832]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5713024)))];
            tensor<fp16, [1, 832, ?]> input_679_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd19_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd19_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd19_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd19_nonlinear1_batchnorm_running_var_to_fp16, x = input_677_cast_fp16)[name = tensor<string, []>("input_679_cast_fp16")];
            tensor<fp16, [1, 832, ?]> input_681_cast_fp16 = relu(x = input_679_cast_fp16)[name = tensor<string, []>("input_681_cast_fp16")];
            tensor<string, []> input_683_pad_type_0 = const()[name = tensor<string, []>("input_683_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_683_strides_0 = const()[name = tensor<string, []>("input_683_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_683_pad_0 = const()[name = tensor<string, []>("input_683_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_683_dilations_0 = const()[name = tensor<string, []>("input_683_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_683_groups_0 = const()[name = tensor<string, []>("input_683_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 832, 1]> const_86_to_fp16 = const()[name = tensor<string, []>("const_86_to_fp16"), val = tensor<fp16, [128, 832, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5714752)))];
            tensor<fp16, [128]> const_87_to_fp16 = const()[name = tensor<string, []>("const_87_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5927808)))];
            tensor<fp16, [1, 128, ?]> input_685_cast_fp16 = conv(bias = const_87_to_fp16, dilations = input_683_dilations_0, groups = input_683_groups_0, pad = input_683_pad_0, pad_type = input_683_pad_type_0, strides = input_683_strides_0, weight = const_86_to_fp16, x = input_681_cast_fp16)[name = tensor<string, []>("input_685_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_687_cast_fp16 = relu(x = input_685_cast_fp16)[name = tensor<string, []>("input_687_cast_fp16")];
            tensor<string, []> y_61_pad_type_0 = const()[name = tensor<string, []>("y_61_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_61_pad_0 = const()[name = tensor<string, []>("y_61_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_61_dilations_0 = const()[name = tensor<string, []>("y_61_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_61_strides_0 = const()[name = tensor<string, []>("y_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_61_groups_0 = const()[name = tensor<string, []>("y_61_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd19_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd19_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5928128)))];
            tensor<fp16, [1, 32, ?]> y_61_cast_fp16 = conv(dilations = y_61_dilations_0, groups = y_61_groups_0, pad = y_61_pad_0, pad_type = y_61_pad_type_0, strides = y_61_strides_0, weight = net_xvector_block2_tdnnd19_cam_layer_linear_local_weight_to_fp16, x = input_687_cast_fp16)[name = tensor<string, []>("y_61_cast_fp16")];
            tensor<int32, [1]> var_2386_axes_0 = const()[name = tensor<string, []>("op_2386_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2386_keep_dims_0 = const()[name = tensor<string, []>("op_2386_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2386_cast_fp16 = reduce_mean(axes = var_2386_axes_0, keep_dims = var_2386_keep_dims_0, x = input_687_cast_fp16)[name = tensor<string, []>("op_2386_cast_fp16")];
            tensor<int32, [1]> var_2387 = const()[name = tensor<string, []>("op_2387"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2388 = const()[name = tensor<string, []>("op_2388"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_121_pad_type_0 = const()[name = tensor<string, []>("seg_121_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_121_pad_0 = const()[name = tensor<string, []>("seg_121_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_121_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_121_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_121_ceil_mode_0 = const()[name = tensor<string, []>("seg_121_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_121_cast_fp16 = avg_pool(ceil_mode = seg_121_ceil_mode_0, exclude_padding_from_average = seg_121_exclude_padding_from_average_0, kernel_sizes = var_2387, pad = seg_121_pad_0, pad_type = seg_121_pad_type_0, strides = var_2388, x = input_687_cast_fp16)[name = tensor<string, []>("seg_121_cast_fp16")];
            tensor<int32, [3]> var_2391_shape_cast_fp16 = shape(x = seg_121_cast_fp16)[name = tensor<string, []>("op_2391_shape_cast_fp16")];
            tensor<int32, []> gather_124 = const()[name = tensor<string, []>("gather_124"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_125 = const()[name = tensor<string, []>("gather_125"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_126_axis_0 = const()[name = tensor<string, []>("gather_126_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_126_batch_dims_0 = const()[name = tensor<string, []>("gather_126_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_126_validate_indices_0 = const()[name = tensor<string, []>("gather_126_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2391_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2391_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_126_to_uint16 = const()[name = tensor<string, []>("select_126_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2391_shape_cast_fp16_to_uint16 = cast(dtype = var_2391_shape_cast_fp16_to_uint16_dtype_0, x = var_2391_shape_cast_fp16)[name = tensor<string, []>("cast_195")];
            tensor<uint16, []> gather_126_cast_uint16 = gather(axis = gather_126_axis_0, batch_dims = gather_126_batch_dims_0, indices = select_126_to_uint16, validate_indices = gather_126_validate_indices_0, x = var_2391_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_126_cast_uint16")];
            tensor<string, []> gather_126_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_126_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2394_axes_0 = const()[name = tensor<string, []>("op_2394_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2394_cast_fp16 = expand_dims(axes = var_2394_axes_0, x = seg_121_cast_fp16)[name = tensor<string, []>("op_2394_cast_fp16")];
            tensor<int32, []> concat_61_axis_0 = const()[name = tensor<string, []>("concat_61_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_61_interleave_0 = const()[name = tensor<string, []>("concat_61_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_126_cast_uint16_to_int32 = cast(dtype = gather_126_cast_uint16_to_int32_dtype_0, x = gather_126_cast_uint16)[name = tensor<string, []>("cast_194")];
            tensor<int32, [4]> concat_61 = concat(axis = concat_61_axis_0, interleave = concat_61_interleave_0, values = (gather_124, gather_125, gather_126_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_61")];
            tensor<int32, [4]> shape_157_cast_fp16 = shape(x = var_2394_cast_fp16)[name = tensor<string, []>("shape_157_cast_fp16")];
            tensor<int32, [4]> real_div_30 = real_div(x = concat_61, y = shape_157_cast_fp16)[name = tensor<string, []>("real_div_30")];
            tensor<fp16, [?, ?, ?, ?]> var_2396_cast_fp16 = tile(reps = real_div_30, x = var_2394_cast_fp16)[name = tensor<string, []>("op_2396_cast_fp16")];
            tensor<int32, [3]> var_2397 = const()[name = tensor<string, []>("op_2397"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_123_cast_fp16 = reshape(shape = var_2397, x = var_2396_cast_fp16)[name = tensor<string, []>("seg_123_cast_fp16")];
            tensor<int32, [3]> var_2399_shape_cast_fp16 = shape(x = input_687_cast_fp16)[name = tensor<string, []>("op_2399_shape_cast_fp16")];
            tensor<int32, []> gather_127_axis_0 = const()[name = tensor<string, []>("gather_127_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_127_batch_dims_0 = const()[name = tensor<string, []>("gather_127_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_127_validate_indices_0 = const()[name = tensor<string, []>("gather_127_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2399_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2399_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_127_to_uint16 = const()[name = tensor<string, []>("select_127_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2399_shape_cast_fp16_to_uint16 = cast(dtype = var_2399_shape_cast_fp16_to_uint16_dtype_0, x = var_2399_shape_cast_fp16)[name = tensor<string, []>("cast_193")];
            tensor<uint16, []> gather_127_cast_uint16 = gather(axis = gather_127_axis_0, batch_dims = gather_127_batch_dims_0, indices = select_127_to_uint16, validate_indices = gather_127_validate_indices_0, x = var_2399_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_127_cast_uint16")];
            tensor<string, []> gather_127_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_127_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_62_values0_0 = const()[name = tensor<string, []>("concat_62_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_62_values1_0 = const()[name = tensor<string, []>("concat_62_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_62_axis_0 = const()[name = tensor<string, []>("concat_62_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_62_interleave_0 = const()[name = tensor<string, []>("concat_62_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_127_cast_uint16_to_int32 = cast(dtype = gather_127_cast_uint16_to_int32_dtype_0, x = gather_127_cast_uint16)[name = tensor<string, []>("cast_192")];
            tensor<int32, [3]> concat_62 = concat(axis = concat_62_axis_0, interleave = concat_62_interleave_0, values = (concat_62_values0_0, concat_62_values1_0, gather_127_cast_uint16_to_int32))[name = tensor<string, []>("concat_62")];
            tensor<int32, [3]> var_2400_begin_0 = const()[name = tensor<string, []>("op_2400_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2400_end_mask_0 = const()[name = tensor<string, []>("op_2400_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2400_cast_fp16 = slice_by_index(begin = var_2400_begin_0, end = concat_62, end_mask = var_2400_end_mask_0, x = seg_123_cast_fp16)[name = tensor<string, []>("op_2400_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_689_cast_fp16 = add(x = var_2386_cast_fp16, y = var_2400_cast_fp16)[name = tensor<string, []>("input_689_cast_fp16")];
            tensor<string, []> input_691_pad_type_0 = const()[name = tensor<string, []>("input_691_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_691_strides_0 = const()[name = tensor<string, []>("input_691_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_691_pad_0 = const()[name = tensor<string, []>("input_691_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_691_dilations_0 = const()[name = tensor<string, []>("input_691_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_691_groups_0 = const()[name = tensor<string, []>("input_691_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd19_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd19_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5952768)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd19_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd19_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5969216)))];
            tensor<fp16, [1, 64, ?]> input_691_cast_fp16 = conv(bias = net_xvector_block2_tdnnd19_cam_layer_linear1_bias_to_fp16, dilations = input_691_dilations_0, groups = input_691_groups_0, pad = input_691_pad_0, pad_type = input_691_pad_type_0, strides = input_691_strides_0, weight = net_xvector_block2_tdnnd19_cam_layer_linear1_weight_to_fp16, x = input_689_cast_fp16)[name = tensor<string, []>("input_691_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_693_cast_fp16 = relu(x = input_691_cast_fp16)[name = tensor<string, []>("input_693_cast_fp16")];
            tensor<string, []> input_695_pad_type_0 = const()[name = tensor<string, []>("input_695_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_695_strides_0 = const()[name = tensor<string, []>("input_695_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_695_pad_0 = const()[name = tensor<string, []>("input_695_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_695_dilations_0 = const()[name = tensor<string, []>("input_695_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_695_groups_0 = const()[name = tensor<string, []>("input_695_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd19_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd19_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5969408)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd19_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd19_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5973568)))];
            tensor<fp16, [1, 32, ?]> input_695_cast_fp16 = conv(bias = net_xvector_block2_tdnnd19_cam_layer_linear2_bias_to_fp16, dilations = input_695_dilations_0, groups = input_695_groups_0, pad = input_695_pad_0, pad_type = input_695_pad_type_0, strides = input_695_strides_0, weight = net_xvector_block2_tdnnd19_cam_layer_linear2_weight_to_fp16, x = input_693_cast_fp16)[name = tensor<string, []>("input_695_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_61_cast_fp16 = sigmoid(x = input_695_cast_fp16)[name = tensor<string, []>("m_61_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2418_cast_fp16 = mul(x = y_61_cast_fp16, y = m_61_cast_fp16)[name = tensor<string, []>("op_2418_cast_fp16")];
            tensor<bool, []> input_697_interleave_0 = const()[name = tensor<string, []>("input_697_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 864, ?]> input_697_cast_fp16 = concat(axis = var_11, interleave = input_697_interleave_0, values = (input_677_cast_fp16, var_2418_cast_fp16))[name = tensor<string, []>("input_697_cast_fp16")];
            tensor<fp16, [864]> net_xvector_block2_tdnnd20_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd20_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [864]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5973696)))];
            tensor<fp16, [864]> net_xvector_block2_tdnnd20_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd20_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [864]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5975488)))];
            tensor<fp16, [864]> net_xvector_block2_tdnnd20_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd20_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [864]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5977280)))];
            tensor<fp16, [864]> net_xvector_block2_tdnnd20_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd20_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [864]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5979072)))];
            tensor<fp16, [1, 864, ?]> input_699_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd20_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd20_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd20_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd20_nonlinear1_batchnorm_running_var_to_fp16, x = input_697_cast_fp16)[name = tensor<string, []>("input_699_cast_fp16")];
            tensor<fp16, [1, 864, ?]> input_701_cast_fp16 = relu(x = input_699_cast_fp16)[name = tensor<string, []>("input_701_cast_fp16")];
            tensor<string, []> input_703_pad_type_0 = const()[name = tensor<string, []>("input_703_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_703_strides_0 = const()[name = tensor<string, []>("input_703_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_703_pad_0 = const()[name = tensor<string, []>("input_703_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_703_dilations_0 = const()[name = tensor<string, []>("input_703_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_703_groups_0 = const()[name = tensor<string, []>("input_703_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 864, 1]> const_88_to_fp16 = const()[name = tensor<string, []>("const_88_to_fp16"), val = tensor<fp16, [128, 864, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5980864)))];
            tensor<fp16, [128]> const_89_to_fp16 = const()[name = tensor<string, []>("const_89_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6202112)))];
            tensor<fp16, [1, 128, ?]> input_705_cast_fp16 = conv(bias = const_89_to_fp16, dilations = input_703_dilations_0, groups = input_703_groups_0, pad = input_703_pad_0, pad_type = input_703_pad_type_0, strides = input_703_strides_0, weight = const_88_to_fp16, x = input_701_cast_fp16)[name = tensor<string, []>("input_705_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_707_cast_fp16 = relu(x = input_705_cast_fp16)[name = tensor<string, []>("input_707_cast_fp16")];
            tensor<string, []> y_63_pad_type_0 = const()[name = tensor<string, []>("y_63_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_63_pad_0 = const()[name = tensor<string, []>("y_63_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_63_dilations_0 = const()[name = tensor<string, []>("y_63_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_63_strides_0 = const()[name = tensor<string, []>("y_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_63_groups_0 = const()[name = tensor<string, []>("y_63_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd20_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd20_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6202432)))];
            tensor<fp16, [1, 32, ?]> y_63_cast_fp16 = conv(dilations = y_63_dilations_0, groups = y_63_groups_0, pad = y_63_pad_0, pad_type = y_63_pad_type_0, strides = y_63_strides_0, weight = net_xvector_block2_tdnnd20_cam_layer_linear_local_weight_to_fp16, x = input_707_cast_fp16)[name = tensor<string, []>("y_63_cast_fp16")];
            tensor<int32, [1]> var_2455_axes_0 = const()[name = tensor<string, []>("op_2455_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2455_keep_dims_0 = const()[name = tensor<string, []>("op_2455_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2455_cast_fp16 = reduce_mean(axes = var_2455_axes_0, keep_dims = var_2455_keep_dims_0, x = input_707_cast_fp16)[name = tensor<string, []>("op_2455_cast_fp16")];
            tensor<int32, [1]> var_2456 = const()[name = tensor<string, []>("op_2456"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2457 = const()[name = tensor<string, []>("op_2457"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_125_pad_type_0 = const()[name = tensor<string, []>("seg_125_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_125_pad_0 = const()[name = tensor<string, []>("seg_125_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_125_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_125_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_125_ceil_mode_0 = const()[name = tensor<string, []>("seg_125_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_125_cast_fp16 = avg_pool(ceil_mode = seg_125_ceil_mode_0, exclude_padding_from_average = seg_125_exclude_padding_from_average_0, kernel_sizes = var_2456, pad = seg_125_pad_0, pad_type = seg_125_pad_type_0, strides = var_2457, x = input_707_cast_fp16)[name = tensor<string, []>("seg_125_cast_fp16")];
            tensor<int32, [3]> var_2460_shape_cast_fp16 = shape(x = seg_125_cast_fp16)[name = tensor<string, []>("op_2460_shape_cast_fp16")];
            tensor<int32, []> gather_128 = const()[name = tensor<string, []>("gather_128"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_129 = const()[name = tensor<string, []>("gather_129"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_130_axis_0 = const()[name = tensor<string, []>("gather_130_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_130_batch_dims_0 = const()[name = tensor<string, []>("gather_130_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_130_validate_indices_0 = const()[name = tensor<string, []>("gather_130_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2460_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2460_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_130_to_uint16 = const()[name = tensor<string, []>("select_130_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2460_shape_cast_fp16_to_uint16 = cast(dtype = var_2460_shape_cast_fp16_to_uint16_dtype_0, x = var_2460_shape_cast_fp16)[name = tensor<string, []>("cast_191")];
            tensor<uint16, []> gather_130_cast_uint16 = gather(axis = gather_130_axis_0, batch_dims = gather_130_batch_dims_0, indices = select_130_to_uint16, validate_indices = gather_130_validate_indices_0, x = var_2460_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_130_cast_uint16")];
            tensor<string, []> gather_130_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_130_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2463_axes_0 = const()[name = tensor<string, []>("op_2463_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2463_cast_fp16 = expand_dims(axes = var_2463_axes_0, x = seg_125_cast_fp16)[name = tensor<string, []>("op_2463_cast_fp16")];
            tensor<int32, []> concat_63_axis_0 = const()[name = tensor<string, []>("concat_63_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_63_interleave_0 = const()[name = tensor<string, []>("concat_63_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_130_cast_uint16_to_int32 = cast(dtype = gather_130_cast_uint16_to_int32_dtype_0, x = gather_130_cast_uint16)[name = tensor<string, []>("cast_190")];
            tensor<int32, [4]> concat_63 = concat(axis = concat_63_axis_0, interleave = concat_63_interleave_0, values = (gather_128, gather_129, gather_130_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_63")];
            tensor<int32, [4]> shape_162_cast_fp16 = shape(x = var_2463_cast_fp16)[name = tensor<string, []>("shape_162_cast_fp16")];
            tensor<int32, [4]> real_div_31 = real_div(x = concat_63, y = shape_162_cast_fp16)[name = tensor<string, []>("real_div_31")];
            tensor<fp16, [?, ?, ?, ?]> var_2465_cast_fp16 = tile(reps = real_div_31, x = var_2463_cast_fp16)[name = tensor<string, []>("op_2465_cast_fp16")];
            tensor<int32, [3]> var_2466 = const()[name = tensor<string, []>("op_2466"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_127_cast_fp16 = reshape(shape = var_2466, x = var_2465_cast_fp16)[name = tensor<string, []>("seg_127_cast_fp16")];
            tensor<int32, [3]> var_2468_shape_cast_fp16 = shape(x = input_707_cast_fp16)[name = tensor<string, []>("op_2468_shape_cast_fp16")];
            tensor<int32, []> gather_131_axis_0 = const()[name = tensor<string, []>("gather_131_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_131_batch_dims_0 = const()[name = tensor<string, []>("gather_131_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_131_validate_indices_0 = const()[name = tensor<string, []>("gather_131_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2468_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2468_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_131_to_uint16 = const()[name = tensor<string, []>("select_131_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2468_shape_cast_fp16_to_uint16 = cast(dtype = var_2468_shape_cast_fp16_to_uint16_dtype_0, x = var_2468_shape_cast_fp16)[name = tensor<string, []>("cast_189")];
            tensor<uint16, []> gather_131_cast_uint16 = gather(axis = gather_131_axis_0, batch_dims = gather_131_batch_dims_0, indices = select_131_to_uint16, validate_indices = gather_131_validate_indices_0, x = var_2468_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_131_cast_uint16")];
            tensor<string, []> gather_131_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_131_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_64_values0_0 = const()[name = tensor<string, []>("concat_64_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_64_values1_0 = const()[name = tensor<string, []>("concat_64_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_64_axis_0 = const()[name = tensor<string, []>("concat_64_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_64_interleave_0 = const()[name = tensor<string, []>("concat_64_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_131_cast_uint16_to_int32 = cast(dtype = gather_131_cast_uint16_to_int32_dtype_0, x = gather_131_cast_uint16)[name = tensor<string, []>("cast_188")];
            tensor<int32, [3]> concat_64 = concat(axis = concat_64_axis_0, interleave = concat_64_interleave_0, values = (concat_64_values0_0, concat_64_values1_0, gather_131_cast_uint16_to_int32))[name = tensor<string, []>("concat_64")];
            tensor<int32, [3]> var_2469_begin_0 = const()[name = tensor<string, []>("op_2469_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2469_end_mask_0 = const()[name = tensor<string, []>("op_2469_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2469_cast_fp16 = slice_by_index(begin = var_2469_begin_0, end = concat_64, end_mask = var_2469_end_mask_0, x = seg_127_cast_fp16)[name = tensor<string, []>("op_2469_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_709_cast_fp16 = add(x = var_2455_cast_fp16, y = var_2469_cast_fp16)[name = tensor<string, []>("input_709_cast_fp16")];
            tensor<string, []> input_711_pad_type_0 = const()[name = tensor<string, []>("input_711_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_711_strides_0 = const()[name = tensor<string, []>("input_711_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_711_pad_0 = const()[name = tensor<string, []>("input_711_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_711_dilations_0 = const()[name = tensor<string, []>("input_711_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_711_groups_0 = const()[name = tensor<string, []>("input_711_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd20_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd20_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6227072)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd20_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd20_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6243520)))];
            tensor<fp16, [1, 64, ?]> input_711_cast_fp16 = conv(bias = net_xvector_block2_tdnnd20_cam_layer_linear1_bias_to_fp16, dilations = input_711_dilations_0, groups = input_711_groups_0, pad = input_711_pad_0, pad_type = input_711_pad_type_0, strides = input_711_strides_0, weight = net_xvector_block2_tdnnd20_cam_layer_linear1_weight_to_fp16, x = input_709_cast_fp16)[name = tensor<string, []>("input_711_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_713_cast_fp16 = relu(x = input_711_cast_fp16)[name = tensor<string, []>("input_713_cast_fp16")];
            tensor<string, []> input_715_pad_type_0 = const()[name = tensor<string, []>("input_715_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_715_strides_0 = const()[name = tensor<string, []>("input_715_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_715_pad_0 = const()[name = tensor<string, []>("input_715_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_715_dilations_0 = const()[name = tensor<string, []>("input_715_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_715_groups_0 = const()[name = tensor<string, []>("input_715_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd20_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd20_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6243712)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd20_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd20_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6247872)))];
            tensor<fp16, [1, 32, ?]> input_715_cast_fp16 = conv(bias = net_xvector_block2_tdnnd20_cam_layer_linear2_bias_to_fp16, dilations = input_715_dilations_0, groups = input_715_groups_0, pad = input_715_pad_0, pad_type = input_715_pad_type_0, strides = input_715_strides_0, weight = net_xvector_block2_tdnnd20_cam_layer_linear2_weight_to_fp16, x = input_713_cast_fp16)[name = tensor<string, []>("input_715_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_63_cast_fp16 = sigmoid(x = input_715_cast_fp16)[name = tensor<string, []>("m_63_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2487_cast_fp16 = mul(x = y_63_cast_fp16, y = m_63_cast_fp16)[name = tensor<string, []>("op_2487_cast_fp16")];
            tensor<bool, []> input_717_interleave_0 = const()[name = tensor<string, []>("input_717_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 896, ?]> input_717_cast_fp16 = concat(axis = var_11, interleave = input_717_interleave_0, values = (input_697_cast_fp16, var_2487_cast_fp16))[name = tensor<string, []>("input_717_cast_fp16")];
            tensor<fp16, [896]> net_xvector_block2_tdnnd21_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd21_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6248000)))];
            tensor<fp16, [896]> net_xvector_block2_tdnnd21_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd21_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6249856)))];
            tensor<fp16, [896]> net_xvector_block2_tdnnd21_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd21_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6251712)))];
            tensor<fp16, [896]> net_xvector_block2_tdnnd21_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd21_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6253568)))];
            tensor<fp16, [1, 896, ?]> input_719_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd21_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd21_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd21_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd21_nonlinear1_batchnorm_running_var_to_fp16, x = input_717_cast_fp16)[name = tensor<string, []>("input_719_cast_fp16")];
            tensor<fp16, [1, 896, ?]> input_721_cast_fp16 = relu(x = input_719_cast_fp16)[name = tensor<string, []>("input_721_cast_fp16")];
            tensor<string, []> input_723_pad_type_0 = const()[name = tensor<string, []>("input_723_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_723_strides_0 = const()[name = tensor<string, []>("input_723_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_723_pad_0 = const()[name = tensor<string, []>("input_723_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_723_dilations_0 = const()[name = tensor<string, []>("input_723_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_723_groups_0 = const()[name = tensor<string, []>("input_723_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 896, 1]> const_90_to_fp16 = const()[name = tensor<string, []>("const_90_to_fp16"), val = tensor<fp16, [128, 896, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6255424)))];
            tensor<fp16, [128]> const_91_to_fp16 = const()[name = tensor<string, []>("const_91_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6484864)))];
            tensor<fp16, [1, 128, ?]> input_725_cast_fp16 = conv(bias = const_91_to_fp16, dilations = input_723_dilations_0, groups = input_723_groups_0, pad = input_723_pad_0, pad_type = input_723_pad_type_0, strides = input_723_strides_0, weight = const_90_to_fp16, x = input_721_cast_fp16)[name = tensor<string, []>("input_725_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_727_cast_fp16 = relu(x = input_725_cast_fp16)[name = tensor<string, []>("input_727_cast_fp16")];
            tensor<string, []> y_65_pad_type_0 = const()[name = tensor<string, []>("y_65_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_65_pad_0 = const()[name = tensor<string, []>("y_65_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_65_dilations_0 = const()[name = tensor<string, []>("y_65_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_65_strides_0 = const()[name = tensor<string, []>("y_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_65_groups_0 = const()[name = tensor<string, []>("y_65_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd21_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd21_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6485184)))];
            tensor<fp16, [1, 32, ?]> y_65_cast_fp16 = conv(dilations = y_65_dilations_0, groups = y_65_groups_0, pad = y_65_pad_0, pad_type = y_65_pad_type_0, strides = y_65_strides_0, weight = net_xvector_block2_tdnnd21_cam_layer_linear_local_weight_to_fp16, x = input_727_cast_fp16)[name = tensor<string, []>("y_65_cast_fp16")];
            tensor<int32, [1]> var_2524_axes_0 = const()[name = tensor<string, []>("op_2524_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2524_keep_dims_0 = const()[name = tensor<string, []>("op_2524_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2524_cast_fp16 = reduce_mean(axes = var_2524_axes_0, keep_dims = var_2524_keep_dims_0, x = input_727_cast_fp16)[name = tensor<string, []>("op_2524_cast_fp16")];
            tensor<int32, [1]> var_2525 = const()[name = tensor<string, []>("op_2525"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2526 = const()[name = tensor<string, []>("op_2526"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_129_pad_type_0 = const()[name = tensor<string, []>("seg_129_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_129_pad_0 = const()[name = tensor<string, []>("seg_129_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_129_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_129_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_129_ceil_mode_0 = const()[name = tensor<string, []>("seg_129_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_129_cast_fp16 = avg_pool(ceil_mode = seg_129_ceil_mode_0, exclude_padding_from_average = seg_129_exclude_padding_from_average_0, kernel_sizes = var_2525, pad = seg_129_pad_0, pad_type = seg_129_pad_type_0, strides = var_2526, x = input_727_cast_fp16)[name = tensor<string, []>("seg_129_cast_fp16")];
            tensor<int32, [3]> var_2529_shape_cast_fp16 = shape(x = seg_129_cast_fp16)[name = tensor<string, []>("op_2529_shape_cast_fp16")];
            tensor<int32, []> gather_132 = const()[name = tensor<string, []>("gather_132"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_133 = const()[name = tensor<string, []>("gather_133"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_134_axis_0 = const()[name = tensor<string, []>("gather_134_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_134_batch_dims_0 = const()[name = tensor<string, []>("gather_134_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_134_validate_indices_0 = const()[name = tensor<string, []>("gather_134_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2529_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2529_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_134_to_uint16 = const()[name = tensor<string, []>("select_134_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2529_shape_cast_fp16_to_uint16 = cast(dtype = var_2529_shape_cast_fp16_to_uint16_dtype_0, x = var_2529_shape_cast_fp16)[name = tensor<string, []>("cast_187")];
            tensor<uint16, []> gather_134_cast_uint16 = gather(axis = gather_134_axis_0, batch_dims = gather_134_batch_dims_0, indices = select_134_to_uint16, validate_indices = gather_134_validate_indices_0, x = var_2529_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_134_cast_uint16")];
            tensor<string, []> gather_134_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_134_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2532_axes_0 = const()[name = tensor<string, []>("op_2532_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2532_cast_fp16 = expand_dims(axes = var_2532_axes_0, x = seg_129_cast_fp16)[name = tensor<string, []>("op_2532_cast_fp16")];
            tensor<int32, []> concat_65_axis_0 = const()[name = tensor<string, []>("concat_65_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_65_interleave_0 = const()[name = tensor<string, []>("concat_65_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_134_cast_uint16_to_int32 = cast(dtype = gather_134_cast_uint16_to_int32_dtype_0, x = gather_134_cast_uint16)[name = tensor<string, []>("cast_186")];
            tensor<int32, [4]> concat_65 = concat(axis = concat_65_axis_0, interleave = concat_65_interleave_0, values = (gather_132, gather_133, gather_134_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_65")];
            tensor<int32, [4]> shape_167_cast_fp16 = shape(x = var_2532_cast_fp16)[name = tensor<string, []>("shape_167_cast_fp16")];
            tensor<int32, [4]> real_div_32 = real_div(x = concat_65, y = shape_167_cast_fp16)[name = tensor<string, []>("real_div_32")];
            tensor<fp16, [?, ?, ?, ?]> var_2534_cast_fp16 = tile(reps = real_div_32, x = var_2532_cast_fp16)[name = tensor<string, []>("op_2534_cast_fp16")];
            tensor<int32, [3]> var_2535 = const()[name = tensor<string, []>("op_2535"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_131_cast_fp16 = reshape(shape = var_2535, x = var_2534_cast_fp16)[name = tensor<string, []>("seg_131_cast_fp16")];
            tensor<int32, [3]> var_2537_shape_cast_fp16 = shape(x = input_727_cast_fp16)[name = tensor<string, []>("op_2537_shape_cast_fp16")];
            tensor<int32, []> gather_135_axis_0 = const()[name = tensor<string, []>("gather_135_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_135_batch_dims_0 = const()[name = tensor<string, []>("gather_135_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_135_validate_indices_0 = const()[name = tensor<string, []>("gather_135_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2537_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2537_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_135_to_uint16 = const()[name = tensor<string, []>("select_135_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2537_shape_cast_fp16_to_uint16 = cast(dtype = var_2537_shape_cast_fp16_to_uint16_dtype_0, x = var_2537_shape_cast_fp16)[name = tensor<string, []>("cast_185")];
            tensor<uint16, []> gather_135_cast_uint16 = gather(axis = gather_135_axis_0, batch_dims = gather_135_batch_dims_0, indices = select_135_to_uint16, validate_indices = gather_135_validate_indices_0, x = var_2537_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_135_cast_uint16")];
            tensor<string, []> gather_135_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_135_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_66_values0_0 = const()[name = tensor<string, []>("concat_66_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_66_values1_0 = const()[name = tensor<string, []>("concat_66_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_66_axis_0 = const()[name = tensor<string, []>("concat_66_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_66_interleave_0 = const()[name = tensor<string, []>("concat_66_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_135_cast_uint16_to_int32 = cast(dtype = gather_135_cast_uint16_to_int32_dtype_0, x = gather_135_cast_uint16)[name = tensor<string, []>("cast_184")];
            tensor<int32, [3]> concat_66 = concat(axis = concat_66_axis_0, interleave = concat_66_interleave_0, values = (concat_66_values0_0, concat_66_values1_0, gather_135_cast_uint16_to_int32))[name = tensor<string, []>("concat_66")];
            tensor<int32, [3]> var_2538_begin_0 = const()[name = tensor<string, []>("op_2538_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2538_end_mask_0 = const()[name = tensor<string, []>("op_2538_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2538_cast_fp16 = slice_by_index(begin = var_2538_begin_0, end = concat_66, end_mask = var_2538_end_mask_0, x = seg_131_cast_fp16)[name = tensor<string, []>("op_2538_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_729_cast_fp16 = add(x = var_2524_cast_fp16, y = var_2538_cast_fp16)[name = tensor<string, []>("input_729_cast_fp16")];
            tensor<string, []> input_731_pad_type_0 = const()[name = tensor<string, []>("input_731_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_731_strides_0 = const()[name = tensor<string, []>("input_731_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_731_pad_0 = const()[name = tensor<string, []>("input_731_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_731_dilations_0 = const()[name = tensor<string, []>("input_731_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_731_groups_0 = const()[name = tensor<string, []>("input_731_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd21_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd21_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6509824)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd21_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd21_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6526272)))];
            tensor<fp16, [1, 64, ?]> input_731_cast_fp16 = conv(bias = net_xvector_block2_tdnnd21_cam_layer_linear1_bias_to_fp16, dilations = input_731_dilations_0, groups = input_731_groups_0, pad = input_731_pad_0, pad_type = input_731_pad_type_0, strides = input_731_strides_0, weight = net_xvector_block2_tdnnd21_cam_layer_linear1_weight_to_fp16, x = input_729_cast_fp16)[name = tensor<string, []>("input_731_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_733_cast_fp16 = relu(x = input_731_cast_fp16)[name = tensor<string, []>("input_733_cast_fp16")];
            tensor<string, []> input_735_pad_type_0 = const()[name = tensor<string, []>("input_735_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_735_strides_0 = const()[name = tensor<string, []>("input_735_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_735_pad_0 = const()[name = tensor<string, []>("input_735_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_735_dilations_0 = const()[name = tensor<string, []>("input_735_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_735_groups_0 = const()[name = tensor<string, []>("input_735_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd21_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd21_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6526464)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd21_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd21_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6530624)))];
            tensor<fp16, [1, 32, ?]> input_735_cast_fp16 = conv(bias = net_xvector_block2_tdnnd21_cam_layer_linear2_bias_to_fp16, dilations = input_735_dilations_0, groups = input_735_groups_0, pad = input_735_pad_0, pad_type = input_735_pad_type_0, strides = input_735_strides_0, weight = net_xvector_block2_tdnnd21_cam_layer_linear2_weight_to_fp16, x = input_733_cast_fp16)[name = tensor<string, []>("input_735_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_65_cast_fp16 = sigmoid(x = input_735_cast_fp16)[name = tensor<string, []>("m_65_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2556_cast_fp16 = mul(x = y_65_cast_fp16, y = m_65_cast_fp16)[name = tensor<string, []>("op_2556_cast_fp16")];
            tensor<bool, []> input_737_interleave_0 = const()[name = tensor<string, []>("input_737_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 928, ?]> input_737_cast_fp16 = concat(axis = var_11, interleave = input_737_interleave_0, values = (input_717_cast_fp16, var_2556_cast_fp16))[name = tensor<string, []>("input_737_cast_fp16")];
            tensor<fp16, [928]> net_xvector_block2_tdnnd22_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd22_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [928]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6530752)))];
            tensor<fp16, [928]> net_xvector_block2_tdnnd22_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd22_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [928]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6532672)))];
            tensor<fp16, [928]> net_xvector_block2_tdnnd22_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd22_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [928]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6534592)))];
            tensor<fp16, [928]> net_xvector_block2_tdnnd22_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd22_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [928]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6536512)))];
            tensor<fp16, [1, 928, ?]> input_739_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd22_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd22_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd22_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd22_nonlinear1_batchnorm_running_var_to_fp16, x = input_737_cast_fp16)[name = tensor<string, []>("input_739_cast_fp16")];
            tensor<fp16, [1, 928, ?]> input_741_cast_fp16 = relu(x = input_739_cast_fp16)[name = tensor<string, []>("input_741_cast_fp16")];
            tensor<string, []> input_743_pad_type_0 = const()[name = tensor<string, []>("input_743_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_743_strides_0 = const()[name = tensor<string, []>("input_743_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_743_pad_0 = const()[name = tensor<string, []>("input_743_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_743_dilations_0 = const()[name = tensor<string, []>("input_743_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_743_groups_0 = const()[name = tensor<string, []>("input_743_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 928, 1]> const_92_to_fp16 = const()[name = tensor<string, []>("const_92_to_fp16"), val = tensor<fp16, [128, 928, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6538432)))];
            tensor<fp16, [128]> const_93_to_fp16 = const()[name = tensor<string, []>("const_93_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6776064)))];
            tensor<fp16, [1, 128, ?]> input_745_cast_fp16 = conv(bias = const_93_to_fp16, dilations = input_743_dilations_0, groups = input_743_groups_0, pad = input_743_pad_0, pad_type = input_743_pad_type_0, strides = input_743_strides_0, weight = const_92_to_fp16, x = input_741_cast_fp16)[name = tensor<string, []>("input_745_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_747_cast_fp16 = relu(x = input_745_cast_fp16)[name = tensor<string, []>("input_747_cast_fp16")];
            tensor<string, []> y_67_pad_type_0 = const()[name = tensor<string, []>("y_67_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_67_pad_0 = const()[name = tensor<string, []>("y_67_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_67_dilations_0 = const()[name = tensor<string, []>("y_67_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_67_strides_0 = const()[name = tensor<string, []>("y_67_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_67_groups_0 = const()[name = tensor<string, []>("y_67_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd22_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd22_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6776384)))];
            tensor<fp16, [1, 32, ?]> y_67_cast_fp16 = conv(dilations = y_67_dilations_0, groups = y_67_groups_0, pad = y_67_pad_0, pad_type = y_67_pad_type_0, strides = y_67_strides_0, weight = net_xvector_block2_tdnnd22_cam_layer_linear_local_weight_to_fp16, x = input_747_cast_fp16)[name = tensor<string, []>("y_67_cast_fp16")];
            tensor<int32, [1]> var_2593_axes_0 = const()[name = tensor<string, []>("op_2593_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2593_keep_dims_0 = const()[name = tensor<string, []>("op_2593_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2593_cast_fp16 = reduce_mean(axes = var_2593_axes_0, keep_dims = var_2593_keep_dims_0, x = input_747_cast_fp16)[name = tensor<string, []>("op_2593_cast_fp16")];
            tensor<int32, [1]> var_2594 = const()[name = tensor<string, []>("op_2594"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2595 = const()[name = tensor<string, []>("op_2595"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_133_pad_type_0 = const()[name = tensor<string, []>("seg_133_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_133_pad_0 = const()[name = tensor<string, []>("seg_133_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_133_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_133_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_133_ceil_mode_0 = const()[name = tensor<string, []>("seg_133_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_133_cast_fp16 = avg_pool(ceil_mode = seg_133_ceil_mode_0, exclude_padding_from_average = seg_133_exclude_padding_from_average_0, kernel_sizes = var_2594, pad = seg_133_pad_0, pad_type = seg_133_pad_type_0, strides = var_2595, x = input_747_cast_fp16)[name = tensor<string, []>("seg_133_cast_fp16")];
            tensor<int32, [3]> var_2598_shape_cast_fp16 = shape(x = seg_133_cast_fp16)[name = tensor<string, []>("op_2598_shape_cast_fp16")];
            tensor<int32, []> gather_136 = const()[name = tensor<string, []>("gather_136"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_137 = const()[name = tensor<string, []>("gather_137"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_138_axis_0 = const()[name = tensor<string, []>("gather_138_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_138_batch_dims_0 = const()[name = tensor<string, []>("gather_138_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_138_validate_indices_0 = const()[name = tensor<string, []>("gather_138_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2598_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2598_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_138_to_uint16 = const()[name = tensor<string, []>("select_138_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2598_shape_cast_fp16_to_uint16 = cast(dtype = var_2598_shape_cast_fp16_to_uint16_dtype_0, x = var_2598_shape_cast_fp16)[name = tensor<string, []>("cast_183")];
            tensor<uint16, []> gather_138_cast_uint16 = gather(axis = gather_138_axis_0, batch_dims = gather_138_batch_dims_0, indices = select_138_to_uint16, validate_indices = gather_138_validate_indices_0, x = var_2598_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_138_cast_uint16")];
            tensor<string, []> gather_138_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_138_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2601_axes_0 = const()[name = tensor<string, []>("op_2601_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2601_cast_fp16 = expand_dims(axes = var_2601_axes_0, x = seg_133_cast_fp16)[name = tensor<string, []>("op_2601_cast_fp16")];
            tensor<int32, []> concat_67_axis_0 = const()[name = tensor<string, []>("concat_67_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_67_interleave_0 = const()[name = tensor<string, []>("concat_67_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_138_cast_uint16_to_int32 = cast(dtype = gather_138_cast_uint16_to_int32_dtype_0, x = gather_138_cast_uint16)[name = tensor<string, []>("cast_182")];
            tensor<int32, [4]> concat_67 = concat(axis = concat_67_axis_0, interleave = concat_67_interleave_0, values = (gather_136, gather_137, gather_138_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_67")];
            tensor<int32, [4]> shape_172_cast_fp16 = shape(x = var_2601_cast_fp16)[name = tensor<string, []>("shape_172_cast_fp16")];
            tensor<int32, [4]> real_div_33 = real_div(x = concat_67, y = shape_172_cast_fp16)[name = tensor<string, []>("real_div_33")];
            tensor<fp16, [?, ?, ?, ?]> var_2603_cast_fp16 = tile(reps = real_div_33, x = var_2601_cast_fp16)[name = tensor<string, []>("op_2603_cast_fp16")];
            tensor<int32, [3]> var_2604 = const()[name = tensor<string, []>("op_2604"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_135_cast_fp16 = reshape(shape = var_2604, x = var_2603_cast_fp16)[name = tensor<string, []>("seg_135_cast_fp16")];
            tensor<int32, [3]> var_2606_shape_cast_fp16 = shape(x = input_747_cast_fp16)[name = tensor<string, []>("op_2606_shape_cast_fp16")];
            tensor<int32, []> gather_139_axis_0 = const()[name = tensor<string, []>("gather_139_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_139_batch_dims_0 = const()[name = tensor<string, []>("gather_139_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_139_validate_indices_0 = const()[name = tensor<string, []>("gather_139_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2606_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2606_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_139_to_uint16 = const()[name = tensor<string, []>("select_139_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2606_shape_cast_fp16_to_uint16 = cast(dtype = var_2606_shape_cast_fp16_to_uint16_dtype_0, x = var_2606_shape_cast_fp16)[name = tensor<string, []>("cast_181")];
            tensor<uint16, []> gather_139_cast_uint16 = gather(axis = gather_139_axis_0, batch_dims = gather_139_batch_dims_0, indices = select_139_to_uint16, validate_indices = gather_139_validate_indices_0, x = var_2606_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_139_cast_uint16")];
            tensor<string, []> gather_139_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_139_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_68_values0_0 = const()[name = tensor<string, []>("concat_68_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_68_values1_0 = const()[name = tensor<string, []>("concat_68_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_68_axis_0 = const()[name = tensor<string, []>("concat_68_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_68_interleave_0 = const()[name = tensor<string, []>("concat_68_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_139_cast_uint16_to_int32 = cast(dtype = gather_139_cast_uint16_to_int32_dtype_0, x = gather_139_cast_uint16)[name = tensor<string, []>("cast_180")];
            tensor<int32, [3]> concat_68 = concat(axis = concat_68_axis_0, interleave = concat_68_interleave_0, values = (concat_68_values0_0, concat_68_values1_0, gather_139_cast_uint16_to_int32))[name = tensor<string, []>("concat_68")];
            tensor<int32, [3]> var_2607_begin_0 = const()[name = tensor<string, []>("op_2607_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2607_end_mask_0 = const()[name = tensor<string, []>("op_2607_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2607_cast_fp16 = slice_by_index(begin = var_2607_begin_0, end = concat_68, end_mask = var_2607_end_mask_0, x = seg_135_cast_fp16)[name = tensor<string, []>("op_2607_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_749_cast_fp16 = add(x = var_2593_cast_fp16, y = var_2607_cast_fp16)[name = tensor<string, []>("input_749_cast_fp16")];
            tensor<string, []> input_751_pad_type_0 = const()[name = tensor<string, []>("input_751_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_751_strides_0 = const()[name = tensor<string, []>("input_751_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_751_pad_0 = const()[name = tensor<string, []>("input_751_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_751_dilations_0 = const()[name = tensor<string, []>("input_751_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_751_groups_0 = const()[name = tensor<string, []>("input_751_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd22_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd22_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6801024)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd22_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd22_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6817472)))];
            tensor<fp16, [1, 64, ?]> input_751_cast_fp16 = conv(bias = net_xvector_block2_tdnnd22_cam_layer_linear1_bias_to_fp16, dilations = input_751_dilations_0, groups = input_751_groups_0, pad = input_751_pad_0, pad_type = input_751_pad_type_0, strides = input_751_strides_0, weight = net_xvector_block2_tdnnd22_cam_layer_linear1_weight_to_fp16, x = input_749_cast_fp16)[name = tensor<string, []>("input_751_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_753_cast_fp16 = relu(x = input_751_cast_fp16)[name = tensor<string, []>("input_753_cast_fp16")];
            tensor<string, []> input_755_pad_type_0 = const()[name = tensor<string, []>("input_755_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_755_strides_0 = const()[name = tensor<string, []>("input_755_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_755_pad_0 = const()[name = tensor<string, []>("input_755_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_755_dilations_0 = const()[name = tensor<string, []>("input_755_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_755_groups_0 = const()[name = tensor<string, []>("input_755_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd22_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd22_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6817664)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd22_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd22_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6821824)))];
            tensor<fp16, [1, 32, ?]> input_755_cast_fp16 = conv(bias = net_xvector_block2_tdnnd22_cam_layer_linear2_bias_to_fp16, dilations = input_755_dilations_0, groups = input_755_groups_0, pad = input_755_pad_0, pad_type = input_755_pad_type_0, strides = input_755_strides_0, weight = net_xvector_block2_tdnnd22_cam_layer_linear2_weight_to_fp16, x = input_753_cast_fp16)[name = tensor<string, []>("input_755_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_67_cast_fp16 = sigmoid(x = input_755_cast_fp16)[name = tensor<string, []>("m_67_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2625_cast_fp16 = mul(x = y_67_cast_fp16, y = m_67_cast_fp16)[name = tensor<string, []>("op_2625_cast_fp16")];
            tensor<bool, []> input_757_interleave_0 = const()[name = tensor<string, []>("input_757_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 960, ?]> input_757_cast_fp16 = concat(axis = var_11, interleave = input_757_interleave_0, values = (input_737_cast_fp16, var_2625_cast_fp16))[name = tensor<string, []>("input_757_cast_fp16")];
            tensor<fp16, [960]> net_xvector_block2_tdnnd23_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd23_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6821952)))];
            tensor<fp16, [960]> net_xvector_block2_tdnnd23_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd23_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6823936)))];
            tensor<fp16, [960]> net_xvector_block2_tdnnd23_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd23_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6825920)))];
            tensor<fp16, [960]> net_xvector_block2_tdnnd23_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd23_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6827904)))];
            tensor<fp16, [1, 960, ?]> input_759_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd23_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd23_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd23_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd23_nonlinear1_batchnorm_running_var_to_fp16, x = input_757_cast_fp16)[name = tensor<string, []>("input_759_cast_fp16")];
            tensor<fp16, [1, 960, ?]> input_761_cast_fp16 = relu(x = input_759_cast_fp16)[name = tensor<string, []>("input_761_cast_fp16")];
            tensor<string, []> input_763_pad_type_0 = const()[name = tensor<string, []>("input_763_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_763_strides_0 = const()[name = tensor<string, []>("input_763_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_763_pad_0 = const()[name = tensor<string, []>("input_763_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_763_dilations_0 = const()[name = tensor<string, []>("input_763_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_763_groups_0 = const()[name = tensor<string, []>("input_763_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 960, 1]> const_94_to_fp16 = const()[name = tensor<string, []>("const_94_to_fp16"), val = tensor<fp16, [128, 960, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6829888)))];
            tensor<fp16, [128]> const_95_to_fp16 = const()[name = tensor<string, []>("const_95_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7075712)))];
            tensor<fp16, [1, 128, ?]> input_765_cast_fp16 = conv(bias = const_95_to_fp16, dilations = input_763_dilations_0, groups = input_763_groups_0, pad = input_763_pad_0, pad_type = input_763_pad_type_0, strides = input_763_strides_0, weight = const_94_to_fp16, x = input_761_cast_fp16)[name = tensor<string, []>("input_765_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_767_cast_fp16 = relu(x = input_765_cast_fp16)[name = tensor<string, []>("input_767_cast_fp16")];
            tensor<string, []> y_69_pad_type_0 = const()[name = tensor<string, []>("y_69_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_69_pad_0 = const()[name = tensor<string, []>("y_69_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_69_dilations_0 = const()[name = tensor<string, []>("y_69_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_69_strides_0 = const()[name = tensor<string, []>("y_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_69_groups_0 = const()[name = tensor<string, []>("y_69_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd23_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd23_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7076032)))];
            tensor<fp16, [1, 32, ?]> y_69_cast_fp16 = conv(dilations = y_69_dilations_0, groups = y_69_groups_0, pad = y_69_pad_0, pad_type = y_69_pad_type_0, strides = y_69_strides_0, weight = net_xvector_block2_tdnnd23_cam_layer_linear_local_weight_to_fp16, x = input_767_cast_fp16)[name = tensor<string, []>("y_69_cast_fp16")];
            tensor<int32, [1]> var_2662_axes_0 = const()[name = tensor<string, []>("op_2662_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2662_keep_dims_0 = const()[name = tensor<string, []>("op_2662_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2662_cast_fp16 = reduce_mean(axes = var_2662_axes_0, keep_dims = var_2662_keep_dims_0, x = input_767_cast_fp16)[name = tensor<string, []>("op_2662_cast_fp16")];
            tensor<int32, [1]> var_2663 = const()[name = tensor<string, []>("op_2663"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2664 = const()[name = tensor<string, []>("op_2664"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_137_pad_type_0 = const()[name = tensor<string, []>("seg_137_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_137_pad_0 = const()[name = tensor<string, []>("seg_137_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_137_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_137_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_137_ceil_mode_0 = const()[name = tensor<string, []>("seg_137_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_137_cast_fp16 = avg_pool(ceil_mode = seg_137_ceil_mode_0, exclude_padding_from_average = seg_137_exclude_padding_from_average_0, kernel_sizes = var_2663, pad = seg_137_pad_0, pad_type = seg_137_pad_type_0, strides = var_2664, x = input_767_cast_fp16)[name = tensor<string, []>("seg_137_cast_fp16")];
            tensor<int32, [3]> var_2667_shape_cast_fp16 = shape(x = seg_137_cast_fp16)[name = tensor<string, []>("op_2667_shape_cast_fp16")];
            tensor<int32, []> gather_140 = const()[name = tensor<string, []>("gather_140"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_141 = const()[name = tensor<string, []>("gather_141"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_142_axis_0 = const()[name = tensor<string, []>("gather_142_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_142_batch_dims_0 = const()[name = tensor<string, []>("gather_142_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_142_validate_indices_0 = const()[name = tensor<string, []>("gather_142_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2667_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2667_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_142_to_uint16 = const()[name = tensor<string, []>("select_142_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2667_shape_cast_fp16_to_uint16 = cast(dtype = var_2667_shape_cast_fp16_to_uint16_dtype_0, x = var_2667_shape_cast_fp16)[name = tensor<string, []>("cast_179")];
            tensor<uint16, []> gather_142_cast_uint16 = gather(axis = gather_142_axis_0, batch_dims = gather_142_batch_dims_0, indices = select_142_to_uint16, validate_indices = gather_142_validate_indices_0, x = var_2667_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_142_cast_uint16")];
            tensor<string, []> gather_142_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_142_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2670_axes_0 = const()[name = tensor<string, []>("op_2670_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2670_cast_fp16 = expand_dims(axes = var_2670_axes_0, x = seg_137_cast_fp16)[name = tensor<string, []>("op_2670_cast_fp16")];
            tensor<int32, []> concat_69_axis_0 = const()[name = tensor<string, []>("concat_69_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_69_interleave_0 = const()[name = tensor<string, []>("concat_69_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_142_cast_uint16_to_int32 = cast(dtype = gather_142_cast_uint16_to_int32_dtype_0, x = gather_142_cast_uint16)[name = tensor<string, []>("cast_178")];
            tensor<int32, [4]> concat_69 = concat(axis = concat_69_axis_0, interleave = concat_69_interleave_0, values = (gather_140, gather_141, gather_142_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_69")];
            tensor<int32, [4]> shape_177_cast_fp16 = shape(x = var_2670_cast_fp16)[name = tensor<string, []>("shape_177_cast_fp16")];
            tensor<int32, [4]> real_div_34 = real_div(x = concat_69, y = shape_177_cast_fp16)[name = tensor<string, []>("real_div_34")];
            tensor<fp16, [?, ?, ?, ?]> var_2672_cast_fp16 = tile(reps = real_div_34, x = var_2670_cast_fp16)[name = tensor<string, []>("op_2672_cast_fp16")];
            tensor<int32, [3]> var_2673 = const()[name = tensor<string, []>("op_2673"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_139_cast_fp16 = reshape(shape = var_2673, x = var_2672_cast_fp16)[name = tensor<string, []>("seg_139_cast_fp16")];
            tensor<int32, [3]> var_2675_shape_cast_fp16 = shape(x = input_767_cast_fp16)[name = tensor<string, []>("op_2675_shape_cast_fp16")];
            tensor<int32, []> gather_143_axis_0 = const()[name = tensor<string, []>("gather_143_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_143_batch_dims_0 = const()[name = tensor<string, []>("gather_143_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_143_validate_indices_0 = const()[name = tensor<string, []>("gather_143_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2675_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2675_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_143_to_uint16 = const()[name = tensor<string, []>("select_143_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2675_shape_cast_fp16_to_uint16 = cast(dtype = var_2675_shape_cast_fp16_to_uint16_dtype_0, x = var_2675_shape_cast_fp16)[name = tensor<string, []>("cast_177")];
            tensor<uint16, []> gather_143_cast_uint16 = gather(axis = gather_143_axis_0, batch_dims = gather_143_batch_dims_0, indices = select_143_to_uint16, validate_indices = gather_143_validate_indices_0, x = var_2675_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_143_cast_uint16")];
            tensor<string, []> gather_143_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_143_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_70_values0_0 = const()[name = tensor<string, []>("concat_70_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_70_values1_0 = const()[name = tensor<string, []>("concat_70_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_70_axis_0 = const()[name = tensor<string, []>("concat_70_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_70_interleave_0 = const()[name = tensor<string, []>("concat_70_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_143_cast_uint16_to_int32 = cast(dtype = gather_143_cast_uint16_to_int32_dtype_0, x = gather_143_cast_uint16)[name = tensor<string, []>("cast_176")];
            tensor<int32, [3]> concat_70 = concat(axis = concat_70_axis_0, interleave = concat_70_interleave_0, values = (concat_70_values0_0, concat_70_values1_0, gather_143_cast_uint16_to_int32))[name = tensor<string, []>("concat_70")];
            tensor<int32, [3]> var_2676_begin_0 = const()[name = tensor<string, []>("op_2676_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2676_end_mask_0 = const()[name = tensor<string, []>("op_2676_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2676_cast_fp16 = slice_by_index(begin = var_2676_begin_0, end = concat_70, end_mask = var_2676_end_mask_0, x = seg_139_cast_fp16)[name = tensor<string, []>("op_2676_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_769_cast_fp16 = add(x = var_2662_cast_fp16, y = var_2676_cast_fp16)[name = tensor<string, []>("input_769_cast_fp16")];
            tensor<string, []> input_771_pad_type_0 = const()[name = tensor<string, []>("input_771_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_771_strides_0 = const()[name = tensor<string, []>("input_771_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_771_pad_0 = const()[name = tensor<string, []>("input_771_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_771_dilations_0 = const()[name = tensor<string, []>("input_771_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_771_groups_0 = const()[name = tensor<string, []>("input_771_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd23_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd23_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7100672)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd23_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd23_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7117120)))];
            tensor<fp16, [1, 64, ?]> input_771_cast_fp16 = conv(bias = net_xvector_block2_tdnnd23_cam_layer_linear1_bias_to_fp16, dilations = input_771_dilations_0, groups = input_771_groups_0, pad = input_771_pad_0, pad_type = input_771_pad_type_0, strides = input_771_strides_0, weight = net_xvector_block2_tdnnd23_cam_layer_linear1_weight_to_fp16, x = input_769_cast_fp16)[name = tensor<string, []>("input_771_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_773_cast_fp16 = relu(x = input_771_cast_fp16)[name = tensor<string, []>("input_773_cast_fp16")];
            tensor<string, []> input_775_pad_type_0 = const()[name = tensor<string, []>("input_775_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_775_strides_0 = const()[name = tensor<string, []>("input_775_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_775_pad_0 = const()[name = tensor<string, []>("input_775_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_775_dilations_0 = const()[name = tensor<string, []>("input_775_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_775_groups_0 = const()[name = tensor<string, []>("input_775_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd23_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd23_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7117312)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd23_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd23_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7121472)))];
            tensor<fp16, [1, 32, ?]> input_775_cast_fp16 = conv(bias = net_xvector_block2_tdnnd23_cam_layer_linear2_bias_to_fp16, dilations = input_775_dilations_0, groups = input_775_groups_0, pad = input_775_pad_0, pad_type = input_775_pad_type_0, strides = input_775_strides_0, weight = net_xvector_block2_tdnnd23_cam_layer_linear2_weight_to_fp16, x = input_773_cast_fp16)[name = tensor<string, []>("input_775_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_69_cast_fp16 = sigmoid(x = input_775_cast_fp16)[name = tensor<string, []>("m_69_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2694_cast_fp16 = mul(x = y_69_cast_fp16, y = m_69_cast_fp16)[name = tensor<string, []>("op_2694_cast_fp16")];
            tensor<bool, []> input_777_interleave_0 = const()[name = tensor<string, []>("input_777_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 992, ?]> input_777_cast_fp16 = concat(axis = var_11, interleave = input_777_interleave_0, values = (input_757_cast_fp16, var_2694_cast_fp16))[name = tensor<string, []>("input_777_cast_fp16")];
            tensor<fp16, [992]> net_xvector_block2_tdnnd24_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd24_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [992]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7121600)))];
            tensor<fp16, [992]> net_xvector_block2_tdnnd24_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd24_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [992]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7123648)))];
            tensor<fp16, [992]> net_xvector_block2_tdnnd24_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd24_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [992]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7125696)))];
            tensor<fp16, [992]> net_xvector_block2_tdnnd24_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd24_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [992]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7127744)))];
            tensor<fp16, [1, 992, ?]> input_779_cast_fp16 = batch_norm(beta = net_xvector_block2_tdnnd24_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block2_tdnnd24_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block2_tdnnd24_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block2_tdnnd24_nonlinear1_batchnorm_running_var_to_fp16, x = input_777_cast_fp16)[name = tensor<string, []>("input_779_cast_fp16")];
            tensor<fp16, [1, 992, ?]> input_781_cast_fp16 = relu(x = input_779_cast_fp16)[name = tensor<string, []>("input_781_cast_fp16")];
            tensor<string, []> input_783_pad_type_0 = const()[name = tensor<string, []>("input_783_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_783_strides_0 = const()[name = tensor<string, []>("input_783_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_783_pad_0 = const()[name = tensor<string, []>("input_783_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_783_dilations_0 = const()[name = tensor<string, []>("input_783_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_783_groups_0 = const()[name = tensor<string, []>("input_783_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 992, 1]> const_96_to_fp16 = const()[name = tensor<string, []>("const_96_to_fp16"), val = tensor<fp16, [128, 992, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7129792)))];
            tensor<fp16, [128]> const_97_to_fp16 = const()[name = tensor<string, []>("const_97_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7383808)))];
            tensor<fp16, [1, 128, ?]> input_785_cast_fp16 = conv(bias = const_97_to_fp16, dilations = input_783_dilations_0, groups = input_783_groups_0, pad = input_783_pad_0, pad_type = input_783_pad_type_0, strides = input_783_strides_0, weight = const_96_to_fp16, x = input_781_cast_fp16)[name = tensor<string, []>("input_785_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_787_cast_fp16 = relu(x = input_785_cast_fp16)[name = tensor<string, []>("input_787_cast_fp16")];
            tensor<string, []> y_71_pad_type_0 = const()[name = tensor<string, []>("y_71_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_71_pad_0 = const()[name = tensor<string, []>("y_71_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_71_dilations_0 = const()[name = tensor<string, []>("y_71_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_71_strides_0 = const()[name = tensor<string, []>("y_71_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_71_groups_0 = const()[name = tensor<string, []>("y_71_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block2_tdnnd24_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd24_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7384128)))];
            tensor<fp16, [1, 32, ?]> y_71_cast_fp16 = conv(dilations = y_71_dilations_0, groups = y_71_groups_0, pad = y_71_pad_0, pad_type = y_71_pad_type_0, strides = y_71_strides_0, weight = net_xvector_block2_tdnnd24_cam_layer_linear_local_weight_to_fp16, x = input_787_cast_fp16)[name = tensor<string, []>("y_71_cast_fp16")];
            tensor<int32, [1]> var_2731_axes_0 = const()[name = tensor<string, []>("op_2731_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2731_keep_dims_0 = const()[name = tensor<string, []>("op_2731_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2731_cast_fp16 = reduce_mean(axes = var_2731_axes_0, keep_dims = var_2731_keep_dims_0, x = input_787_cast_fp16)[name = tensor<string, []>("op_2731_cast_fp16")];
            tensor<int32, [1]> var_2732 = const()[name = tensor<string, []>("op_2732"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2733 = const()[name = tensor<string, []>("op_2733"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_141_pad_type_0 = const()[name = tensor<string, []>("seg_141_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_141_pad_0 = const()[name = tensor<string, []>("seg_141_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_141_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_141_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_141_ceil_mode_0 = const()[name = tensor<string, []>("seg_141_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_141_cast_fp16 = avg_pool(ceil_mode = seg_141_ceil_mode_0, exclude_padding_from_average = seg_141_exclude_padding_from_average_0, kernel_sizes = var_2732, pad = seg_141_pad_0, pad_type = seg_141_pad_type_0, strides = var_2733, x = input_787_cast_fp16)[name = tensor<string, []>("seg_141_cast_fp16")];
            tensor<int32, [3]> var_2736_shape_cast_fp16 = shape(x = seg_141_cast_fp16)[name = tensor<string, []>("op_2736_shape_cast_fp16")];
            tensor<int32, []> gather_144 = const()[name = tensor<string, []>("gather_144"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_145 = const()[name = tensor<string, []>("gather_145"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_146_axis_0 = const()[name = tensor<string, []>("gather_146_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_146_batch_dims_0 = const()[name = tensor<string, []>("gather_146_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_146_validate_indices_0 = const()[name = tensor<string, []>("gather_146_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2736_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2736_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_146_to_uint16 = const()[name = tensor<string, []>("select_146_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2736_shape_cast_fp16_to_uint16 = cast(dtype = var_2736_shape_cast_fp16_to_uint16_dtype_0, x = var_2736_shape_cast_fp16)[name = tensor<string, []>("cast_175")];
            tensor<uint16, []> gather_146_cast_uint16 = gather(axis = gather_146_axis_0, batch_dims = gather_146_batch_dims_0, indices = select_146_to_uint16, validate_indices = gather_146_validate_indices_0, x = var_2736_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_146_cast_uint16")];
            tensor<string, []> gather_146_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_146_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2739_axes_0 = const()[name = tensor<string, []>("op_2739_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2739_cast_fp16 = expand_dims(axes = var_2739_axes_0, x = seg_141_cast_fp16)[name = tensor<string, []>("op_2739_cast_fp16")];
            tensor<int32, []> concat_71_axis_0 = const()[name = tensor<string, []>("concat_71_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_71_interleave_0 = const()[name = tensor<string, []>("concat_71_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_146_cast_uint16_to_int32 = cast(dtype = gather_146_cast_uint16_to_int32_dtype_0, x = gather_146_cast_uint16)[name = tensor<string, []>("cast_174")];
            tensor<int32, [4]> concat_71 = concat(axis = concat_71_axis_0, interleave = concat_71_interleave_0, values = (gather_144, gather_145, gather_146_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_71")];
            tensor<int32, [4]> shape_182_cast_fp16 = shape(x = var_2739_cast_fp16)[name = tensor<string, []>("shape_182_cast_fp16")];
            tensor<int32, [4]> real_div_35 = real_div(x = concat_71, y = shape_182_cast_fp16)[name = tensor<string, []>("real_div_35")];
            tensor<fp16, [?, ?, ?, ?]> var_2741_cast_fp16 = tile(reps = real_div_35, x = var_2739_cast_fp16)[name = tensor<string, []>("op_2741_cast_fp16")];
            tensor<int32, [3]> var_2742 = const()[name = tensor<string, []>("op_2742"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_143_cast_fp16 = reshape(shape = var_2742, x = var_2741_cast_fp16)[name = tensor<string, []>("seg_143_cast_fp16")];
            tensor<int32, [3]> var_2744_shape_cast_fp16 = shape(x = input_787_cast_fp16)[name = tensor<string, []>("op_2744_shape_cast_fp16")];
            tensor<int32, []> gather_147_axis_0 = const()[name = tensor<string, []>("gather_147_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_147_batch_dims_0 = const()[name = tensor<string, []>("gather_147_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_147_validate_indices_0 = const()[name = tensor<string, []>("gather_147_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2744_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2744_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_147_to_uint16 = const()[name = tensor<string, []>("select_147_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2744_shape_cast_fp16_to_uint16 = cast(dtype = var_2744_shape_cast_fp16_to_uint16_dtype_0, x = var_2744_shape_cast_fp16)[name = tensor<string, []>("cast_173")];
            tensor<uint16, []> gather_147_cast_uint16 = gather(axis = gather_147_axis_0, batch_dims = gather_147_batch_dims_0, indices = select_147_to_uint16, validate_indices = gather_147_validate_indices_0, x = var_2744_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_147_cast_uint16")];
            tensor<string, []> gather_147_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_147_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_72_values0_0 = const()[name = tensor<string, []>("concat_72_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_72_values1_0 = const()[name = tensor<string, []>("concat_72_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_72_axis_0 = const()[name = tensor<string, []>("concat_72_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_72_interleave_0 = const()[name = tensor<string, []>("concat_72_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_147_cast_uint16_to_int32 = cast(dtype = gather_147_cast_uint16_to_int32_dtype_0, x = gather_147_cast_uint16)[name = tensor<string, []>("cast_172")];
            tensor<int32, [3]> concat_72 = concat(axis = concat_72_axis_0, interleave = concat_72_interleave_0, values = (concat_72_values0_0, concat_72_values1_0, gather_147_cast_uint16_to_int32))[name = tensor<string, []>("concat_72")];
            tensor<int32, [3]> var_2745_begin_0 = const()[name = tensor<string, []>("op_2745_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2745_end_mask_0 = const()[name = tensor<string, []>("op_2745_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2745_cast_fp16 = slice_by_index(begin = var_2745_begin_0, end = concat_72, end_mask = var_2745_end_mask_0, x = seg_143_cast_fp16)[name = tensor<string, []>("op_2745_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_789_cast_fp16 = add(x = var_2731_cast_fp16, y = var_2745_cast_fp16)[name = tensor<string, []>("input_789_cast_fp16")];
            tensor<string, []> input_791_pad_type_0 = const()[name = tensor<string, []>("input_791_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_791_strides_0 = const()[name = tensor<string, []>("input_791_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_791_pad_0 = const()[name = tensor<string, []>("input_791_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_791_dilations_0 = const()[name = tensor<string, []>("input_791_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_791_groups_0 = const()[name = tensor<string, []>("input_791_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block2_tdnnd24_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd24_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7408768)))];
            tensor<fp16, [64]> net_xvector_block2_tdnnd24_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd24_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7425216)))];
            tensor<fp16, [1, 64, ?]> input_791_cast_fp16 = conv(bias = net_xvector_block2_tdnnd24_cam_layer_linear1_bias_to_fp16, dilations = input_791_dilations_0, groups = input_791_groups_0, pad = input_791_pad_0, pad_type = input_791_pad_type_0, strides = input_791_strides_0, weight = net_xvector_block2_tdnnd24_cam_layer_linear1_weight_to_fp16, x = input_789_cast_fp16)[name = tensor<string, []>("input_791_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_793_cast_fp16 = relu(x = input_791_cast_fp16)[name = tensor<string, []>("input_793_cast_fp16")];
            tensor<string, []> input_795_pad_type_0 = const()[name = tensor<string, []>("input_795_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_795_strides_0 = const()[name = tensor<string, []>("input_795_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_795_pad_0 = const()[name = tensor<string, []>("input_795_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_795_dilations_0 = const()[name = tensor<string, []>("input_795_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_795_groups_0 = const()[name = tensor<string, []>("input_795_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block2_tdnnd24_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd24_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7425408)))];
            tensor<fp16, [32]> net_xvector_block2_tdnnd24_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block2_tdnnd24_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7429568)))];
            tensor<fp16, [1, 32, ?]> input_795_cast_fp16 = conv(bias = net_xvector_block2_tdnnd24_cam_layer_linear2_bias_to_fp16, dilations = input_795_dilations_0, groups = input_795_groups_0, pad = input_795_pad_0, pad_type = input_795_pad_type_0, strides = input_795_strides_0, weight = net_xvector_block2_tdnnd24_cam_layer_linear2_weight_to_fp16, x = input_793_cast_fp16)[name = tensor<string, []>("input_795_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_71_cast_fp16 = sigmoid(x = input_795_cast_fp16)[name = tensor<string, []>("m_71_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2763_cast_fp16 = mul(x = y_71_cast_fp16, y = m_71_cast_fp16)[name = tensor<string, []>("op_2763_cast_fp16")];
            tensor<bool, []> input_797_interleave_0 = const()[name = tensor<string, []>("input_797_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 1024, ?]> input_797_cast_fp16 = concat(axis = var_11, interleave = input_797_interleave_0, values = (input_777_cast_fp16, var_2763_cast_fp16))[name = tensor<string, []>("input_797_cast_fp16")];
            tensor<fp16, [1024]> net_xvector_transit2_nonlinear_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit2_nonlinear_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7429696)))];
            tensor<fp16, [1024]> net_xvector_transit2_nonlinear_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit2_nonlinear_batchnorm_running_var_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7431808)))];
            tensor<fp16, [1024]> net_xvector_transit2_nonlinear_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit2_nonlinear_batchnorm_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7433920)))];
            tensor<fp16, [1024]> net_xvector_transit2_nonlinear_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit2_nonlinear_batchnorm_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7436032)))];
            tensor<fp16, [1, 1024, ?]> input_799_cast_fp16 = batch_norm(beta = net_xvector_transit2_nonlinear_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_transit2_nonlinear_batchnorm_weight_to_fp16, mean = net_xvector_transit2_nonlinear_batchnorm_running_mean_to_fp16, variance = net_xvector_transit2_nonlinear_batchnorm_running_var_to_fp16, x = input_797_cast_fp16)[name = tensor<string, []>("input_799_cast_fp16")];
            tensor<fp16, [1, 1024, ?]> input_801_cast_fp16 = relu(x = input_799_cast_fp16)[name = tensor<string, []>("input_801_cast_fp16")];
            tensor<string, []> input_803_pad_type_0 = const()[name = tensor<string, []>("input_803_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_803_strides_0 = const()[name = tensor<string, []>("input_803_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_803_pad_0 = const()[name = tensor<string, []>("input_803_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_803_dilations_0 = const()[name = tensor<string, []>("input_803_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_803_groups_0 = const()[name = tensor<string, []>("input_803_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 1024, 1]> net_xvector_transit2_linear_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit2_linear_weight_to_fp16"), val = tensor<fp16, [512, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7438144)))];
            tensor<fp16, [1, 512, ?]> input_803_cast_fp16 = conv(dilations = input_803_dilations_0, groups = input_803_groups_0, pad = input_803_pad_0, pad_type = input_803_pad_type_0, strides = input_803_strides_0, weight = net_xvector_transit2_linear_weight_to_fp16, x = input_801_cast_fp16)[name = tensor<string, []>("input_803_cast_fp16")];
            tensor<fp16, [512]> net_xvector_block3_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8486784)))];
            tensor<fp16, [512]> net_xvector_block3_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8487872)))];
            tensor<fp16, [512]> net_xvector_block3_tdnnd1_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd1_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8488960)))];
            tensor<fp16, [512]> net_xvector_block3_tdnnd1_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd1_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8490048)))];
            tensor<fp16, [1, 512, ?]> input_805_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd1_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd1_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16, x = input_803_cast_fp16)[name = tensor<string, []>("input_805_cast_fp16")];
            tensor<fp16, [1, 512, ?]> input_807_cast_fp16 = relu(x = input_805_cast_fp16)[name = tensor<string, []>("input_807_cast_fp16")];
            tensor<string, []> input_809_pad_type_0 = const()[name = tensor<string, []>("input_809_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_809_strides_0 = const()[name = tensor<string, []>("input_809_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_809_pad_0 = const()[name = tensor<string, []>("input_809_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_809_dilations_0 = const()[name = tensor<string, []>("input_809_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_809_groups_0 = const()[name = tensor<string, []>("input_809_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 512, 1]> const_98_to_fp16 = const()[name = tensor<string, []>("const_98_to_fp16"), val = tensor<fp16, [128, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8491136)))];
            tensor<fp16, [128]> const_99_to_fp16 = const()[name = tensor<string, []>("const_99_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8622272)))];
            tensor<fp16, [1, 128, ?]> input_811_cast_fp16 = conv(bias = const_99_to_fp16, dilations = input_809_dilations_0, groups = input_809_groups_0, pad = input_809_pad_0, pad_type = input_809_pad_type_0, strides = input_809_strides_0, weight = const_98_to_fp16, x = input_807_cast_fp16)[name = tensor<string, []>("input_811_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_813_cast_fp16 = relu(x = input_811_cast_fp16)[name = tensor<string, []>("input_813_cast_fp16")];
            tensor<string, []> y_73_pad_type_0 = const()[name = tensor<string, []>("y_73_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_73_pad_0 = const()[name = tensor<string, []>("y_73_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_73_dilations_0 = const()[name = tensor<string, []>("y_73_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_73_strides_0 = const()[name = tensor<string, []>("y_73_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_73_groups_0 = const()[name = tensor<string, []>("y_73_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd1_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd1_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8622592)))];
            tensor<fp16, [1, 32, ?]> y_73_cast_fp16 = conv(dilations = y_73_dilations_0, groups = y_73_groups_0, pad = y_73_pad_0, pad_type = y_73_pad_type_0, strides = y_73_strides_0, weight = net_xvector_block3_tdnnd1_cam_layer_linear_local_weight_to_fp16, x = input_813_cast_fp16)[name = tensor<string, []>("y_73_cast_fp16")];
            tensor<int32, [1]> var_2831_axes_0 = const()[name = tensor<string, []>("op_2831_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2831_keep_dims_0 = const()[name = tensor<string, []>("op_2831_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2831_cast_fp16 = reduce_mean(axes = var_2831_axes_0, keep_dims = var_2831_keep_dims_0, x = input_813_cast_fp16)[name = tensor<string, []>("op_2831_cast_fp16")];
            tensor<int32, [1]> var_2832 = const()[name = tensor<string, []>("op_2832"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2833 = const()[name = tensor<string, []>("op_2833"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_145_pad_type_0 = const()[name = tensor<string, []>("seg_145_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_145_pad_0 = const()[name = tensor<string, []>("seg_145_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_145_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_145_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_145_ceil_mode_0 = const()[name = tensor<string, []>("seg_145_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_145_cast_fp16 = avg_pool(ceil_mode = seg_145_ceil_mode_0, exclude_padding_from_average = seg_145_exclude_padding_from_average_0, kernel_sizes = var_2832, pad = seg_145_pad_0, pad_type = seg_145_pad_type_0, strides = var_2833, x = input_813_cast_fp16)[name = tensor<string, []>("seg_145_cast_fp16")];
            tensor<int32, [3]> var_2836_shape_cast_fp16 = shape(x = seg_145_cast_fp16)[name = tensor<string, []>("op_2836_shape_cast_fp16")];
            tensor<int32, []> gather_148 = const()[name = tensor<string, []>("gather_148"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_149 = const()[name = tensor<string, []>("gather_149"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_150_axis_0 = const()[name = tensor<string, []>("gather_150_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_150_batch_dims_0 = const()[name = tensor<string, []>("gather_150_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_150_validate_indices_0 = const()[name = tensor<string, []>("gather_150_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2836_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2836_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_150_to_uint16 = const()[name = tensor<string, []>("select_150_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2836_shape_cast_fp16_to_uint16 = cast(dtype = var_2836_shape_cast_fp16_to_uint16_dtype_0, x = var_2836_shape_cast_fp16)[name = tensor<string, []>("cast_171")];
            tensor<uint16, []> gather_150_cast_uint16 = gather(axis = gather_150_axis_0, batch_dims = gather_150_batch_dims_0, indices = select_150_to_uint16, validate_indices = gather_150_validate_indices_0, x = var_2836_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_150_cast_uint16")];
            tensor<string, []> gather_150_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_150_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2839_axes_0 = const()[name = tensor<string, []>("op_2839_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2839_cast_fp16 = expand_dims(axes = var_2839_axes_0, x = seg_145_cast_fp16)[name = tensor<string, []>("op_2839_cast_fp16")];
            tensor<int32, []> concat_73_axis_0 = const()[name = tensor<string, []>("concat_73_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_73_interleave_0 = const()[name = tensor<string, []>("concat_73_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_150_cast_uint16_to_int32 = cast(dtype = gather_150_cast_uint16_to_int32_dtype_0, x = gather_150_cast_uint16)[name = tensor<string, []>("cast_170")];
            tensor<int32, [4]> concat_73 = concat(axis = concat_73_axis_0, interleave = concat_73_interleave_0, values = (gather_148, gather_149, gather_150_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_73")];
            tensor<int32, [4]> shape_187_cast_fp16 = shape(x = var_2839_cast_fp16)[name = tensor<string, []>("shape_187_cast_fp16")];
            tensor<int32, [4]> real_div_36 = real_div(x = concat_73, y = shape_187_cast_fp16)[name = tensor<string, []>("real_div_36")];
            tensor<fp16, [?, ?, ?, ?]> var_2841_cast_fp16 = tile(reps = real_div_36, x = var_2839_cast_fp16)[name = tensor<string, []>("op_2841_cast_fp16")];
            tensor<int32, [3]> var_2842 = const()[name = tensor<string, []>("op_2842"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_147_cast_fp16 = reshape(shape = var_2842, x = var_2841_cast_fp16)[name = tensor<string, []>("seg_147_cast_fp16")];
            tensor<int32, [3]> var_2844_shape_cast_fp16 = shape(x = input_813_cast_fp16)[name = tensor<string, []>("op_2844_shape_cast_fp16")];
            tensor<int32, []> gather_151_axis_0 = const()[name = tensor<string, []>("gather_151_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_151_batch_dims_0 = const()[name = tensor<string, []>("gather_151_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_151_validate_indices_0 = const()[name = tensor<string, []>("gather_151_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2844_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2844_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_151_to_uint16 = const()[name = tensor<string, []>("select_151_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2844_shape_cast_fp16_to_uint16 = cast(dtype = var_2844_shape_cast_fp16_to_uint16_dtype_0, x = var_2844_shape_cast_fp16)[name = tensor<string, []>("cast_169")];
            tensor<uint16, []> gather_151_cast_uint16 = gather(axis = gather_151_axis_0, batch_dims = gather_151_batch_dims_0, indices = select_151_to_uint16, validate_indices = gather_151_validate_indices_0, x = var_2844_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_151_cast_uint16")];
            tensor<string, []> gather_151_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_151_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_74_values0_0 = const()[name = tensor<string, []>("concat_74_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_74_values1_0 = const()[name = tensor<string, []>("concat_74_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_74_axis_0 = const()[name = tensor<string, []>("concat_74_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_74_interleave_0 = const()[name = tensor<string, []>("concat_74_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_151_cast_uint16_to_int32 = cast(dtype = gather_151_cast_uint16_to_int32_dtype_0, x = gather_151_cast_uint16)[name = tensor<string, []>("cast_168")];
            tensor<int32, [3]> concat_74 = concat(axis = concat_74_axis_0, interleave = concat_74_interleave_0, values = (concat_74_values0_0, concat_74_values1_0, gather_151_cast_uint16_to_int32))[name = tensor<string, []>("concat_74")];
            tensor<int32, [3]> var_2845_begin_0 = const()[name = tensor<string, []>("op_2845_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2845_end_mask_0 = const()[name = tensor<string, []>("op_2845_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2845_cast_fp16 = slice_by_index(begin = var_2845_begin_0, end = concat_74, end_mask = var_2845_end_mask_0, x = seg_147_cast_fp16)[name = tensor<string, []>("op_2845_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_815_cast_fp16 = add(x = var_2831_cast_fp16, y = var_2845_cast_fp16)[name = tensor<string, []>("input_815_cast_fp16")];
            tensor<string, []> input_817_pad_type_0 = const()[name = tensor<string, []>("input_817_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_817_strides_0 = const()[name = tensor<string, []>("input_817_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_817_pad_0 = const()[name = tensor<string, []>("input_817_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_817_dilations_0 = const()[name = tensor<string, []>("input_817_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_817_groups_0 = const()[name = tensor<string, []>("input_817_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd1_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd1_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8647232)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd1_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd1_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8663680)))];
            tensor<fp16, [1, 64, ?]> input_817_cast_fp16 = conv(bias = net_xvector_block3_tdnnd1_cam_layer_linear1_bias_to_fp16, dilations = input_817_dilations_0, groups = input_817_groups_0, pad = input_817_pad_0, pad_type = input_817_pad_type_0, strides = input_817_strides_0, weight = net_xvector_block3_tdnnd1_cam_layer_linear1_weight_to_fp16, x = input_815_cast_fp16)[name = tensor<string, []>("input_817_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_819_cast_fp16 = relu(x = input_817_cast_fp16)[name = tensor<string, []>("input_819_cast_fp16")];
            tensor<string, []> input_821_pad_type_0 = const()[name = tensor<string, []>("input_821_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_821_strides_0 = const()[name = tensor<string, []>("input_821_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_821_pad_0 = const()[name = tensor<string, []>("input_821_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_821_dilations_0 = const()[name = tensor<string, []>("input_821_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_821_groups_0 = const()[name = tensor<string, []>("input_821_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd1_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd1_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8663872)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd1_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd1_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8668032)))];
            tensor<fp16, [1, 32, ?]> input_821_cast_fp16 = conv(bias = net_xvector_block3_tdnnd1_cam_layer_linear2_bias_to_fp16, dilations = input_821_dilations_0, groups = input_821_groups_0, pad = input_821_pad_0, pad_type = input_821_pad_type_0, strides = input_821_strides_0, weight = net_xvector_block3_tdnnd1_cam_layer_linear2_weight_to_fp16, x = input_819_cast_fp16)[name = tensor<string, []>("input_821_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_73_cast_fp16 = sigmoid(x = input_821_cast_fp16)[name = tensor<string, []>("m_73_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2863_cast_fp16 = mul(x = y_73_cast_fp16, y = m_73_cast_fp16)[name = tensor<string, []>("op_2863_cast_fp16")];
            tensor<bool, []> input_823_interleave_0 = const()[name = tensor<string, []>("input_823_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 544, ?]> input_823_cast_fp16 = concat(axis = var_11, interleave = input_823_interleave_0, values = (input_803_cast_fp16, var_2863_cast_fp16))[name = tensor<string, []>("input_823_cast_fp16")];
            tensor<fp16, [544]> net_xvector_block3_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [544]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8668160)))];
            tensor<fp16, [544]> net_xvector_block3_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [544]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8669312)))];
            tensor<fp16, [544]> net_xvector_block3_tdnnd2_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd2_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [544]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8670464)))];
            tensor<fp16, [544]> net_xvector_block3_tdnnd2_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd2_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [544]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8671616)))];
            tensor<fp16, [1, 544, ?]> input_825_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd2_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd2_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16, x = input_823_cast_fp16)[name = tensor<string, []>("input_825_cast_fp16")];
            tensor<fp16, [1, 544, ?]> input_827_cast_fp16 = relu(x = input_825_cast_fp16)[name = tensor<string, []>("input_827_cast_fp16")];
            tensor<string, []> input_829_pad_type_0 = const()[name = tensor<string, []>("input_829_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_829_strides_0 = const()[name = tensor<string, []>("input_829_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_829_pad_0 = const()[name = tensor<string, []>("input_829_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_829_dilations_0 = const()[name = tensor<string, []>("input_829_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_829_groups_0 = const()[name = tensor<string, []>("input_829_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 544, 1]> const_100_to_fp16 = const()[name = tensor<string, []>("const_100_to_fp16"), val = tensor<fp16, [128, 544, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8672768)))];
            tensor<fp16, [128]> const_101_to_fp16 = const()[name = tensor<string, []>("const_101_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8812096)))];
            tensor<fp16, [1, 128, ?]> input_831_cast_fp16 = conv(bias = const_101_to_fp16, dilations = input_829_dilations_0, groups = input_829_groups_0, pad = input_829_pad_0, pad_type = input_829_pad_type_0, strides = input_829_strides_0, weight = const_100_to_fp16, x = input_827_cast_fp16)[name = tensor<string, []>("input_831_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_833_cast_fp16 = relu(x = input_831_cast_fp16)[name = tensor<string, []>("input_833_cast_fp16")];
            tensor<string, []> y_75_pad_type_0 = const()[name = tensor<string, []>("y_75_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_75_pad_0 = const()[name = tensor<string, []>("y_75_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_75_dilations_0 = const()[name = tensor<string, []>("y_75_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_75_strides_0 = const()[name = tensor<string, []>("y_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_75_groups_0 = const()[name = tensor<string, []>("y_75_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd2_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd2_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8812416)))];
            tensor<fp16, [1, 32, ?]> y_75_cast_fp16 = conv(dilations = y_75_dilations_0, groups = y_75_groups_0, pad = y_75_pad_0, pad_type = y_75_pad_type_0, strides = y_75_strides_0, weight = net_xvector_block3_tdnnd2_cam_layer_linear_local_weight_to_fp16, x = input_833_cast_fp16)[name = tensor<string, []>("y_75_cast_fp16")];
            tensor<int32, [1]> var_2900_axes_0 = const()[name = tensor<string, []>("op_2900_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2900_keep_dims_0 = const()[name = tensor<string, []>("op_2900_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2900_cast_fp16 = reduce_mean(axes = var_2900_axes_0, keep_dims = var_2900_keep_dims_0, x = input_833_cast_fp16)[name = tensor<string, []>("op_2900_cast_fp16")];
            tensor<int32, [1]> var_2901 = const()[name = tensor<string, []>("op_2901"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2902 = const()[name = tensor<string, []>("op_2902"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_149_pad_type_0 = const()[name = tensor<string, []>("seg_149_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_149_pad_0 = const()[name = tensor<string, []>("seg_149_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_149_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_149_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_149_ceil_mode_0 = const()[name = tensor<string, []>("seg_149_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_149_cast_fp16 = avg_pool(ceil_mode = seg_149_ceil_mode_0, exclude_padding_from_average = seg_149_exclude_padding_from_average_0, kernel_sizes = var_2901, pad = seg_149_pad_0, pad_type = seg_149_pad_type_0, strides = var_2902, x = input_833_cast_fp16)[name = tensor<string, []>("seg_149_cast_fp16")];
            tensor<int32, [3]> var_2905_shape_cast_fp16 = shape(x = seg_149_cast_fp16)[name = tensor<string, []>("op_2905_shape_cast_fp16")];
            tensor<int32, []> gather_152 = const()[name = tensor<string, []>("gather_152"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_153 = const()[name = tensor<string, []>("gather_153"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_154_axis_0 = const()[name = tensor<string, []>("gather_154_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_154_batch_dims_0 = const()[name = tensor<string, []>("gather_154_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_154_validate_indices_0 = const()[name = tensor<string, []>("gather_154_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2905_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2905_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_154_to_uint16 = const()[name = tensor<string, []>("select_154_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2905_shape_cast_fp16_to_uint16 = cast(dtype = var_2905_shape_cast_fp16_to_uint16_dtype_0, x = var_2905_shape_cast_fp16)[name = tensor<string, []>("cast_167")];
            tensor<uint16, []> gather_154_cast_uint16 = gather(axis = gather_154_axis_0, batch_dims = gather_154_batch_dims_0, indices = select_154_to_uint16, validate_indices = gather_154_validate_indices_0, x = var_2905_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_154_cast_uint16")];
            tensor<string, []> gather_154_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_154_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2908_axes_0 = const()[name = tensor<string, []>("op_2908_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2908_cast_fp16 = expand_dims(axes = var_2908_axes_0, x = seg_149_cast_fp16)[name = tensor<string, []>("op_2908_cast_fp16")];
            tensor<int32, []> concat_75_axis_0 = const()[name = tensor<string, []>("concat_75_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_75_interleave_0 = const()[name = tensor<string, []>("concat_75_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_154_cast_uint16_to_int32 = cast(dtype = gather_154_cast_uint16_to_int32_dtype_0, x = gather_154_cast_uint16)[name = tensor<string, []>("cast_166")];
            tensor<int32, [4]> concat_75 = concat(axis = concat_75_axis_0, interleave = concat_75_interleave_0, values = (gather_152, gather_153, gather_154_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_75")];
            tensor<int32, [4]> shape_192_cast_fp16 = shape(x = var_2908_cast_fp16)[name = tensor<string, []>("shape_192_cast_fp16")];
            tensor<int32, [4]> real_div_37 = real_div(x = concat_75, y = shape_192_cast_fp16)[name = tensor<string, []>("real_div_37")];
            tensor<fp16, [?, ?, ?, ?]> var_2910_cast_fp16 = tile(reps = real_div_37, x = var_2908_cast_fp16)[name = tensor<string, []>("op_2910_cast_fp16")];
            tensor<int32, [3]> var_2911 = const()[name = tensor<string, []>("op_2911"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_151_cast_fp16 = reshape(shape = var_2911, x = var_2910_cast_fp16)[name = tensor<string, []>("seg_151_cast_fp16")];
            tensor<int32, [3]> var_2913_shape_cast_fp16 = shape(x = input_833_cast_fp16)[name = tensor<string, []>("op_2913_shape_cast_fp16")];
            tensor<int32, []> gather_155_axis_0 = const()[name = tensor<string, []>("gather_155_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_155_batch_dims_0 = const()[name = tensor<string, []>("gather_155_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_155_validate_indices_0 = const()[name = tensor<string, []>("gather_155_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2913_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2913_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_155_to_uint16 = const()[name = tensor<string, []>("select_155_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2913_shape_cast_fp16_to_uint16 = cast(dtype = var_2913_shape_cast_fp16_to_uint16_dtype_0, x = var_2913_shape_cast_fp16)[name = tensor<string, []>("cast_165")];
            tensor<uint16, []> gather_155_cast_uint16 = gather(axis = gather_155_axis_0, batch_dims = gather_155_batch_dims_0, indices = select_155_to_uint16, validate_indices = gather_155_validate_indices_0, x = var_2913_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_155_cast_uint16")];
            tensor<string, []> gather_155_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_155_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_76_values0_0 = const()[name = tensor<string, []>("concat_76_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_76_values1_0 = const()[name = tensor<string, []>("concat_76_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_76_axis_0 = const()[name = tensor<string, []>("concat_76_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_76_interleave_0 = const()[name = tensor<string, []>("concat_76_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_155_cast_uint16_to_int32 = cast(dtype = gather_155_cast_uint16_to_int32_dtype_0, x = gather_155_cast_uint16)[name = tensor<string, []>("cast_164")];
            tensor<int32, [3]> concat_76 = concat(axis = concat_76_axis_0, interleave = concat_76_interleave_0, values = (concat_76_values0_0, concat_76_values1_0, gather_155_cast_uint16_to_int32))[name = tensor<string, []>("concat_76")];
            tensor<int32, [3]> var_2914_begin_0 = const()[name = tensor<string, []>("op_2914_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2914_end_mask_0 = const()[name = tensor<string, []>("op_2914_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2914_cast_fp16 = slice_by_index(begin = var_2914_begin_0, end = concat_76, end_mask = var_2914_end_mask_0, x = seg_151_cast_fp16)[name = tensor<string, []>("op_2914_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_835_cast_fp16 = add(x = var_2900_cast_fp16, y = var_2914_cast_fp16)[name = tensor<string, []>("input_835_cast_fp16")];
            tensor<string, []> input_837_pad_type_0 = const()[name = tensor<string, []>("input_837_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_837_strides_0 = const()[name = tensor<string, []>("input_837_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_837_pad_0 = const()[name = tensor<string, []>("input_837_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_837_dilations_0 = const()[name = tensor<string, []>("input_837_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_837_groups_0 = const()[name = tensor<string, []>("input_837_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd2_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd2_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8837056)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd2_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd2_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8853504)))];
            tensor<fp16, [1, 64, ?]> input_837_cast_fp16 = conv(bias = net_xvector_block3_tdnnd2_cam_layer_linear1_bias_to_fp16, dilations = input_837_dilations_0, groups = input_837_groups_0, pad = input_837_pad_0, pad_type = input_837_pad_type_0, strides = input_837_strides_0, weight = net_xvector_block3_tdnnd2_cam_layer_linear1_weight_to_fp16, x = input_835_cast_fp16)[name = tensor<string, []>("input_837_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_839_cast_fp16 = relu(x = input_837_cast_fp16)[name = tensor<string, []>("input_839_cast_fp16")];
            tensor<string, []> input_841_pad_type_0 = const()[name = tensor<string, []>("input_841_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_841_strides_0 = const()[name = tensor<string, []>("input_841_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_841_pad_0 = const()[name = tensor<string, []>("input_841_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_841_dilations_0 = const()[name = tensor<string, []>("input_841_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_841_groups_0 = const()[name = tensor<string, []>("input_841_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd2_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd2_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8853696)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd2_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd2_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8857856)))];
            tensor<fp16, [1, 32, ?]> input_841_cast_fp16 = conv(bias = net_xvector_block3_tdnnd2_cam_layer_linear2_bias_to_fp16, dilations = input_841_dilations_0, groups = input_841_groups_0, pad = input_841_pad_0, pad_type = input_841_pad_type_0, strides = input_841_strides_0, weight = net_xvector_block3_tdnnd2_cam_layer_linear2_weight_to_fp16, x = input_839_cast_fp16)[name = tensor<string, []>("input_841_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_75_cast_fp16 = sigmoid(x = input_841_cast_fp16)[name = tensor<string, []>("m_75_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_2932_cast_fp16 = mul(x = y_75_cast_fp16, y = m_75_cast_fp16)[name = tensor<string, []>("op_2932_cast_fp16")];
            tensor<bool, []> input_843_interleave_0 = const()[name = tensor<string, []>("input_843_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 576, ?]> input_843_cast_fp16 = concat(axis = var_11, interleave = input_843_interleave_0, values = (input_823_cast_fp16, var_2932_cast_fp16))[name = tensor<string, []>("input_843_cast_fp16")];
            tensor<fp16, [576]> net_xvector_block3_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [576]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8857984)))];
            tensor<fp16, [576]> net_xvector_block3_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [576]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8859200)))];
            tensor<fp16, [576]> net_xvector_block3_tdnnd3_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd3_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [576]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8860416)))];
            tensor<fp16, [576]> net_xvector_block3_tdnnd3_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd3_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [576]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8861632)))];
            tensor<fp16, [1, 576, ?]> input_845_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd3_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd3_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16, x = input_843_cast_fp16)[name = tensor<string, []>("input_845_cast_fp16")];
            tensor<fp16, [1, 576, ?]> input_847_cast_fp16 = relu(x = input_845_cast_fp16)[name = tensor<string, []>("input_847_cast_fp16")];
            tensor<string, []> input_849_pad_type_0 = const()[name = tensor<string, []>("input_849_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_849_strides_0 = const()[name = tensor<string, []>("input_849_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_849_pad_0 = const()[name = tensor<string, []>("input_849_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_849_dilations_0 = const()[name = tensor<string, []>("input_849_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_849_groups_0 = const()[name = tensor<string, []>("input_849_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 576, 1]> const_102_to_fp16 = const()[name = tensor<string, []>("const_102_to_fp16"), val = tensor<fp16, [128, 576, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8862848)))];
            tensor<fp16, [128]> const_103_to_fp16 = const()[name = tensor<string, []>("const_103_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9010368)))];
            tensor<fp16, [1, 128, ?]> input_851_cast_fp16 = conv(bias = const_103_to_fp16, dilations = input_849_dilations_0, groups = input_849_groups_0, pad = input_849_pad_0, pad_type = input_849_pad_type_0, strides = input_849_strides_0, weight = const_102_to_fp16, x = input_847_cast_fp16)[name = tensor<string, []>("input_851_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_853_cast_fp16 = relu(x = input_851_cast_fp16)[name = tensor<string, []>("input_853_cast_fp16")];
            tensor<string, []> y_77_pad_type_0 = const()[name = tensor<string, []>("y_77_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_77_pad_0 = const()[name = tensor<string, []>("y_77_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_77_dilations_0 = const()[name = tensor<string, []>("y_77_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_77_strides_0 = const()[name = tensor<string, []>("y_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_77_groups_0 = const()[name = tensor<string, []>("y_77_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd3_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd3_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9010688)))];
            tensor<fp16, [1, 32, ?]> y_77_cast_fp16 = conv(dilations = y_77_dilations_0, groups = y_77_groups_0, pad = y_77_pad_0, pad_type = y_77_pad_type_0, strides = y_77_strides_0, weight = net_xvector_block3_tdnnd3_cam_layer_linear_local_weight_to_fp16, x = input_853_cast_fp16)[name = tensor<string, []>("y_77_cast_fp16")];
            tensor<int32, [1]> var_2969_axes_0 = const()[name = tensor<string, []>("op_2969_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_2969_keep_dims_0 = const()[name = tensor<string, []>("op_2969_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_2969_cast_fp16 = reduce_mean(axes = var_2969_axes_0, keep_dims = var_2969_keep_dims_0, x = input_853_cast_fp16)[name = tensor<string, []>("op_2969_cast_fp16")];
            tensor<int32, [1]> var_2970 = const()[name = tensor<string, []>("op_2970"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_2971 = const()[name = tensor<string, []>("op_2971"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_153_pad_type_0 = const()[name = tensor<string, []>("seg_153_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_153_pad_0 = const()[name = tensor<string, []>("seg_153_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_153_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_153_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_153_ceil_mode_0 = const()[name = tensor<string, []>("seg_153_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_153_cast_fp16 = avg_pool(ceil_mode = seg_153_ceil_mode_0, exclude_padding_from_average = seg_153_exclude_padding_from_average_0, kernel_sizes = var_2970, pad = seg_153_pad_0, pad_type = seg_153_pad_type_0, strides = var_2971, x = input_853_cast_fp16)[name = tensor<string, []>("seg_153_cast_fp16")];
            tensor<int32, [3]> var_2974_shape_cast_fp16 = shape(x = seg_153_cast_fp16)[name = tensor<string, []>("op_2974_shape_cast_fp16")];
            tensor<int32, []> gather_156 = const()[name = tensor<string, []>("gather_156"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_157 = const()[name = tensor<string, []>("gather_157"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_158_axis_0 = const()[name = tensor<string, []>("gather_158_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_158_batch_dims_0 = const()[name = tensor<string, []>("gather_158_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_158_validate_indices_0 = const()[name = tensor<string, []>("gather_158_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2974_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2974_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_158_to_uint16 = const()[name = tensor<string, []>("select_158_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2974_shape_cast_fp16_to_uint16 = cast(dtype = var_2974_shape_cast_fp16_to_uint16_dtype_0, x = var_2974_shape_cast_fp16)[name = tensor<string, []>("cast_163")];
            tensor<uint16, []> gather_158_cast_uint16 = gather(axis = gather_158_axis_0, batch_dims = gather_158_batch_dims_0, indices = select_158_to_uint16, validate_indices = gather_158_validate_indices_0, x = var_2974_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_158_cast_uint16")];
            tensor<string, []> gather_158_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_158_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_2977_axes_0 = const()[name = tensor<string, []>("op_2977_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_2977_cast_fp16 = expand_dims(axes = var_2977_axes_0, x = seg_153_cast_fp16)[name = tensor<string, []>("op_2977_cast_fp16")];
            tensor<int32, []> concat_77_axis_0 = const()[name = tensor<string, []>("concat_77_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_77_interleave_0 = const()[name = tensor<string, []>("concat_77_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_158_cast_uint16_to_int32 = cast(dtype = gather_158_cast_uint16_to_int32_dtype_0, x = gather_158_cast_uint16)[name = tensor<string, []>("cast_162")];
            tensor<int32, [4]> concat_77 = concat(axis = concat_77_axis_0, interleave = concat_77_interleave_0, values = (gather_156, gather_157, gather_158_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_77")];
            tensor<int32, [4]> shape_197_cast_fp16 = shape(x = var_2977_cast_fp16)[name = tensor<string, []>("shape_197_cast_fp16")];
            tensor<int32, [4]> real_div_38 = real_div(x = concat_77, y = shape_197_cast_fp16)[name = tensor<string, []>("real_div_38")];
            tensor<fp16, [?, ?, ?, ?]> var_2979_cast_fp16 = tile(reps = real_div_38, x = var_2977_cast_fp16)[name = tensor<string, []>("op_2979_cast_fp16")];
            tensor<int32, [3]> var_2980 = const()[name = tensor<string, []>("op_2980"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_155_cast_fp16 = reshape(shape = var_2980, x = var_2979_cast_fp16)[name = tensor<string, []>("seg_155_cast_fp16")];
            tensor<int32, [3]> var_2982_shape_cast_fp16 = shape(x = input_853_cast_fp16)[name = tensor<string, []>("op_2982_shape_cast_fp16")];
            tensor<int32, []> gather_159_axis_0 = const()[name = tensor<string, []>("gather_159_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_159_batch_dims_0 = const()[name = tensor<string, []>("gather_159_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_159_validate_indices_0 = const()[name = tensor<string, []>("gather_159_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_2982_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_2982_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_159_to_uint16 = const()[name = tensor<string, []>("select_159_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_2982_shape_cast_fp16_to_uint16 = cast(dtype = var_2982_shape_cast_fp16_to_uint16_dtype_0, x = var_2982_shape_cast_fp16)[name = tensor<string, []>("cast_161")];
            tensor<uint16, []> gather_159_cast_uint16 = gather(axis = gather_159_axis_0, batch_dims = gather_159_batch_dims_0, indices = select_159_to_uint16, validate_indices = gather_159_validate_indices_0, x = var_2982_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_159_cast_uint16")];
            tensor<string, []> gather_159_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_159_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_78_values0_0 = const()[name = tensor<string, []>("concat_78_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_78_values1_0 = const()[name = tensor<string, []>("concat_78_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_78_axis_0 = const()[name = tensor<string, []>("concat_78_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_78_interleave_0 = const()[name = tensor<string, []>("concat_78_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_159_cast_uint16_to_int32 = cast(dtype = gather_159_cast_uint16_to_int32_dtype_0, x = gather_159_cast_uint16)[name = tensor<string, []>("cast_160")];
            tensor<int32, [3]> concat_78 = concat(axis = concat_78_axis_0, interleave = concat_78_interleave_0, values = (concat_78_values0_0, concat_78_values1_0, gather_159_cast_uint16_to_int32))[name = tensor<string, []>("concat_78")];
            tensor<int32, [3]> var_2983_begin_0 = const()[name = tensor<string, []>("op_2983_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_2983_end_mask_0 = const()[name = tensor<string, []>("op_2983_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_2983_cast_fp16 = slice_by_index(begin = var_2983_begin_0, end = concat_78, end_mask = var_2983_end_mask_0, x = seg_155_cast_fp16)[name = tensor<string, []>("op_2983_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_855_cast_fp16 = add(x = var_2969_cast_fp16, y = var_2983_cast_fp16)[name = tensor<string, []>("input_855_cast_fp16")];
            tensor<string, []> input_857_pad_type_0 = const()[name = tensor<string, []>("input_857_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_857_strides_0 = const()[name = tensor<string, []>("input_857_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_857_pad_0 = const()[name = tensor<string, []>("input_857_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_857_dilations_0 = const()[name = tensor<string, []>("input_857_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_857_groups_0 = const()[name = tensor<string, []>("input_857_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd3_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd3_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9035328)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd3_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd3_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9051776)))];
            tensor<fp16, [1, 64, ?]> input_857_cast_fp16 = conv(bias = net_xvector_block3_tdnnd3_cam_layer_linear1_bias_to_fp16, dilations = input_857_dilations_0, groups = input_857_groups_0, pad = input_857_pad_0, pad_type = input_857_pad_type_0, strides = input_857_strides_0, weight = net_xvector_block3_tdnnd3_cam_layer_linear1_weight_to_fp16, x = input_855_cast_fp16)[name = tensor<string, []>("input_857_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_859_cast_fp16 = relu(x = input_857_cast_fp16)[name = tensor<string, []>("input_859_cast_fp16")];
            tensor<string, []> input_861_pad_type_0 = const()[name = tensor<string, []>("input_861_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_861_strides_0 = const()[name = tensor<string, []>("input_861_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_861_pad_0 = const()[name = tensor<string, []>("input_861_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_861_dilations_0 = const()[name = tensor<string, []>("input_861_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_861_groups_0 = const()[name = tensor<string, []>("input_861_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd3_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd3_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9051968)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd3_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd3_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9056128)))];
            tensor<fp16, [1, 32, ?]> input_861_cast_fp16 = conv(bias = net_xvector_block3_tdnnd3_cam_layer_linear2_bias_to_fp16, dilations = input_861_dilations_0, groups = input_861_groups_0, pad = input_861_pad_0, pad_type = input_861_pad_type_0, strides = input_861_strides_0, weight = net_xvector_block3_tdnnd3_cam_layer_linear2_weight_to_fp16, x = input_859_cast_fp16)[name = tensor<string, []>("input_861_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_77_cast_fp16 = sigmoid(x = input_861_cast_fp16)[name = tensor<string, []>("m_77_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3001_cast_fp16 = mul(x = y_77_cast_fp16, y = m_77_cast_fp16)[name = tensor<string, []>("op_3001_cast_fp16")];
            tensor<bool, []> input_863_interleave_0 = const()[name = tensor<string, []>("input_863_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 608, ?]> input_863_cast_fp16 = concat(axis = var_11, interleave = input_863_interleave_0, values = (input_843_cast_fp16, var_3001_cast_fp16))[name = tensor<string, []>("input_863_cast_fp16")];
            tensor<fp16, [608]> net_xvector_block3_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9056256)))];
            tensor<fp16, [608]> net_xvector_block3_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9057536)))];
            tensor<fp16, [608]> net_xvector_block3_tdnnd4_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd4_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9058816)))];
            tensor<fp16, [608]> net_xvector_block3_tdnnd4_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd4_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [608]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9060096)))];
            tensor<fp16, [1, 608, ?]> input_865_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd4_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd4_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16, x = input_863_cast_fp16)[name = tensor<string, []>("input_865_cast_fp16")];
            tensor<fp16, [1, 608, ?]> input_867_cast_fp16 = relu(x = input_865_cast_fp16)[name = tensor<string, []>("input_867_cast_fp16")];
            tensor<string, []> input_869_pad_type_0 = const()[name = tensor<string, []>("input_869_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_869_strides_0 = const()[name = tensor<string, []>("input_869_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_869_pad_0 = const()[name = tensor<string, []>("input_869_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_869_dilations_0 = const()[name = tensor<string, []>("input_869_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_869_groups_0 = const()[name = tensor<string, []>("input_869_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 608, 1]> const_104_to_fp16 = const()[name = tensor<string, []>("const_104_to_fp16"), val = tensor<fp16, [128, 608, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9061376)))];
            tensor<fp16, [128]> const_105_to_fp16 = const()[name = tensor<string, []>("const_105_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9217088)))];
            tensor<fp16, [1, 128, ?]> input_871_cast_fp16 = conv(bias = const_105_to_fp16, dilations = input_869_dilations_0, groups = input_869_groups_0, pad = input_869_pad_0, pad_type = input_869_pad_type_0, strides = input_869_strides_0, weight = const_104_to_fp16, x = input_867_cast_fp16)[name = tensor<string, []>("input_871_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_873_cast_fp16 = relu(x = input_871_cast_fp16)[name = tensor<string, []>("input_873_cast_fp16")];
            tensor<string, []> y_79_pad_type_0 = const()[name = tensor<string, []>("y_79_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_79_pad_0 = const()[name = tensor<string, []>("y_79_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_79_dilations_0 = const()[name = tensor<string, []>("y_79_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_79_strides_0 = const()[name = tensor<string, []>("y_79_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_79_groups_0 = const()[name = tensor<string, []>("y_79_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd4_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd4_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9217408)))];
            tensor<fp16, [1, 32, ?]> y_79_cast_fp16 = conv(dilations = y_79_dilations_0, groups = y_79_groups_0, pad = y_79_pad_0, pad_type = y_79_pad_type_0, strides = y_79_strides_0, weight = net_xvector_block3_tdnnd4_cam_layer_linear_local_weight_to_fp16, x = input_873_cast_fp16)[name = tensor<string, []>("y_79_cast_fp16")];
            tensor<int32, [1]> var_3038_axes_0 = const()[name = tensor<string, []>("op_3038_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3038_keep_dims_0 = const()[name = tensor<string, []>("op_3038_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3038_cast_fp16 = reduce_mean(axes = var_3038_axes_0, keep_dims = var_3038_keep_dims_0, x = input_873_cast_fp16)[name = tensor<string, []>("op_3038_cast_fp16")];
            tensor<int32, [1]> var_3039 = const()[name = tensor<string, []>("op_3039"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3040 = const()[name = tensor<string, []>("op_3040"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_157_pad_type_0 = const()[name = tensor<string, []>("seg_157_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_157_pad_0 = const()[name = tensor<string, []>("seg_157_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_157_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_157_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_157_ceil_mode_0 = const()[name = tensor<string, []>("seg_157_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_157_cast_fp16 = avg_pool(ceil_mode = seg_157_ceil_mode_0, exclude_padding_from_average = seg_157_exclude_padding_from_average_0, kernel_sizes = var_3039, pad = seg_157_pad_0, pad_type = seg_157_pad_type_0, strides = var_3040, x = input_873_cast_fp16)[name = tensor<string, []>("seg_157_cast_fp16")];
            tensor<int32, [3]> var_3043_shape_cast_fp16 = shape(x = seg_157_cast_fp16)[name = tensor<string, []>("op_3043_shape_cast_fp16")];
            tensor<int32, []> gather_160 = const()[name = tensor<string, []>("gather_160"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_161 = const()[name = tensor<string, []>("gather_161"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_162_axis_0 = const()[name = tensor<string, []>("gather_162_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_162_batch_dims_0 = const()[name = tensor<string, []>("gather_162_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_162_validate_indices_0 = const()[name = tensor<string, []>("gather_162_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3043_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3043_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_162_to_uint16 = const()[name = tensor<string, []>("select_162_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3043_shape_cast_fp16_to_uint16 = cast(dtype = var_3043_shape_cast_fp16_to_uint16_dtype_0, x = var_3043_shape_cast_fp16)[name = tensor<string, []>("cast_159")];
            tensor<uint16, []> gather_162_cast_uint16 = gather(axis = gather_162_axis_0, batch_dims = gather_162_batch_dims_0, indices = select_162_to_uint16, validate_indices = gather_162_validate_indices_0, x = var_3043_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_162_cast_uint16")];
            tensor<string, []> gather_162_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_162_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3046_axes_0 = const()[name = tensor<string, []>("op_3046_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3046_cast_fp16 = expand_dims(axes = var_3046_axes_0, x = seg_157_cast_fp16)[name = tensor<string, []>("op_3046_cast_fp16")];
            tensor<int32, []> concat_79_axis_0 = const()[name = tensor<string, []>("concat_79_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_79_interleave_0 = const()[name = tensor<string, []>("concat_79_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_162_cast_uint16_to_int32 = cast(dtype = gather_162_cast_uint16_to_int32_dtype_0, x = gather_162_cast_uint16)[name = tensor<string, []>("cast_158")];
            tensor<int32, [4]> concat_79 = concat(axis = concat_79_axis_0, interleave = concat_79_interleave_0, values = (gather_160, gather_161, gather_162_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_79")];
            tensor<int32, [4]> shape_202_cast_fp16 = shape(x = var_3046_cast_fp16)[name = tensor<string, []>("shape_202_cast_fp16")];
            tensor<int32, [4]> real_div_39 = real_div(x = concat_79, y = shape_202_cast_fp16)[name = tensor<string, []>("real_div_39")];
            tensor<fp16, [?, ?, ?, ?]> var_3048_cast_fp16 = tile(reps = real_div_39, x = var_3046_cast_fp16)[name = tensor<string, []>("op_3048_cast_fp16")];
            tensor<int32, [3]> var_3049 = const()[name = tensor<string, []>("op_3049"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_159_cast_fp16 = reshape(shape = var_3049, x = var_3048_cast_fp16)[name = tensor<string, []>("seg_159_cast_fp16")];
            tensor<int32, [3]> var_3051_shape_cast_fp16 = shape(x = input_873_cast_fp16)[name = tensor<string, []>("op_3051_shape_cast_fp16")];
            tensor<int32, []> gather_163_axis_0 = const()[name = tensor<string, []>("gather_163_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_163_batch_dims_0 = const()[name = tensor<string, []>("gather_163_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_163_validate_indices_0 = const()[name = tensor<string, []>("gather_163_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3051_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3051_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_163_to_uint16 = const()[name = tensor<string, []>("select_163_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3051_shape_cast_fp16_to_uint16 = cast(dtype = var_3051_shape_cast_fp16_to_uint16_dtype_0, x = var_3051_shape_cast_fp16)[name = tensor<string, []>("cast_157")];
            tensor<uint16, []> gather_163_cast_uint16 = gather(axis = gather_163_axis_0, batch_dims = gather_163_batch_dims_0, indices = select_163_to_uint16, validate_indices = gather_163_validate_indices_0, x = var_3051_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_163_cast_uint16")];
            tensor<string, []> gather_163_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_163_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_80_values0_0 = const()[name = tensor<string, []>("concat_80_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_80_values1_0 = const()[name = tensor<string, []>("concat_80_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_80_axis_0 = const()[name = tensor<string, []>("concat_80_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_80_interleave_0 = const()[name = tensor<string, []>("concat_80_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_163_cast_uint16_to_int32 = cast(dtype = gather_163_cast_uint16_to_int32_dtype_0, x = gather_163_cast_uint16)[name = tensor<string, []>("cast_156")];
            tensor<int32, [3]> concat_80 = concat(axis = concat_80_axis_0, interleave = concat_80_interleave_0, values = (concat_80_values0_0, concat_80_values1_0, gather_163_cast_uint16_to_int32))[name = tensor<string, []>("concat_80")];
            tensor<int32, [3]> var_3052_begin_0 = const()[name = tensor<string, []>("op_3052_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3052_end_mask_0 = const()[name = tensor<string, []>("op_3052_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3052_cast_fp16 = slice_by_index(begin = var_3052_begin_0, end = concat_80, end_mask = var_3052_end_mask_0, x = seg_159_cast_fp16)[name = tensor<string, []>("op_3052_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_875_cast_fp16 = add(x = var_3038_cast_fp16, y = var_3052_cast_fp16)[name = tensor<string, []>("input_875_cast_fp16")];
            tensor<string, []> input_877_pad_type_0 = const()[name = tensor<string, []>("input_877_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_877_strides_0 = const()[name = tensor<string, []>("input_877_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_877_pad_0 = const()[name = tensor<string, []>("input_877_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_877_dilations_0 = const()[name = tensor<string, []>("input_877_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_877_groups_0 = const()[name = tensor<string, []>("input_877_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd4_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd4_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9242048)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd4_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd4_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9258496)))];
            tensor<fp16, [1, 64, ?]> input_877_cast_fp16 = conv(bias = net_xvector_block3_tdnnd4_cam_layer_linear1_bias_to_fp16, dilations = input_877_dilations_0, groups = input_877_groups_0, pad = input_877_pad_0, pad_type = input_877_pad_type_0, strides = input_877_strides_0, weight = net_xvector_block3_tdnnd4_cam_layer_linear1_weight_to_fp16, x = input_875_cast_fp16)[name = tensor<string, []>("input_877_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_879_cast_fp16 = relu(x = input_877_cast_fp16)[name = tensor<string, []>("input_879_cast_fp16")];
            tensor<string, []> input_881_pad_type_0 = const()[name = tensor<string, []>("input_881_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_881_strides_0 = const()[name = tensor<string, []>("input_881_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_881_pad_0 = const()[name = tensor<string, []>("input_881_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_881_dilations_0 = const()[name = tensor<string, []>("input_881_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_881_groups_0 = const()[name = tensor<string, []>("input_881_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd4_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd4_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9258688)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd4_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd4_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9262848)))];
            tensor<fp16, [1, 32, ?]> input_881_cast_fp16 = conv(bias = net_xvector_block3_tdnnd4_cam_layer_linear2_bias_to_fp16, dilations = input_881_dilations_0, groups = input_881_groups_0, pad = input_881_pad_0, pad_type = input_881_pad_type_0, strides = input_881_strides_0, weight = net_xvector_block3_tdnnd4_cam_layer_linear2_weight_to_fp16, x = input_879_cast_fp16)[name = tensor<string, []>("input_881_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_79_cast_fp16 = sigmoid(x = input_881_cast_fp16)[name = tensor<string, []>("m_79_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3070_cast_fp16 = mul(x = y_79_cast_fp16, y = m_79_cast_fp16)[name = tensor<string, []>("op_3070_cast_fp16")];
            tensor<bool, []> input_883_interleave_0 = const()[name = tensor<string, []>("input_883_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 640, ?]> input_883_cast_fp16 = concat(axis = var_11, interleave = input_883_interleave_0, values = (input_863_cast_fp16, var_3070_cast_fp16))[name = tensor<string, []>("input_883_cast_fp16")];
            tensor<fp16, [640]> net_xvector_block3_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9262976)))];
            tensor<fp16, [640]> net_xvector_block3_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9264320)))];
            tensor<fp16, [640]> net_xvector_block3_tdnnd5_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd5_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9265664)))];
            tensor<fp16, [640]> net_xvector_block3_tdnnd5_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd5_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9267008)))];
            tensor<fp16, [1, 640, ?]> input_885_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd5_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd5_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16, x = input_883_cast_fp16)[name = tensor<string, []>("input_885_cast_fp16")];
            tensor<fp16, [1, 640, ?]> input_887_cast_fp16 = relu(x = input_885_cast_fp16)[name = tensor<string, []>("input_887_cast_fp16")];
            tensor<string, []> input_889_pad_type_0 = const()[name = tensor<string, []>("input_889_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_889_strides_0 = const()[name = tensor<string, []>("input_889_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_889_pad_0 = const()[name = tensor<string, []>("input_889_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_889_dilations_0 = const()[name = tensor<string, []>("input_889_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_889_groups_0 = const()[name = tensor<string, []>("input_889_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 640, 1]> const_106_to_fp16 = const()[name = tensor<string, []>("const_106_to_fp16"), val = tensor<fp16, [128, 640, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9268352)))];
            tensor<fp16, [128]> const_107_to_fp16 = const()[name = tensor<string, []>("const_107_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9432256)))];
            tensor<fp16, [1, 128, ?]> input_891_cast_fp16 = conv(bias = const_107_to_fp16, dilations = input_889_dilations_0, groups = input_889_groups_0, pad = input_889_pad_0, pad_type = input_889_pad_type_0, strides = input_889_strides_0, weight = const_106_to_fp16, x = input_887_cast_fp16)[name = tensor<string, []>("input_891_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_893_cast_fp16 = relu(x = input_891_cast_fp16)[name = tensor<string, []>("input_893_cast_fp16")];
            tensor<string, []> y_81_pad_type_0 = const()[name = tensor<string, []>("y_81_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_81_pad_0 = const()[name = tensor<string, []>("y_81_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_81_dilations_0 = const()[name = tensor<string, []>("y_81_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_81_strides_0 = const()[name = tensor<string, []>("y_81_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_81_groups_0 = const()[name = tensor<string, []>("y_81_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd5_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd5_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9432576)))];
            tensor<fp16, [1, 32, ?]> y_81_cast_fp16 = conv(dilations = y_81_dilations_0, groups = y_81_groups_0, pad = y_81_pad_0, pad_type = y_81_pad_type_0, strides = y_81_strides_0, weight = net_xvector_block3_tdnnd5_cam_layer_linear_local_weight_to_fp16, x = input_893_cast_fp16)[name = tensor<string, []>("y_81_cast_fp16")];
            tensor<int32, [1]> var_3107_axes_0 = const()[name = tensor<string, []>("op_3107_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3107_keep_dims_0 = const()[name = tensor<string, []>("op_3107_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3107_cast_fp16 = reduce_mean(axes = var_3107_axes_0, keep_dims = var_3107_keep_dims_0, x = input_893_cast_fp16)[name = tensor<string, []>("op_3107_cast_fp16")];
            tensor<int32, [1]> var_3108 = const()[name = tensor<string, []>("op_3108"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3109 = const()[name = tensor<string, []>("op_3109"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_161_pad_type_0 = const()[name = tensor<string, []>("seg_161_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_161_pad_0 = const()[name = tensor<string, []>("seg_161_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_161_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_161_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_161_ceil_mode_0 = const()[name = tensor<string, []>("seg_161_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_161_cast_fp16 = avg_pool(ceil_mode = seg_161_ceil_mode_0, exclude_padding_from_average = seg_161_exclude_padding_from_average_0, kernel_sizes = var_3108, pad = seg_161_pad_0, pad_type = seg_161_pad_type_0, strides = var_3109, x = input_893_cast_fp16)[name = tensor<string, []>("seg_161_cast_fp16")];
            tensor<int32, [3]> var_3112_shape_cast_fp16 = shape(x = seg_161_cast_fp16)[name = tensor<string, []>("op_3112_shape_cast_fp16")];
            tensor<int32, []> gather_164 = const()[name = tensor<string, []>("gather_164"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_165 = const()[name = tensor<string, []>("gather_165"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_166_axis_0 = const()[name = tensor<string, []>("gather_166_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_166_batch_dims_0 = const()[name = tensor<string, []>("gather_166_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_166_validate_indices_0 = const()[name = tensor<string, []>("gather_166_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3112_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3112_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_166_to_uint16 = const()[name = tensor<string, []>("select_166_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3112_shape_cast_fp16_to_uint16 = cast(dtype = var_3112_shape_cast_fp16_to_uint16_dtype_0, x = var_3112_shape_cast_fp16)[name = tensor<string, []>("cast_155")];
            tensor<uint16, []> gather_166_cast_uint16 = gather(axis = gather_166_axis_0, batch_dims = gather_166_batch_dims_0, indices = select_166_to_uint16, validate_indices = gather_166_validate_indices_0, x = var_3112_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_166_cast_uint16")];
            tensor<string, []> gather_166_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_166_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3115_axes_0 = const()[name = tensor<string, []>("op_3115_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3115_cast_fp16 = expand_dims(axes = var_3115_axes_0, x = seg_161_cast_fp16)[name = tensor<string, []>("op_3115_cast_fp16")];
            tensor<int32, []> concat_81_axis_0 = const()[name = tensor<string, []>("concat_81_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_81_interleave_0 = const()[name = tensor<string, []>("concat_81_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_166_cast_uint16_to_int32 = cast(dtype = gather_166_cast_uint16_to_int32_dtype_0, x = gather_166_cast_uint16)[name = tensor<string, []>("cast_154")];
            tensor<int32, [4]> concat_81 = concat(axis = concat_81_axis_0, interleave = concat_81_interleave_0, values = (gather_164, gather_165, gather_166_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_81")];
            tensor<int32, [4]> shape_207_cast_fp16 = shape(x = var_3115_cast_fp16)[name = tensor<string, []>("shape_207_cast_fp16")];
            tensor<int32, [4]> real_div_40 = real_div(x = concat_81, y = shape_207_cast_fp16)[name = tensor<string, []>("real_div_40")];
            tensor<fp16, [?, ?, ?, ?]> var_3117_cast_fp16 = tile(reps = real_div_40, x = var_3115_cast_fp16)[name = tensor<string, []>("op_3117_cast_fp16")];
            tensor<int32, [3]> var_3118 = const()[name = tensor<string, []>("op_3118"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_163_cast_fp16 = reshape(shape = var_3118, x = var_3117_cast_fp16)[name = tensor<string, []>("seg_163_cast_fp16")];
            tensor<int32, [3]> var_3120_shape_cast_fp16 = shape(x = input_893_cast_fp16)[name = tensor<string, []>("op_3120_shape_cast_fp16")];
            tensor<int32, []> gather_167_axis_0 = const()[name = tensor<string, []>("gather_167_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_167_batch_dims_0 = const()[name = tensor<string, []>("gather_167_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_167_validate_indices_0 = const()[name = tensor<string, []>("gather_167_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3120_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3120_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_167_to_uint16 = const()[name = tensor<string, []>("select_167_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3120_shape_cast_fp16_to_uint16 = cast(dtype = var_3120_shape_cast_fp16_to_uint16_dtype_0, x = var_3120_shape_cast_fp16)[name = tensor<string, []>("cast_153")];
            tensor<uint16, []> gather_167_cast_uint16 = gather(axis = gather_167_axis_0, batch_dims = gather_167_batch_dims_0, indices = select_167_to_uint16, validate_indices = gather_167_validate_indices_0, x = var_3120_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_167_cast_uint16")];
            tensor<string, []> gather_167_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_167_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_82_values0_0 = const()[name = tensor<string, []>("concat_82_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_82_values1_0 = const()[name = tensor<string, []>("concat_82_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_82_axis_0 = const()[name = tensor<string, []>("concat_82_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_82_interleave_0 = const()[name = tensor<string, []>("concat_82_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_167_cast_uint16_to_int32 = cast(dtype = gather_167_cast_uint16_to_int32_dtype_0, x = gather_167_cast_uint16)[name = tensor<string, []>("cast_152")];
            tensor<int32, [3]> concat_82 = concat(axis = concat_82_axis_0, interleave = concat_82_interleave_0, values = (concat_82_values0_0, concat_82_values1_0, gather_167_cast_uint16_to_int32))[name = tensor<string, []>("concat_82")];
            tensor<int32, [3]> var_3121_begin_0 = const()[name = tensor<string, []>("op_3121_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3121_end_mask_0 = const()[name = tensor<string, []>("op_3121_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3121_cast_fp16 = slice_by_index(begin = var_3121_begin_0, end = concat_82, end_mask = var_3121_end_mask_0, x = seg_163_cast_fp16)[name = tensor<string, []>("op_3121_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_895_cast_fp16 = add(x = var_3107_cast_fp16, y = var_3121_cast_fp16)[name = tensor<string, []>("input_895_cast_fp16")];
            tensor<string, []> input_897_pad_type_0 = const()[name = tensor<string, []>("input_897_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_897_strides_0 = const()[name = tensor<string, []>("input_897_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_897_pad_0 = const()[name = tensor<string, []>("input_897_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_897_dilations_0 = const()[name = tensor<string, []>("input_897_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_897_groups_0 = const()[name = tensor<string, []>("input_897_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd5_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd5_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9457216)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd5_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd5_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9473664)))];
            tensor<fp16, [1, 64, ?]> input_897_cast_fp16 = conv(bias = net_xvector_block3_tdnnd5_cam_layer_linear1_bias_to_fp16, dilations = input_897_dilations_0, groups = input_897_groups_0, pad = input_897_pad_0, pad_type = input_897_pad_type_0, strides = input_897_strides_0, weight = net_xvector_block3_tdnnd5_cam_layer_linear1_weight_to_fp16, x = input_895_cast_fp16)[name = tensor<string, []>("input_897_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_899_cast_fp16 = relu(x = input_897_cast_fp16)[name = tensor<string, []>("input_899_cast_fp16")];
            tensor<string, []> input_901_pad_type_0 = const()[name = tensor<string, []>("input_901_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_901_strides_0 = const()[name = tensor<string, []>("input_901_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_901_pad_0 = const()[name = tensor<string, []>("input_901_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_901_dilations_0 = const()[name = tensor<string, []>("input_901_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_901_groups_0 = const()[name = tensor<string, []>("input_901_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd5_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd5_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9473856)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd5_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd5_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9478016)))];
            tensor<fp16, [1, 32, ?]> input_901_cast_fp16 = conv(bias = net_xvector_block3_tdnnd5_cam_layer_linear2_bias_to_fp16, dilations = input_901_dilations_0, groups = input_901_groups_0, pad = input_901_pad_0, pad_type = input_901_pad_type_0, strides = input_901_strides_0, weight = net_xvector_block3_tdnnd5_cam_layer_linear2_weight_to_fp16, x = input_899_cast_fp16)[name = tensor<string, []>("input_901_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_81_cast_fp16 = sigmoid(x = input_901_cast_fp16)[name = tensor<string, []>("m_81_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3139_cast_fp16 = mul(x = y_81_cast_fp16, y = m_81_cast_fp16)[name = tensor<string, []>("op_3139_cast_fp16")];
            tensor<bool, []> input_903_interleave_0 = const()[name = tensor<string, []>("input_903_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 672, ?]> input_903_cast_fp16 = concat(axis = var_11, interleave = input_903_interleave_0, values = (input_883_cast_fp16, var_3139_cast_fp16))[name = tensor<string, []>("input_903_cast_fp16")];
            tensor<fp16, [672]> net_xvector_block3_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [672]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9478144)))];
            tensor<fp16, [672]> net_xvector_block3_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [672]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9479552)))];
            tensor<fp16, [672]> net_xvector_block3_tdnnd6_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd6_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [672]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9480960)))];
            tensor<fp16, [672]> net_xvector_block3_tdnnd6_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd6_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [672]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9482368)))];
            tensor<fp16, [1, 672, ?]> input_905_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd6_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd6_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16, x = input_903_cast_fp16)[name = tensor<string, []>("input_905_cast_fp16")];
            tensor<fp16, [1, 672, ?]> input_907_cast_fp16 = relu(x = input_905_cast_fp16)[name = tensor<string, []>("input_907_cast_fp16")];
            tensor<string, []> input_909_pad_type_0 = const()[name = tensor<string, []>("input_909_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_909_strides_0 = const()[name = tensor<string, []>("input_909_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_909_pad_0 = const()[name = tensor<string, []>("input_909_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_909_dilations_0 = const()[name = tensor<string, []>("input_909_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_909_groups_0 = const()[name = tensor<string, []>("input_909_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 672, 1]> const_108_to_fp16 = const()[name = tensor<string, []>("const_108_to_fp16"), val = tensor<fp16, [128, 672, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9483776)))];
            tensor<fp16, [128]> const_109_to_fp16 = const()[name = tensor<string, []>("const_109_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9655872)))];
            tensor<fp16, [1, 128, ?]> input_911_cast_fp16 = conv(bias = const_109_to_fp16, dilations = input_909_dilations_0, groups = input_909_groups_0, pad = input_909_pad_0, pad_type = input_909_pad_type_0, strides = input_909_strides_0, weight = const_108_to_fp16, x = input_907_cast_fp16)[name = tensor<string, []>("input_911_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_913_cast_fp16 = relu(x = input_911_cast_fp16)[name = tensor<string, []>("input_913_cast_fp16")];
            tensor<string, []> y_83_pad_type_0 = const()[name = tensor<string, []>("y_83_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_83_pad_0 = const()[name = tensor<string, []>("y_83_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_83_dilations_0 = const()[name = tensor<string, []>("y_83_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_83_strides_0 = const()[name = tensor<string, []>("y_83_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_83_groups_0 = const()[name = tensor<string, []>("y_83_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd6_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd6_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9656192)))];
            tensor<fp16, [1, 32, ?]> y_83_cast_fp16 = conv(dilations = y_83_dilations_0, groups = y_83_groups_0, pad = y_83_pad_0, pad_type = y_83_pad_type_0, strides = y_83_strides_0, weight = net_xvector_block3_tdnnd6_cam_layer_linear_local_weight_to_fp16, x = input_913_cast_fp16)[name = tensor<string, []>("y_83_cast_fp16")];
            tensor<int32, [1]> var_3176_axes_0 = const()[name = tensor<string, []>("op_3176_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3176_keep_dims_0 = const()[name = tensor<string, []>("op_3176_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3176_cast_fp16 = reduce_mean(axes = var_3176_axes_0, keep_dims = var_3176_keep_dims_0, x = input_913_cast_fp16)[name = tensor<string, []>("op_3176_cast_fp16")];
            tensor<int32, [1]> var_3177 = const()[name = tensor<string, []>("op_3177"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3178 = const()[name = tensor<string, []>("op_3178"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_165_pad_type_0 = const()[name = tensor<string, []>("seg_165_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_165_pad_0 = const()[name = tensor<string, []>("seg_165_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_165_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_165_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_165_ceil_mode_0 = const()[name = tensor<string, []>("seg_165_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_165_cast_fp16 = avg_pool(ceil_mode = seg_165_ceil_mode_0, exclude_padding_from_average = seg_165_exclude_padding_from_average_0, kernel_sizes = var_3177, pad = seg_165_pad_0, pad_type = seg_165_pad_type_0, strides = var_3178, x = input_913_cast_fp16)[name = tensor<string, []>("seg_165_cast_fp16")];
            tensor<int32, [3]> var_3181_shape_cast_fp16 = shape(x = seg_165_cast_fp16)[name = tensor<string, []>("op_3181_shape_cast_fp16")];
            tensor<int32, []> gather_168 = const()[name = tensor<string, []>("gather_168"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_169 = const()[name = tensor<string, []>("gather_169"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_170_axis_0 = const()[name = tensor<string, []>("gather_170_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_170_batch_dims_0 = const()[name = tensor<string, []>("gather_170_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_170_validate_indices_0 = const()[name = tensor<string, []>("gather_170_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3181_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3181_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_170_to_uint16 = const()[name = tensor<string, []>("select_170_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3181_shape_cast_fp16_to_uint16 = cast(dtype = var_3181_shape_cast_fp16_to_uint16_dtype_0, x = var_3181_shape_cast_fp16)[name = tensor<string, []>("cast_151")];
            tensor<uint16, []> gather_170_cast_uint16 = gather(axis = gather_170_axis_0, batch_dims = gather_170_batch_dims_0, indices = select_170_to_uint16, validate_indices = gather_170_validate_indices_0, x = var_3181_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_170_cast_uint16")];
            tensor<string, []> gather_170_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_170_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3184_axes_0 = const()[name = tensor<string, []>("op_3184_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3184_cast_fp16 = expand_dims(axes = var_3184_axes_0, x = seg_165_cast_fp16)[name = tensor<string, []>("op_3184_cast_fp16")];
            tensor<int32, []> concat_83_axis_0 = const()[name = tensor<string, []>("concat_83_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_83_interleave_0 = const()[name = tensor<string, []>("concat_83_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_170_cast_uint16_to_int32 = cast(dtype = gather_170_cast_uint16_to_int32_dtype_0, x = gather_170_cast_uint16)[name = tensor<string, []>("cast_150")];
            tensor<int32, [4]> concat_83 = concat(axis = concat_83_axis_0, interleave = concat_83_interleave_0, values = (gather_168, gather_169, gather_170_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_83")];
            tensor<int32, [4]> shape_212_cast_fp16 = shape(x = var_3184_cast_fp16)[name = tensor<string, []>("shape_212_cast_fp16")];
            tensor<int32, [4]> real_div_41 = real_div(x = concat_83, y = shape_212_cast_fp16)[name = tensor<string, []>("real_div_41")];
            tensor<fp16, [?, ?, ?, ?]> var_3186_cast_fp16 = tile(reps = real_div_41, x = var_3184_cast_fp16)[name = tensor<string, []>("op_3186_cast_fp16")];
            tensor<int32, [3]> var_3187 = const()[name = tensor<string, []>("op_3187"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_167_cast_fp16 = reshape(shape = var_3187, x = var_3186_cast_fp16)[name = tensor<string, []>("seg_167_cast_fp16")];
            tensor<int32, [3]> var_3189_shape_cast_fp16 = shape(x = input_913_cast_fp16)[name = tensor<string, []>("op_3189_shape_cast_fp16")];
            tensor<int32, []> gather_171_axis_0 = const()[name = tensor<string, []>("gather_171_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_171_batch_dims_0 = const()[name = tensor<string, []>("gather_171_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_171_validate_indices_0 = const()[name = tensor<string, []>("gather_171_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3189_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3189_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_171_to_uint16 = const()[name = tensor<string, []>("select_171_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3189_shape_cast_fp16_to_uint16 = cast(dtype = var_3189_shape_cast_fp16_to_uint16_dtype_0, x = var_3189_shape_cast_fp16)[name = tensor<string, []>("cast_149")];
            tensor<uint16, []> gather_171_cast_uint16 = gather(axis = gather_171_axis_0, batch_dims = gather_171_batch_dims_0, indices = select_171_to_uint16, validate_indices = gather_171_validate_indices_0, x = var_3189_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_171_cast_uint16")];
            tensor<string, []> gather_171_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_171_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_84_values0_0 = const()[name = tensor<string, []>("concat_84_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_84_values1_0 = const()[name = tensor<string, []>("concat_84_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_84_axis_0 = const()[name = tensor<string, []>("concat_84_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_84_interleave_0 = const()[name = tensor<string, []>("concat_84_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_171_cast_uint16_to_int32 = cast(dtype = gather_171_cast_uint16_to_int32_dtype_0, x = gather_171_cast_uint16)[name = tensor<string, []>("cast_148")];
            tensor<int32, [3]> concat_84 = concat(axis = concat_84_axis_0, interleave = concat_84_interleave_0, values = (concat_84_values0_0, concat_84_values1_0, gather_171_cast_uint16_to_int32))[name = tensor<string, []>("concat_84")];
            tensor<int32, [3]> var_3190_begin_0 = const()[name = tensor<string, []>("op_3190_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3190_end_mask_0 = const()[name = tensor<string, []>("op_3190_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3190_cast_fp16 = slice_by_index(begin = var_3190_begin_0, end = concat_84, end_mask = var_3190_end_mask_0, x = seg_167_cast_fp16)[name = tensor<string, []>("op_3190_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_915_cast_fp16 = add(x = var_3176_cast_fp16, y = var_3190_cast_fp16)[name = tensor<string, []>("input_915_cast_fp16")];
            tensor<string, []> input_917_pad_type_0 = const()[name = tensor<string, []>("input_917_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_917_strides_0 = const()[name = tensor<string, []>("input_917_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_917_pad_0 = const()[name = tensor<string, []>("input_917_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_917_dilations_0 = const()[name = tensor<string, []>("input_917_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_917_groups_0 = const()[name = tensor<string, []>("input_917_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd6_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd6_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9680832)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd6_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd6_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9697280)))];
            tensor<fp16, [1, 64, ?]> input_917_cast_fp16 = conv(bias = net_xvector_block3_tdnnd6_cam_layer_linear1_bias_to_fp16, dilations = input_917_dilations_0, groups = input_917_groups_0, pad = input_917_pad_0, pad_type = input_917_pad_type_0, strides = input_917_strides_0, weight = net_xvector_block3_tdnnd6_cam_layer_linear1_weight_to_fp16, x = input_915_cast_fp16)[name = tensor<string, []>("input_917_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_919_cast_fp16 = relu(x = input_917_cast_fp16)[name = tensor<string, []>("input_919_cast_fp16")];
            tensor<string, []> input_921_pad_type_0 = const()[name = tensor<string, []>("input_921_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_921_strides_0 = const()[name = tensor<string, []>("input_921_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_921_pad_0 = const()[name = tensor<string, []>("input_921_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_921_dilations_0 = const()[name = tensor<string, []>("input_921_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_921_groups_0 = const()[name = tensor<string, []>("input_921_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd6_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd6_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9697472)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd6_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd6_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9701632)))];
            tensor<fp16, [1, 32, ?]> input_921_cast_fp16 = conv(bias = net_xvector_block3_tdnnd6_cam_layer_linear2_bias_to_fp16, dilations = input_921_dilations_0, groups = input_921_groups_0, pad = input_921_pad_0, pad_type = input_921_pad_type_0, strides = input_921_strides_0, weight = net_xvector_block3_tdnnd6_cam_layer_linear2_weight_to_fp16, x = input_919_cast_fp16)[name = tensor<string, []>("input_921_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_83_cast_fp16 = sigmoid(x = input_921_cast_fp16)[name = tensor<string, []>("m_83_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3208_cast_fp16 = mul(x = y_83_cast_fp16, y = m_83_cast_fp16)[name = tensor<string, []>("op_3208_cast_fp16")];
            tensor<bool, []> input_923_interleave_0 = const()[name = tensor<string, []>("input_923_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 704, ?]> input_923_cast_fp16 = concat(axis = var_11, interleave = input_923_interleave_0, values = (input_903_cast_fp16, var_3208_cast_fp16))[name = tensor<string, []>("input_923_cast_fp16")];
            tensor<fp16, [704]> net_xvector_block3_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [704]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9701760)))];
            tensor<fp16, [704]> net_xvector_block3_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [704]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9703232)))];
            tensor<fp16, [704]> net_xvector_block3_tdnnd7_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd7_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [704]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9704704)))];
            tensor<fp16, [704]> net_xvector_block3_tdnnd7_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd7_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [704]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9706176)))];
            tensor<fp16, [1, 704, ?]> input_925_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd7_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd7_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16, x = input_923_cast_fp16)[name = tensor<string, []>("input_925_cast_fp16")];
            tensor<fp16, [1, 704, ?]> input_927_cast_fp16 = relu(x = input_925_cast_fp16)[name = tensor<string, []>("input_927_cast_fp16")];
            tensor<string, []> input_929_pad_type_0 = const()[name = tensor<string, []>("input_929_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_929_strides_0 = const()[name = tensor<string, []>("input_929_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_929_pad_0 = const()[name = tensor<string, []>("input_929_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_929_dilations_0 = const()[name = tensor<string, []>("input_929_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_929_groups_0 = const()[name = tensor<string, []>("input_929_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 704, 1]> const_110_to_fp16 = const()[name = tensor<string, []>("const_110_to_fp16"), val = tensor<fp16, [128, 704, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9707648)))];
            tensor<fp16, [128]> const_111_to_fp16 = const()[name = tensor<string, []>("const_111_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9887936)))];
            tensor<fp16, [1, 128, ?]> input_931_cast_fp16 = conv(bias = const_111_to_fp16, dilations = input_929_dilations_0, groups = input_929_groups_0, pad = input_929_pad_0, pad_type = input_929_pad_type_0, strides = input_929_strides_0, weight = const_110_to_fp16, x = input_927_cast_fp16)[name = tensor<string, []>("input_931_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_933_cast_fp16 = relu(x = input_931_cast_fp16)[name = tensor<string, []>("input_933_cast_fp16")];
            tensor<string, []> y_85_pad_type_0 = const()[name = tensor<string, []>("y_85_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_85_pad_0 = const()[name = tensor<string, []>("y_85_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_85_dilations_0 = const()[name = tensor<string, []>("y_85_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_85_strides_0 = const()[name = tensor<string, []>("y_85_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_85_groups_0 = const()[name = tensor<string, []>("y_85_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd7_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd7_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9888256)))];
            tensor<fp16, [1, 32, ?]> y_85_cast_fp16 = conv(dilations = y_85_dilations_0, groups = y_85_groups_0, pad = y_85_pad_0, pad_type = y_85_pad_type_0, strides = y_85_strides_0, weight = net_xvector_block3_tdnnd7_cam_layer_linear_local_weight_to_fp16, x = input_933_cast_fp16)[name = tensor<string, []>("y_85_cast_fp16")];
            tensor<int32, [1]> var_3245_axes_0 = const()[name = tensor<string, []>("op_3245_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3245_keep_dims_0 = const()[name = tensor<string, []>("op_3245_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3245_cast_fp16 = reduce_mean(axes = var_3245_axes_0, keep_dims = var_3245_keep_dims_0, x = input_933_cast_fp16)[name = tensor<string, []>("op_3245_cast_fp16")];
            tensor<int32, [1]> var_3246 = const()[name = tensor<string, []>("op_3246"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3247 = const()[name = tensor<string, []>("op_3247"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_169_pad_type_0 = const()[name = tensor<string, []>("seg_169_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_169_pad_0 = const()[name = tensor<string, []>("seg_169_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_169_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_169_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_169_ceil_mode_0 = const()[name = tensor<string, []>("seg_169_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_169_cast_fp16 = avg_pool(ceil_mode = seg_169_ceil_mode_0, exclude_padding_from_average = seg_169_exclude_padding_from_average_0, kernel_sizes = var_3246, pad = seg_169_pad_0, pad_type = seg_169_pad_type_0, strides = var_3247, x = input_933_cast_fp16)[name = tensor<string, []>("seg_169_cast_fp16")];
            tensor<int32, [3]> var_3250_shape_cast_fp16 = shape(x = seg_169_cast_fp16)[name = tensor<string, []>("op_3250_shape_cast_fp16")];
            tensor<int32, []> gather_172 = const()[name = tensor<string, []>("gather_172"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_173 = const()[name = tensor<string, []>("gather_173"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_174_axis_0 = const()[name = tensor<string, []>("gather_174_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_174_batch_dims_0 = const()[name = tensor<string, []>("gather_174_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_174_validate_indices_0 = const()[name = tensor<string, []>("gather_174_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3250_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3250_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_174_to_uint16 = const()[name = tensor<string, []>("select_174_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3250_shape_cast_fp16_to_uint16 = cast(dtype = var_3250_shape_cast_fp16_to_uint16_dtype_0, x = var_3250_shape_cast_fp16)[name = tensor<string, []>("cast_147")];
            tensor<uint16, []> gather_174_cast_uint16 = gather(axis = gather_174_axis_0, batch_dims = gather_174_batch_dims_0, indices = select_174_to_uint16, validate_indices = gather_174_validate_indices_0, x = var_3250_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_174_cast_uint16")];
            tensor<string, []> gather_174_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_174_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3253_axes_0 = const()[name = tensor<string, []>("op_3253_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3253_cast_fp16 = expand_dims(axes = var_3253_axes_0, x = seg_169_cast_fp16)[name = tensor<string, []>("op_3253_cast_fp16")];
            tensor<int32, []> concat_85_axis_0 = const()[name = tensor<string, []>("concat_85_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_85_interleave_0 = const()[name = tensor<string, []>("concat_85_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_174_cast_uint16_to_int32 = cast(dtype = gather_174_cast_uint16_to_int32_dtype_0, x = gather_174_cast_uint16)[name = tensor<string, []>("cast_146")];
            tensor<int32, [4]> concat_85 = concat(axis = concat_85_axis_0, interleave = concat_85_interleave_0, values = (gather_172, gather_173, gather_174_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_85")];
            tensor<int32, [4]> shape_217_cast_fp16 = shape(x = var_3253_cast_fp16)[name = tensor<string, []>("shape_217_cast_fp16")];
            tensor<int32, [4]> real_div_42 = real_div(x = concat_85, y = shape_217_cast_fp16)[name = tensor<string, []>("real_div_42")];
            tensor<fp16, [?, ?, ?, ?]> var_3255_cast_fp16 = tile(reps = real_div_42, x = var_3253_cast_fp16)[name = tensor<string, []>("op_3255_cast_fp16")];
            tensor<int32, [3]> var_3256 = const()[name = tensor<string, []>("op_3256"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_171_cast_fp16 = reshape(shape = var_3256, x = var_3255_cast_fp16)[name = tensor<string, []>("seg_171_cast_fp16")];
            tensor<int32, [3]> var_3258_shape_cast_fp16 = shape(x = input_933_cast_fp16)[name = tensor<string, []>("op_3258_shape_cast_fp16")];
            tensor<int32, []> gather_175_axis_0 = const()[name = tensor<string, []>("gather_175_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_175_batch_dims_0 = const()[name = tensor<string, []>("gather_175_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_175_validate_indices_0 = const()[name = tensor<string, []>("gather_175_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3258_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3258_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_175_to_uint16 = const()[name = tensor<string, []>("select_175_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3258_shape_cast_fp16_to_uint16 = cast(dtype = var_3258_shape_cast_fp16_to_uint16_dtype_0, x = var_3258_shape_cast_fp16)[name = tensor<string, []>("cast_145")];
            tensor<uint16, []> gather_175_cast_uint16 = gather(axis = gather_175_axis_0, batch_dims = gather_175_batch_dims_0, indices = select_175_to_uint16, validate_indices = gather_175_validate_indices_0, x = var_3258_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_175_cast_uint16")];
            tensor<string, []> gather_175_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_175_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_86_values0_0 = const()[name = tensor<string, []>("concat_86_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_86_values1_0 = const()[name = tensor<string, []>("concat_86_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_86_axis_0 = const()[name = tensor<string, []>("concat_86_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_86_interleave_0 = const()[name = tensor<string, []>("concat_86_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_175_cast_uint16_to_int32 = cast(dtype = gather_175_cast_uint16_to_int32_dtype_0, x = gather_175_cast_uint16)[name = tensor<string, []>("cast_144")];
            tensor<int32, [3]> concat_86 = concat(axis = concat_86_axis_0, interleave = concat_86_interleave_0, values = (concat_86_values0_0, concat_86_values1_0, gather_175_cast_uint16_to_int32))[name = tensor<string, []>("concat_86")];
            tensor<int32, [3]> var_3259_begin_0 = const()[name = tensor<string, []>("op_3259_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3259_end_mask_0 = const()[name = tensor<string, []>("op_3259_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3259_cast_fp16 = slice_by_index(begin = var_3259_begin_0, end = concat_86, end_mask = var_3259_end_mask_0, x = seg_171_cast_fp16)[name = tensor<string, []>("op_3259_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_935_cast_fp16 = add(x = var_3245_cast_fp16, y = var_3259_cast_fp16)[name = tensor<string, []>("input_935_cast_fp16")];
            tensor<string, []> input_937_pad_type_0 = const()[name = tensor<string, []>("input_937_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_937_strides_0 = const()[name = tensor<string, []>("input_937_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_937_pad_0 = const()[name = tensor<string, []>("input_937_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_937_dilations_0 = const()[name = tensor<string, []>("input_937_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_937_groups_0 = const()[name = tensor<string, []>("input_937_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd7_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd7_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9912896)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd7_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd7_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9929344)))];
            tensor<fp16, [1, 64, ?]> input_937_cast_fp16 = conv(bias = net_xvector_block3_tdnnd7_cam_layer_linear1_bias_to_fp16, dilations = input_937_dilations_0, groups = input_937_groups_0, pad = input_937_pad_0, pad_type = input_937_pad_type_0, strides = input_937_strides_0, weight = net_xvector_block3_tdnnd7_cam_layer_linear1_weight_to_fp16, x = input_935_cast_fp16)[name = tensor<string, []>("input_937_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_939_cast_fp16 = relu(x = input_937_cast_fp16)[name = tensor<string, []>("input_939_cast_fp16")];
            tensor<string, []> input_941_pad_type_0 = const()[name = tensor<string, []>("input_941_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_941_strides_0 = const()[name = tensor<string, []>("input_941_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_941_pad_0 = const()[name = tensor<string, []>("input_941_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_941_dilations_0 = const()[name = tensor<string, []>("input_941_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_941_groups_0 = const()[name = tensor<string, []>("input_941_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd7_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd7_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9929536)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd7_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd7_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9933696)))];
            tensor<fp16, [1, 32, ?]> input_941_cast_fp16 = conv(bias = net_xvector_block3_tdnnd7_cam_layer_linear2_bias_to_fp16, dilations = input_941_dilations_0, groups = input_941_groups_0, pad = input_941_pad_0, pad_type = input_941_pad_type_0, strides = input_941_strides_0, weight = net_xvector_block3_tdnnd7_cam_layer_linear2_weight_to_fp16, x = input_939_cast_fp16)[name = tensor<string, []>("input_941_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_85_cast_fp16 = sigmoid(x = input_941_cast_fp16)[name = tensor<string, []>("m_85_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3277_cast_fp16 = mul(x = y_85_cast_fp16, y = m_85_cast_fp16)[name = tensor<string, []>("op_3277_cast_fp16")];
            tensor<bool, []> input_943_interleave_0 = const()[name = tensor<string, []>("input_943_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 736, ?]> input_943_cast_fp16 = concat(axis = var_11, interleave = input_943_interleave_0, values = (input_923_cast_fp16, var_3277_cast_fp16))[name = tensor<string, []>("input_943_cast_fp16")];
            tensor<fp16, [736]> net_xvector_block3_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [736]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9933824)))];
            tensor<fp16, [736]> net_xvector_block3_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [736]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9935360)))];
            tensor<fp16, [736]> net_xvector_block3_tdnnd8_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd8_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [736]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9936896)))];
            tensor<fp16, [736]> net_xvector_block3_tdnnd8_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd8_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [736]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9938432)))];
            tensor<fp16, [1, 736, ?]> input_945_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd8_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd8_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16, x = input_943_cast_fp16)[name = tensor<string, []>("input_945_cast_fp16")];
            tensor<fp16, [1, 736, ?]> input_947_cast_fp16 = relu(x = input_945_cast_fp16)[name = tensor<string, []>("input_947_cast_fp16")];
            tensor<string, []> input_949_pad_type_0 = const()[name = tensor<string, []>("input_949_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_949_strides_0 = const()[name = tensor<string, []>("input_949_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_949_pad_0 = const()[name = tensor<string, []>("input_949_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_949_dilations_0 = const()[name = tensor<string, []>("input_949_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_949_groups_0 = const()[name = tensor<string, []>("input_949_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 736, 1]> const_112_to_fp16 = const()[name = tensor<string, []>("const_112_to_fp16"), val = tensor<fp16, [128, 736, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9939968)))];
            tensor<fp16, [128]> const_113_to_fp16 = const()[name = tensor<string, []>("const_113_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10128448)))];
            tensor<fp16, [1, 128, ?]> input_951_cast_fp16 = conv(bias = const_113_to_fp16, dilations = input_949_dilations_0, groups = input_949_groups_0, pad = input_949_pad_0, pad_type = input_949_pad_type_0, strides = input_949_strides_0, weight = const_112_to_fp16, x = input_947_cast_fp16)[name = tensor<string, []>("input_951_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_953_cast_fp16 = relu(x = input_951_cast_fp16)[name = tensor<string, []>("input_953_cast_fp16")];
            tensor<string, []> y_87_pad_type_0 = const()[name = tensor<string, []>("y_87_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_87_pad_0 = const()[name = tensor<string, []>("y_87_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_87_dilations_0 = const()[name = tensor<string, []>("y_87_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_87_strides_0 = const()[name = tensor<string, []>("y_87_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_87_groups_0 = const()[name = tensor<string, []>("y_87_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd8_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd8_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10128768)))];
            tensor<fp16, [1, 32, ?]> y_87_cast_fp16 = conv(dilations = y_87_dilations_0, groups = y_87_groups_0, pad = y_87_pad_0, pad_type = y_87_pad_type_0, strides = y_87_strides_0, weight = net_xvector_block3_tdnnd8_cam_layer_linear_local_weight_to_fp16, x = input_953_cast_fp16)[name = tensor<string, []>("y_87_cast_fp16")];
            tensor<int32, [1]> var_3314_axes_0 = const()[name = tensor<string, []>("op_3314_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3314_keep_dims_0 = const()[name = tensor<string, []>("op_3314_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3314_cast_fp16 = reduce_mean(axes = var_3314_axes_0, keep_dims = var_3314_keep_dims_0, x = input_953_cast_fp16)[name = tensor<string, []>("op_3314_cast_fp16")];
            tensor<int32, [1]> var_3315 = const()[name = tensor<string, []>("op_3315"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3316 = const()[name = tensor<string, []>("op_3316"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_173_pad_type_0 = const()[name = tensor<string, []>("seg_173_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_173_pad_0 = const()[name = tensor<string, []>("seg_173_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_173_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_173_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_173_ceil_mode_0 = const()[name = tensor<string, []>("seg_173_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_173_cast_fp16 = avg_pool(ceil_mode = seg_173_ceil_mode_0, exclude_padding_from_average = seg_173_exclude_padding_from_average_0, kernel_sizes = var_3315, pad = seg_173_pad_0, pad_type = seg_173_pad_type_0, strides = var_3316, x = input_953_cast_fp16)[name = tensor<string, []>("seg_173_cast_fp16")];
            tensor<int32, [3]> var_3319_shape_cast_fp16 = shape(x = seg_173_cast_fp16)[name = tensor<string, []>("op_3319_shape_cast_fp16")];
            tensor<int32, []> gather_176 = const()[name = tensor<string, []>("gather_176"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_177 = const()[name = tensor<string, []>("gather_177"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_178_axis_0 = const()[name = tensor<string, []>("gather_178_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_178_batch_dims_0 = const()[name = tensor<string, []>("gather_178_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_178_validate_indices_0 = const()[name = tensor<string, []>("gather_178_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3319_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3319_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_178_to_uint16 = const()[name = tensor<string, []>("select_178_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3319_shape_cast_fp16_to_uint16 = cast(dtype = var_3319_shape_cast_fp16_to_uint16_dtype_0, x = var_3319_shape_cast_fp16)[name = tensor<string, []>("cast_143")];
            tensor<uint16, []> gather_178_cast_uint16 = gather(axis = gather_178_axis_0, batch_dims = gather_178_batch_dims_0, indices = select_178_to_uint16, validate_indices = gather_178_validate_indices_0, x = var_3319_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_178_cast_uint16")];
            tensor<string, []> gather_178_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_178_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3322_axes_0 = const()[name = tensor<string, []>("op_3322_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3322_cast_fp16 = expand_dims(axes = var_3322_axes_0, x = seg_173_cast_fp16)[name = tensor<string, []>("op_3322_cast_fp16")];
            tensor<int32, []> concat_87_axis_0 = const()[name = tensor<string, []>("concat_87_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_87_interleave_0 = const()[name = tensor<string, []>("concat_87_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_178_cast_uint16_to_int32 = cast(dtype = gather_178_cast_uint16_to_int32_dtype_0, x = gather_178_cast_uint16)[name = tensor<string, []>("cast_142")];
            tensor<int32, [4]> concat_87 = concat(axis = concat_87_axis_0, interleave = concat_87_interleave_0, values = (gather_176, gather_177, gather_178_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_87")];
            tensor<int32, [4]> shape_222_cast_fp16 = shape(x = var_3322_cast_fp16)[name = tensor<string, []>("shape_222_cast_fp16")];
            tensor<int32, [4]> real_div_43 = real_div(x = concat_87, y = shape_222_cast_fp16)[name = tensor<string, []>("real_div_43")];
            tensor<fp16, [?, ?, ?, ?]> var_3324_cast_fp16 = tile(reps = real_div_43, x = var_3322_cast_fp16)[name = tensor<string, []>("op_3324_cast_fp16")];
            tensor<int32, [3]> var_3325 = const()[name = tensor<string, []>("op_3325"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_175_cast_fp16 = reshape(shape = var_3325, x = var_3324_cast_fp16)[name = tensor<string, []>("seg_175_cast_fp16")];
            tensor<int32, [3]> var_3327_shape_cast_fp16 = shape(x = input_953_cast_fp16)[name = tensor<string, []>("op_3327_shape_cast_fp16")];
            tensor<int32, []> gather_179_axis_0 = const()[name = tensor<string, []>("gather_179_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_179_batch_dims_0 = const()[name = tensor<string, []>("gather_179_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_179_validate_indices_0 = const()[name = tensor<string, []>("gather_179_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3327_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3327_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_179_to_uint16 = const()[name = tensor<string, []>("select_179_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3327_shape_cast_fp16_to_uint16 = cast(dtype = var_3327_shape_cast_fp16_to_uint16_dtype_0, x = var_3327_shape_cast_fp16)[name = tensor<string, []>("cast_141")];
            tensor<uint16, []> gather_179_cast_uint16 = gather(axis = gather_179_axis_0, batch_dims = gather_179_batch_dims_0, indices = select_179_to_uint16, validate_indices = gather_179_validate_indices_0, x = var_3327_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_179_cast_uint16")];
            tensor<string, []> gather_179_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_179_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_88_values0_0 = const()[name = tensor<string, []>("concat_88_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_88_values1_0 = const()[name = tensor<string, []>("concat_88_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_88_axis_0 = const()[name = tensor<string, []>("concat_88_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_88_interleave_0 = const()[name = tensor<string, []>("concat_88_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_179_cast_uint16_to_int32 = cast(dtype = gather_179_cast_uint16_to_int32_dtype_0, x = gather_179_cast_uint16)[name = tensor<string, []>("cast_140")];
            tensor<int32, [3]> concat_88 = concat(axis = concat_88_axis_0, interleave = concat_88_interleave_0, values = (concat_88_values0_0, concat_88_values1_0, gather_179_cast_uint16_to_int32))[name = tensor<string, []>("concat_88")];
            tensor<int32, [3]> var_3328_begin_0 = const()[name = tensor<string, []>("op_3328_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3328_end_mask_0 = const()[name = tensor<string, []>("op_3328_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3328_cast_fp16 = slice_by_index(begin = var_3328_begin_0, end = concat_88, end_mask = var_3328_end_mask_0, x = seg_175_cast_fp16)[name = tensor<string, []>("op_3328_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_955_cast_fp16 = add(x = var_3314_cast_fp16, y = var_3328_cast_fp16)[name = tensor<string, []>("input_955_cast_fp16")];
            tensor<string, []> input_957_pad_type_0 = const()[name = tensor<string, []>("input_957_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_957_strides_0 = const()[name = tensor<string, []>("input_957_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_957_pad_0 = const()[name = tensor<string, []>("input_957_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_957_dilations_0 = const()[name = tensor<string, []>("input_957_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_957_groups_0 = const()[name = tensor<string, []>("input_957_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd8_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd8_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10153408)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd8_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd8_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10169856)))];
            tensor<fp16, [1, 64, ?]> input_957_cast_fp16 = conv(bias = net_xvector_block3_tdnnd8_cam_layer_linear1_bias_to_fp16, dilations = input_957_dilations_0, groups = input_957_groups_0, pad = input_957_pad_0, pad_type = input_957_pad_type_0, strides = input_957_strides_0, weight = net_xvector_block3_tdnnd8_cam_layer_linear1_weight_to_fp16, x = input_955_cast_fp16)[name = tensor<string, []>("input_957_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_959_cast_fp16 = relu(x = input_957_cast_fp16)[name = tensor<string, []>("input_959_cast_fp16")];
            tensor<string, []> input_961_pad_type_0 = const()[name = tensor<string, []>("input_961_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_961_strides_0 = const()[name = tensor<string, []>("input_961_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_961_pad_0 = const()[name = tensor<string, []>("input_961_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_961_dilations_0 = const()[name = tensor<string, []>("input_961_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_961_groups_0 = const()[name = tensor<string, []>("input_961_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd8_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd8_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10170048)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd8_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd8_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10174208)))];
            tensor<fp16, [1, 32, ?]> input_961_cast_fp16 = conv(bias = net_xvector_block3_tdnnd8_cam_layer_linear2_bias_to_fp16, dilations = input_961_dilations_0, groups = input_961_groups_0, pad = input_961_pad_0, pad_type = input_961_pad_type_0, strides = input_961_strides_0, weight = net_xvector_block3_tdnnd8_cam_layer_linear2_weight_to_fp16, x = input_959_cast_fp16)[name = tensor<string, []>("input_961_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_87_cast_fp16 = sigmoid(x = input_961_cast_fp16)[name = tensor<string, []>("m_87_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3346_cast_fp16 = mul(x = y_87_cast_fp16, y = m_87_cast_fp16)[name = tensor<string, []>("op_3346_cast_fp16")];
            tensor<bool, []> input_963_interleave_0 = const()[name = tensor<string, []>("input_963_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 768, ?]> input_963_cast_fp16 = concat(axis = var_11, interleave = input_963_interleave_0, values = (input_943_cast_fp16, var_3346_cast_fp16))[name = tensor<string, []>("input_963_cast_fp16")];
            tensor<fp16, [768]> net_xvector_block3_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10174336)))];
            tensor<fp16, [768]> net_xvector_block3_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10175936)))];
            tensor<fp16, [768]> net_xvector_block3_tdnnd9_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd9_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10177536)))];
            tensor<fp16, [768]> net_xvector_block3_tdnnd9_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd9_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10179136)))];
            tensor<fp16, [1, 768, ?]> input_965_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd9_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd9_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16, x = input_963_cast_fp16)[name = tensor<string, []>("input_965_cast_fp16")];
            tensor<fp16, [1, 768, ?]> input_967_cast_fp16 = relu(x = input_965_cast_fp16)[name = tensor<string, []>("input_967_cast_fp16")];
            tensor<string, []> input_969_pad_type_0 = const()[name = tensor<string, []>("input_969_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_969_strides_0 = const()[name = tensor<string, []>("input_969_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_969_pad_0 = const()[name = tensor<string, []>("input_969_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_969_dilations_0 = const()[name = tensor<string, []>("input_969_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_969_groups_0 = const()[name = tensor<string, []>("input_969_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 768, 1]> const_114_to_fp16 = const()[name = tensor<string, []>("const_114_to_fp16"), val = tensor<fp16, [128, 768, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10180736)))];
            tensor<fp16, [128]> const_115_to_fp16 = const()[name = tensor<string, []>("const_115_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10377408)))];
            tensor<fp16, [1, 128, ?]> input_971_cast_fp16 = conv(bias = const_115_to_fp16, dilations = input_969_dilations_0, groups = input_969_groups_0, pad = input_969_pad_0, pad_type = input_969_pad_type_0, strides = input_969_strides_0, weight = const_114_to_fp16, x = input_967_cast_fp16)[name = tensor<string, []>("input_971_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_973_cast_fp16 = relu(x = input_971_cast_fp16)[name = tensor<string, []>("input_973_cast_fp16")];
            tensor<string, []> y_89_pad_type_0 = const()[name = tensor<string, []>("y_89_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_89_pad_0 = const()[name = tensor<string, []>("y_89_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_89_dilations_0 = const()[name = tensor<string, []>("y_89_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_89_strides_0 = const()[name = tensor<string, []>("y_89_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_89_groups_0 = const()[name = tensor<string, []>("y_89_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd9_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd9_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10377728)))];
            tensor<fp16, [1, 32, ?]> y_89_cast_fp16 = conv(dilations = y_89_dilations_0, groups = y_89_groups_0, pad = y_89_pad_0, pad_type = y_89_pad_type_0, strides = y_89_strides_0, weight = net_xvector_block3_tdnnd9_cam_layer_linear_local_weight_to_fp16, x = input_973_cast_fp16)[name = tensor<string, []>("y_89_cast_fp16")];
            tensor<int32, [1]> var_3383_axes_0 = const()[name = tensor<string, []>("op_3383_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3383_keep_dims_0 = const()[name = tensor<string, []>("op_3383_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3383_cast_fp16 = reduce_mean(axes = var_3383_axes_0, keep_dims = var_3383_keep_dims_0, x = input_973_cast_fp16)[name = tensor<string, []>("op_3383_cast_fp16")];
            tensor<int32, [1]> var_3384 = const()[name = tensor<string, []>("op_3384"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3385 = const()[name = tensor<string, []>("op_3385"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_177_pad_type_0 = const()[name = tensor<string, []>("seg_177_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_177_pad_0 = const()[name = tensor<string, []>("seg_177_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_177_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_177_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_177_ceil_mode_0 = const()[name = tensor<string, []>("seg_177_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_177_cast_fp16 = avg_pool(ceil_mode = seg_177_ceil_mode_0, exclude_padding_from_average = seg_177_exclude_padding_from_average_0, kernel_sizes = var_3384, pad = seg_177_pad_0, pad_type = seg_177_pad_type_0, strides = var_3385, x = input_973_cast_fp16)[name = tensor<string, []>("seg_177_cast_fp16")];
            tensor<int32, [3]> var_3388_shape_cast_fp16 = shape(x = seg_177_cast_fp16)[name = tensor<string, []>("op_3388_shape_cast_fp16")];
            tensor<int32, []> gather_180 = const()[name = tensor<string, []>("gather_180"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_181 = const()[name = tensor<string, []>("gather_181"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_182_axis_0 = const()[name = tensor<string, []>("gather_182_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_182_batch_dims_0 = const()[name = tensor<string, []>("gather_182_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_182_validate_indices_0 = const()[name = tensor<string, []>("gather_182_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3388_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3388_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_182_to_uint16 = const()[name = tensor<string, []>("select_182_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3388_shape_cast_fp16_to_uint16 = cast(dtype = var_3388_shape_cast_fp16_to_uint16_dtype_0, x = var_3388_shape_cast_fp16)[name = tensor<string, []>("cast_139")];
            tensor<uint16, []> gather_182_cast_uint16 = gather(axis = gather_182_axis_0, batch_dims = gather_182_batch_dims_0, indices = select_182_to_uint16, validate_indices = gather_182_validate_indices_0, x = var_3388_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_182_cast_uint16")];
            tensor<string, []> gather_182_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_182_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3391_axes_0 = const()[name = tensor<string, []>("op_3391_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3391_cast_fp16 = expand_dims(axes = var_3391_axes_0, x = seg_177_cast_fp16)[name = tensor<string, []>("op_3391_cast_fp16")];
            tensor<int32, []> concat_89_axis_0 = const()[name = tensor<string, []>("concat_89_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_89_interleave_0 = const()[name = tensor<string, []>("concat_89_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_182_cast_uint16_to_int32 = cast(dtype = gather_182_cast_uint16_to_int32_dtype_0, x = gather_182_cast_uint16)[name = tensor<string, []>("cast_138")];
            tensor<int32, [4]> concat_89 = concat(axis = concat_89_axis_0, interleave = concat_89_interleave_0, values = (gather_180, gather_181, gather_182_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_89")];
            tensor<int32, [4]> shape_227_cast_fp16 = shape(x = var_3391_cast_fp16)[name = tensor<string, []>("shape_227_cast_fp16")];
            tensor<int32, [4]> real_div_44 = real_div(x = concat_89, y = shape_227_cast_fp16)[name = tensor<string, []>("real_div_44")];
            tensor<fp16, [?, ?, ?, ?]> var_3393_cast_fp16 = tile(reps = real_div_44, x = var_3391_cast_fp16)[name = tensor<string, []>("op_3393_cast_fp16")];
            tensor<int32, [3]> var_3394 = const()[name = tensor<string, []>("op_3394"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_179_cast_fp16 = reshape(shape = var_3394, x = var_3393_cast_fp16)[name = tensor<string, []>("seg_179_cast_fp16")];
            tensor<int32, [3]> var_3396_shape_cast_fp16 = shape(x = input_973_cast_fp16)[name = tensor<string, []>("op_3396_shape_cast_fp16")];
            tensor<int32, []> gather_183_axis_0 = const()[name = tensor<string, []>("gather_183_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_183_batch_dims_0 = const()[name = tensor<string, []>("gather_183_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_183_validate_indices_0 = const()[name = tensor<string, []>("gather_183_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3396_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3396_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_183_to_uint16 = const()[name = tensor<string, []>("select_183_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3396_shape_cast_fp16_to_uint16 = cast(dtype = var_3396_shape_cast_fp16_to_uint16_dtype_0, x = var_3396_shape_cast_fp16)[name = tensor<string, []>("cast_137")];
            tensor<uint16, []> gather_183_cast_uint16 = gather(axis = gather_183_axis_0, batch_dims = gather_183_batch_dims_0, indices = select_183_to_uint16, validate_indices = gather_183_validate_indices_0, x = var_3396_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_183_cast_uint16")];
            tensor<string, []> gather_183_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_183_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_90_values0_0 = const()[name = tensor<string, []>("concat_90_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_90_values1_0 = const()[name = tensor<string, []>("concat_90_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_90_axis_0 = const()[name = tensor<string, []>("concat_90_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_90_interleave_0 = const()[name = tensor<string, []>("concat_90_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_183_cast_uint16_to_int32 = cast(dtype = gather_183_cast_uint16_to_int32_dtype_0, x = gather_183_cast_uint16)[name = tensor<string, []>("cast_136")];
            tensor<int32, [3]> concat_90 = concat(axis = concat_90_axis_0, interleave = concat_90_interleave_0, values = (concat_90_values0_0, concat_90_values1_0, gather_183_cast_uint16_to_int32))[name = tensor<string, []>("concat_90")];
            tensor<int32, [3]> var_3397_begin_0 = const()[name = tensor<string, []>("op_3397_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3397_end_mask_0 = const()[name = tensor<string, []>("op_3397_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3397_cast_fp16 = slice_by_index(begin = var_3397_begin_0, end = concat_90, end_mask = var_3397_end_mask_0, x = seg_179_cast_fp16)[name = tensor<string, []>("op_3397_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_975_cast_fp16 = add(x = var_3383_cast_fp16, y = var_3397_cast_fp16)[name = tensor<string, []>("input_975_cast_fp16")];
            tensor<string, []> input_977_pad_type_0 = const()[name = tensor<string, []>("input_977_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_977_strides_0 = const()[name = tensor<string, []>("input_977_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_977_pad_0 = const()[name = tensor<string, []>("input_977_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_977_dilations_0 = const()[name = tensor<string, []>("input_977_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_977_groups_0 = const()[name = tensor<string, []>("input_977_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd9_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd9_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10402368)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd9_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd9_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10418816)))];
            tensor<fp16, [1, 64, ?]> input_977_cast_fp16 = conv(bias = net_xvector_block3_tdnnd9_cam_layer_linear1_bias_to_fp16, dilations = input_977_dilations_0, groups = input_977_groups_0, pad = input_977_pad_0, pad_type = input_977_pad_type_0, strides = input_977_strides_0, weight = net_xvector_block3_tdnnd9_cam_layer_linear1_weight_to_fp16, x = input_975_cast_fp16)[name = tensor<string, []>("input_977_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_979_cast_fp16 = relu(x = input_977_cast_fp16)[name = tensor<string, []>("input_979_cast_fp16")];
            tensor<string, []> input_981_pad_type_0 = const()[name = tensor<string, []>("input_981_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_981_strides_0 = const()[name = tensor<string, []>("input_981_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_981_pad_0 = const()[name = tensor<string, []>("input_981_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_981_dilations_0 = const()[name = tensor<string, []>("input_981_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_981_groups_0 = const()[name = tensor<string, []>("input_981_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd9_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd9_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10419008)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd9_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd9_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10423168)))];
            tensor<fp16, [1, 32, ?]> input_981_cast_fp16 = conv(bias = net_xvector_block3_tdnnd9_cam_layer_linear2_bias_to_fp16, dilations = input_981_dilations_0, groups = input_981_groups_0, pad = input_981_pad_0, pad_type = input_981_pad_type_0, strides = input_981_strides_0, weight = net_xvector_block3_tdnnd9_cam_layer_linear2_weight_to_fp16, x = input_979_cast_fp16)[name = tensor<string, []>("input_981_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_89_cast_fp16 = sigmoid(x = input_981_cast_fp16)[name = tensor<string, []>("m_89_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3415_cast_fp16 = mul(x = y_89_cast_fp16, y = m_89_cast_fp16)[name = tensor<string, []>("op_3415_cast_fp16")];
            tensor<bool, []> input_983_interleave_0 = const()[name = tensor<string, []>("input_983_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 800, ?]> input_983_cast_fp16 = concat(axis = var_11, interleave = input_983_interleave_0, values = (input_963_cast_fp16, var_3415_cast_fp16))[name = tensor<string, []>("input_983_cast_fp16")];
            tensor<fp16, [800]> net_xvector_block3_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10423296)))];
            tensor<fp16, [800]> net_xvector_block3_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10424960)))];
            tensor<fp16, [800]> net_xvector_block3_tdnnd10_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd10_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10426624)))];
            tensor<fp16, [800]> net_xvector_block3_tdnnd10_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd10_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [800]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10428288)))];
            tensor<fp16, [1, 800, ?]> input_985_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd10_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd10_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16, x = input_983_cast_fp16)[name = tensor<string, []>("input_985_cast_fp16")];
            tensor<fp16, [1, 800, ?]> input_987_cast_fp16 = relu(x = input_985_cast_fp16)[name = tensor<string, []>("input_987_cast_fp16")];
            tensor<string, []> input_989_pad_type_0 = const()[name = tensor<string, []>("input_989_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_989_strides_0 = const()[name = tensor<string, []>("input_989_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_989_pad_0 = const()[name = tensor<string, []>("input_989_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_989_dilations_0 = const()[name = tensor<string, []>("input_989_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_989_groups_0 = const()[name = tensor<string, []>("input_989_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 800, 1]> const_116_to_fp16 = const()[name = tensor<string, []>("const_116_to_fp16"), val = tensor<fp16, [128, 800, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10429952)))];
            tensor<fp16, [128]> const_117_to_fp16 = const()[name = tensor<string, []>("const_117_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10634816)))];
            tensor<fp16, [1, 128, ?]> input_991_cast_fp16 = conv(bias = const_117_to_fp16, dilations = input_989_dilations_0, groups = input_989_groups_0, pad = input_989_pad_0, pad_type = input_989_pad_type_0, strides = input_989_strides_0, weight = const_116_to_fp16, x = input_987_cast_fp16)[name = tensor<string, []>("input_991_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_993_cast_fp16 = relu(x = input_991_cast_fp16)[name = tensor<string, []>("input_993_cast_fp16")];
            tensor<string, []> y_91_pad_type_0 = const()[name = tensor<string, []>("y_91_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_91_pad_0 = const()[name = tensor<string, []>("y_91_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_91_dilations_0 = const()[name = tensor<string, []>("y_91_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_91_strides_0 = const()[name = tensor<string, []>("y_91_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_91_groups_0 = const()[name = tensor<string, []>("y_91_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd10_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd10_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10635136)))];
            tensor<fp16, [1, 32, ?]> y_91_cast_fp16 = conv(dilations = y_91_dilations_0, groups = y_91_groups_0, pad = y_91_pad_0, pad_type = y_91_pad_type_0, strides = y_91_strides_0, weight = net_xvector_block3_tdnnd10_cam_layer_linear_local_weight_to_fp16, x = input_993_cast_fp16)[name = tensor<string, []>("y_91_cast_fp16")];
            tensor<int32, [1]> var_3452_axes_0 = const()[name = tensor<string, []>("op_3452_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3452_keep_dims_0 = const()[name = tensor<string, []>("op_3452_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3452_cast_fp16 = reduce_mean(axes = var_3452_axes_0, keep_dims = var_3452_keep_dims_0, x = input_993_cast_fp16)[name = tensor<string, []>("op_3452_cast_fp16")];
            tensor<int32, [1]> var_3453 = const()[name = tensor<string, []>("op_3453"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3454 = const()[name = tensor<string, []>("op_3454"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_181_pad_type_0 = const()[name = tensor<string, []>("seg_181_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_181_pad_0 = const()[name = tensor<string, []>("seg_181_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_181_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_181_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_181_ceil_mode_0 = const()[name = tensor<string, []>("seg_181_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_181_cast_fp16 = avg_pool(ceil_mode = seg_181_ceil_mode_0, exclude_padding_from_average = seg_181_exclude_padding_from_average_0, kernel_sizes = var_3453, pad = seg_181_pad_0, pad_type = seg_181_pad_type_0, strides = var_3454, x = input_993_cast_fp16)[name = tensor<string, []>("seg_181_cast_fp16")];
            tensor<int32, [3]> var_3457_shape_cast_fp16 = shape(x = seg_181_cast_fp16)[name = tensor<string, []>("op_3457_shape_cast_fp16")];
            tensor<int32, []> gather_184 = const()[name = tensor<string, []>("gather_184"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_185 = const()[name = tensor<string, []>("gather_185"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_186_axis_0 = const()[name = tensor<string, []>("gather_186_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_186_batch_dims_0 = const()[name = tensor<string, []>("gather_186_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_186_validate_indices_0 = const()[name = tensor<string, []>("gather_186_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3457_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3457_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_186_to_uint16 = const()[name = tensor<string, []>("select_186_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3457_shape_cast_fp16_to_uint16 = cast(dtype = var_3457_shape_cast_fp16_to_uint16_dtype_0, x = var_3457_shape_cast_fp16)[name = tensor<string, []>("cast_135")];
            tensor<uint16, []> gather_186_cast_uint16 = gather(axis = gather_186_axis_0, batch_dims = gather_186_batch_dims_0, indices = select_186_to_uint16, validate_indices = gather_186_validate_indices_0, x = var_3457_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_186_cast_uint16")];
            tensor<string, []> gather_186_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_186_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3460_axes_0 = const()[name = tensor<string, []>("op_3460_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3460_cast_fp16 = expand_dims(axes = var_3460_axes_0, x = seg_181_cast_fp16)[name = tensor<string, []>("op_3460_cast_fp16")];
            tensor<int32, []> concat_91_axis_0 = const()[name = tensor<string, []>("concat_91_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_91_interleave_0 = const()[name = tensor<string, []>("concat_91_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_186_cast_uint16_to_int32 = cast(dtype = gather_186_cast_uint16_to_int32_dtype_0, x = gather_186_cast_uint16)[name = tensor<string, []>("cast_134")];
            tensor<int32, [4]> concat_91 = concat(axis = concat_91_axis_0, interleave = concat_91_interleave_0, values = (gather_184, gather_185, gather_186_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_91")];
            tensor<int32, [4]> shape_232_cast_fp16 = shape(x = var_3460_cast_fp16)[name = tensor<string, []>("shape_232_cast_fp16")];
            tensor<int32, [4]> real_div_45 = real_div(x = concat_91, y = shape_232_cast_fp16)[name = tensor<string, []>("real_div_45")];
            tensor<fp16, [?, ?, ?, ?]> var_3462_cast_fp16 = tile(reps = real_div_45, x = var_3460_cast_fp16)[name = tensor<string, []>("op_3462_cast_fp16")];
            tensor<int32, [3]> var_3463 = const()[name = tensor<string, []>("op_3463"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_183_cast_fp16 = reshape(shape = var_3463, x = var_3462_cast_fp16)[name = tensor<string, []>("seg_183_cast_fp16")];
            tensor<int32, [3]> var_3465_shape_cast_fp16 = shape(x = input_993_cast_fp16)[name = tensor<string, []>("op_3465_shape_cast_fp16")];
            tensor<int32, []> gather_187_axis_0 = const()[name = tensor<string, []>("gather_187_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_187_batch_dims_0 = const()[name = tensor<string, []>("gather_187_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_187_validate_indices_0 = const()[name = tensor<string, []>("gather_187_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3465_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3465_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_187_to_uint16 = const()[name = tensor<string, []>("select_187_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3465_shape_cast_fp16_to_uint16 = cast(dtype = var_3465_shape_cast_fp16_to_uint16_dtype_0, x = var_3465_shape_cast_fp16)[name = tensor<string, []>("cast_133")];
            tensor<uint16, []> gather_187_cast_uint16 = gather(axis = gather_187_axis_0, batch_dims = gather_187_batch_dims_0, indices = select_187_to_uint16, validate_indices = gather_187_validate_indices_0, x = var_3465_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_187_cast_uint16")];
            tensor<string, []> gather_187_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_187_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_92_values0_0 = const()[name = tensor<string, []>("concat_92_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_92_values1_0 = const()[name = tensor<string, []>("concat_92_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_92_axis_0 = const()[name = tensor<string, []>("concat_92_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_92_interleave_0 = const()[name = tensor<string, []>("concat_92_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_187_cast_uint16_to_int32 = cast(dtype = gather_187_cast_uint16_to_int32_dtype_0, x = gather_187_cast_uint16)[name = tensor<string, []>("cast_132")];
            tensor<int32, [3]> concat_92 = concat(axis = concat_92_axis_0, interleave = concat_92_interleave_0, values = (concat_92_values0_0, concat_92_values1_0, gather_187_cast_uint16_to_int32))[name = tensor<string, []>("concat_92")];
            tensor<int32, [3]> var_3466_begin_0 = const()[name = tensor<string, []>("op_3466_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3466_end_mask_0 = const()[name = tensor<string, []>("op_3466_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3466_cast_fp16 = slice_by_index(begin = var_3466_begin_0, end = concat_92, end_mask = var_3466_end_mask_0, x = seg_183_cast_fp16)[name = tensor<string, []>("op_3466_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_995_cast_fp16 = add(x = var_3452_cast_fp16, y = var_3466_cast_fp16)[name = tensor<string, []>("input_995_cast_fp16")];
            tensor<string, []> input_997_pad_type_0 = const()[name = tensor<string, []>("input_997_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_997_strides_0 = const()[name = tensor<string, []>("input_997_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_997_pad_0 = const()[name = tensor<string, []>("input_997_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_997_dilations_0 = const()[name = tensor<string, []>("input_997_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_997_groups_0 = const()[name = tensor<string, []>("input_997_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd10_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd10_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10659776)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd10_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd10_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10676224)))];
            tensor<fp16, [1, 64, ?]> input_997_cast_fp16 = conv(bias = net_xvector_block3_tdnnd10_cam_layer_linear1_bias_to_fp16, dilations = input_997_dilations_0, groups = input_997_groups_0, pad = input_997_pad_0, pad_type = input_997_pad_type_0, strides = input_997_strides_0, weight = net_xvector_block3_tdnnd10_cam_layer_linear1_weight_to_fp16, x = input_995_cast_fp16)[name = tensor<string, []>("input_997_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_999_cast_fp16 = relu(x = input_997_cast_fp16)[name = tensor<string, []>("input_999_cast_fp16")];
            tensor<string, []> input_1001_pad_type_0 = const()[name = tensor<string, []>("input_1001_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1001_strides_0 = const()[name = tensor<string, []>("input_1001_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1001_pad_0 = const()[name = tensor<string, []>("input_1001_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1001_dilations_0 = const()[name = tensor<string, []>("input_1001_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1001_groups_0 = const()[name = tensor<string, []>("input_1001_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd10_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd10_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10676416)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd10_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd10_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10680576)))];
            tensor<fp16, [1, 32, ?]> input_1001_cast_fp16 = conv(bias = net_xvector_block3_tdnnd10_cam_layer_linear2_bias_to_fp16, dilations = input_1001_dilations_0, groups = input_1001_groups_0, pad = input_1001_pad_0, pad_type = input_1001_pad_type_0, strides = input_1001_strides_0, weight = net_xvector_block3_tdnnd10_cam_layer_linear2_weight_to_fp16, x = input_999_cast_fp16)[name = tensor<string, []>("input_1001_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_91_cast_fp16 = sigmoid(x = input_1001_cast_fp16)[name = tensor<string, []>("m_91_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3484_cast_fp16 = mul(x = y_91_cast_fp16, y = m_91_cast_fp16)[name = tensor<string, []>("op_3484_cast_fp16")];
            tensor<bool, []> input_1003_interleave_0 = const()[name = tensor<string, []>("input_1003_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 832, ?]> input_1003_cast_fp16 = concat(axis = var_11, interleave = input_1003_interleave_0, values = (input_983_cast_fp16, var_3484_cast_fp16))[name = tensor<string, []>("input_1003_cast_fp16")];
            tensor<fp16, [832]> net_xvector_block3_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [832]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10680704)))];
            tensor<fp16, [832]> net_xvector_block3_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [832]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10682432)))];
            tensor<fp16, [832]> net_xvector_block3_tdnnd11_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd11_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [832]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10684160)))];
            tensor<fp16, [832]> net_xvector_block3_tdnnd11_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd11_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [832]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10685888)))];
            tensor<fp16, [1, 832, ?]> input_1005_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd11_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd11_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16, x = input_1003_cast_fp16)[name = tensor<string, []>("input_1005_cast_fp16")];
            tensor<fp16, [1, 832, ?]> input_1007_cast_fp16 = relu(x = input_1005_cast_fp16)[name = tensor<string, []>("input_1007_cast_fp16")];
            tensor<string, []> input_1009_pad_type_0 = const()[name = tensor<string, []>("input_1009_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1009_strides_0 = const()[name = tensor<string, []>("input_1009_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1009_pad_0 = const()[name = tensor<string, []>("input_1009_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1009_dilations_0 = const()[name = tensor<string, []>("input_1009_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1009_groups_0 = const()[name = tensor<string, []>("input_1009_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 832, 1]> const_118_to_fp16 = const()[name = tensor<string, []>("const_118_to_fp16"), val = tensor<fp16, [128, 832, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10687616)))];
            tensor<fp16, [128]> const_119_to_fp16 = const()[name = tensor<string, []>("const_119_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10900672)))];
            tensor<fp16, [1, 128, ?]> input_1011_cast_fp16 = conv(bias = const_119_to_fp16, dilations = input_1009_dilations_0, groups = input_1009_groups_0, pad = input_1009_pad_0, pad_type = input_1009_pad_type_0, strides = input_1009_strides_0, weight = const_118_to_fp16, x = input_1007_cast_fp16)[name = tensor<string, []>("input_1011_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1013_cast_fp16 = relu(x = input_1011_cast_fp16)[name = tensor<string, []>("input_1013_cast_fp16")];
            tensor<string, []> y_93_pad_type_0 = const()[name = tensor<string, []>("y_93_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_93_pad_0 = const()[name = tensor<string, []>("y_93_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_93_dilations_0 = const()[name = tensor<string, []>("y_93_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_93_strides_0 = const()[name = tensor<string, []>("y_93_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_93_groups_0 = const()[name = tensor<string, []>("y_93_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd11_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd11_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10900992)))];
            tensor<fp16, [1, 32, ?]> y_93_cast_fp16 = conv(dilations = y_93_dilations_0, groups = y_93_groups_0, pad = y_93_pad_0, pad_type = y_93_pad_type_0, strides = y_93_strides_0, weight = net_xvector_block3_tdnnd11_cam_layer_linear_local_weight_to_fp16, x = input_1013_cast_fp16)[name = tensor<string, []>("y_93_cast_fp16")];
            tensor<int32, [1]> var_3521_axes_0 = const()[name = tensor<string, []>("op_3521_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3521_keep_dims_0 = const()[name = tensor<string, []>("op_3521_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3521_cast_fp16 = reduce_mean(axes = var_3521_axes_0, keep_dims = var_3521_keep_dims_0, x = input_1013_cast_fp16)[name = tensor<string, []>("op_3521_cast_fp16")];
            tensor<int32, [1]> var_3522 = const()[name = tensor<string, []>("op_3522"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3523 = const()[name = tensor<string, []>("op_3523"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_185_pad_type_0 = const()[name = tensor<string, []>("seg_185_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_185_pad_0 = const()[name = tensor<string, []>("seg_185_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_185_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_185_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_185_ceil_mode_0 = const()[name = tensor<string, []>("seg_185_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_185_cast_fp16 = avg_pool(ceil_mode = seg_185_ceil_mode_0, exclude_padding_from_average = seg_185_exclude_padding_from_average_0, kernel_sizes = var_3522, pad = seg_185_pad_0, pad_type = seg_185_pad_type_0, strides = var_3523, x = input_1013_cast_fp16)[name = tensor<string, []>("seg_185_cast_fp16")];
            tensor<int32, [3]> var_3526_shape_cast_fp16 = shape(x = seg_185_cast_fp16)[name = tensor<string, []>("op_3526_shape_cast_fp16")];
            tensor<int32, []> gather_188 = const()[name = tensor<string, []>("gather_188"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_189 = const()[name = tensor<string, []>("gather_189"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_190_axis_0 = const()[name = tensor<string, []>("gather_190_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_190_batch_dims_0 = const()[name = tensor<string, []>("gather_190_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_190_validate_indices_0 = const()[name = tensor<string, []>("gather_190_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3526_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3526_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_190_to_uint16 = const()[name = tensor<string, []>("select_190_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3526_shape_cast_fp16_to_uint16 = cast(dtype = var_3526_shape_cast_fp16_to_uint16_dtype_0, x = var_3526_shape_cast_fp16)[name = tensor<string, []>("cast_131")];
            tensor<uint16, []> gather_190_cast_uint16 = gather(axis = gather_190_axis_0, batch_dims = gather_190_batch_dims_0, indices = select_190_to_uint16, validate_indices = gather_190_validate_indices_0, x = var_3526_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_190_cast_uint16")];
            tensor<string, []> gather_190_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_190_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3529_axes_0 = const()[name = tensor<string, []>("op_3529_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3529_cast_fp16 = expand_dims(axes = var_3529_axes_0, x = seg_185_cast_fp16)[name = tensor<string, []>("op_3529_cast_fp16")];
            tensor<int32, []> concat_93_axis_0 = const()[name = tensor<string, []>("concat_93_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_93_interleave_0 = const()[name = tensor<string, []>("concat_93_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_190_cast_uint16_to_int32 = cast(dtype = gather_190_cast_uint16_to_int32_dtype_0, x = gather_190_cast_uint16)[name = tensor<string, []>("cast_130")];
            tensor<int32, [4]> concat_93 = concat(axis = concat_93_axis_0, interleave = concat_93_interleave_0, values = (gather_188, gather_189, gather_190_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_93")];
            tensor<int32, [4]> shape_237_cast_fp16 = shape(x = var_3529_cast_fp16)[name = tensor<string, []>("shape_237_cast_fp16")];
            tensor<int32, [4]> real_div_46 = real_div(x = concat_93, y = shape_237_cast_fp16)[name = tensor<string, []>("real_div_46")];
            tensor<fp16, [?, ?, ?, ?]> var_3531_cast_fp16 = tile(reps = real_div_46, x = var_3529_cast_fp16)[name = tensor<string, []>("op_3531_cast_fp16")];
            tensor<int32, [3]> var_3532 = const()[name = tensor<string, []>("op_3532"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_187_cast_fp16 = reshape(shape = var_3532, x = var_3531_cast_fp16)[name = tensor<string, []>("seg_187_cast_fp16")];
            tensor<int32, [3]> var_3534_shape_cast_fp16 = shape(x = input_1013_cast_fp16)[name = tensor<string, []>("op_3534_shape_cast_fp16")];
            tensor<int32, []> gather_191_axis_0 = const()[name = tensor<string, []>("gather_191_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_191_batch_dims_0 = const()[name = tensor<string, []>("gather_191_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_191_validate_indices_0 = const()[name = tensor<string, []>("gather_191_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3534_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3534_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_191_to_uint16 = const()[name = tensor<string, []>("select_191_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3534_shape_cast_fp16_to_uint16 = cast(dtype = var_3534_shape_cast_fp16_to_uint16_dtype_0, x = var_3534_shape_cast_fp16)[name = tensor<string, []>("cast_129")];
            tensor<uint16, []> gather_191_cast_uint16 = gather(axis = gather_191_axis_0, batch_dims = gather_191_batch_dims_0, indices = select_191_to_uint16, validate_indices = gather_191_validate_indices_0, x = var_3534_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_191_cast_uint16")];
            tensor<string, []> gather_191_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_191_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_94_values0_0 = const()[name = tensor<string, []>("concat_94_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_94_values1_0 = const()[name = tensor<string, []>("concat_94_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_94_axis_0 = const()[name = tensor<string, []>("concat_94_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_94_interleave_0 = const()[name = tensor<string, []>("concat_94_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_191_cast_uint16_to_int32 = cast(dtype = gather_191_cast_uint16_to_int32_dtype_0, x = gather_191_cast_uint16)[name = tensor<string, []>("cast_128")];
            tensor<int32, [3]> concat_94 = concat(axis = concat_94_axis_0, interleave = concat_94_interleave_0, values = (concat_94_values0_0, concat_94_values1_0, gather_191_cast_uint16_to_int32))[name = tensor<string, []>("concat_94")];
            tensor<int32, [3]> var_3535_begin_0 = const()[name = tensor<string, []>("op_3535_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3535_end_mask_0 = const()[name = tensor<string, []>("op_3535_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3535_cast_fp16 = slice_by_index(begin = var_3535_begin_0, end = concat_94, end_mask = var_3535_end_mask_0, x = seg_187_cast_fp16)[name = tensor<string, []>("op_3535_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1015_cast_fp16 = add(x = var_3521_cast_fp16, y = var_3535_cast_fp16)[name = tensor<string, []>("input_1015_cast_fp16")];
            tensor<string, []> input_1017_pad_type_0 = const()[name = tensor<string, []>("input_1017_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1017_strides_0 = const()[name = tensor<string, []>("input_1017_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1017_pad_0 = const()[name = tensor<string, []>("input_1017_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1017_dilations_0 = const()[name = tensor<string, []>("input_1017_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1017_groups_0 = const()[name = tensor<string, []>("input_1017_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd11_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd11_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10925632)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd11_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd11_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10942080)))];
            tensor<fp16, [1, 64, ?]> input_1017_cast_fp16 = conv(bias = net_xvector_block3_tdnnd11_cam_layer_linear1_bias_to_fp16, dilations = input_1017_dilations_0, groups = input_1017_groups_0, pad = input_1017_pad_0, pad_type = input_1017_pad_type_0, strides = input_1017_strides_0, weight = net_xvector_block3_tdnnd11_cam_layer_linear1_weight_to_fp16, x = input_1015_cast_fp16)[name = tensor<string, []>("input_1017_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_1019_cast_fp16 = relu(x = input_1017_cast_fp16)[name = tensor<string, []>("input_1019_cast_fp16")];
            tensor<string, []> input_1021_pad_type_0 = const()[name = tensor<string, []>("input_1021_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1021_strides_0 = const()[name = tensor<string, []>("input_1021_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1021_pad_0 = const()[name = tensor<string, []>("input_1021_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1021_dilations_0 = const()[name = tensor<string, []>("input_1021_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1021_groups_0 = const()[name = tensor<string, []>("input_1021_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd11_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd11_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10942272)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd11_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd11_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10946432)))];
            tensor<fp16, [1, 32, ?]> input_1021_cast_fp16 = conv(bias = net_xvector_block3_tdnnd11_cam_layer_linear2_bias_to_fp16, dilations = input_1021_dilations_0, groups = input_1021_groups_0, pad = input_1021_pad_0, pad_type = input_1021_pad_type_0, strides = input_1021_strides_0, weight = net_xvector_block3_tdnnd11_cam_layer_linear2_weight_to_fp16, x = input_1019_cast_fp16)[name = tensor<string, []>("input_1021_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_93_cast_fp16 = sigmoid(x = input_1021_cast_fp16)[name = tensor<string, []>("m_93_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3553_cast_fp16 = mul(x = y_93_cast_fp16, y = m_93_cast_fp16)[name = tensor<string, []>("op_3553_cast_fp16")];
            tensor<bool, []> input_1023_interleave_0 = const()[name = tensor<string, []>("input_1023_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 864, ?]> input_1023_cast_fp16 = concat(axis = var_11, interleave = input_1023_interleave_0, values = (input_1003_cast_fp16, var_3553_cast_fp16))[name = tensor<string, []>("input_1023_cast_fp16")];
            tensor<fp16, [864]> net_xvector_block3_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [864]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10946560)))];
            tensor<fp16, [864]> net_xvector_block3_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [864]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10948352)))];
            tensor<fp16, [864]> net_xvector_block3_tdnnd12_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd12_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [864]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10950144)))];
            tensor<fp16, [864]> net_xvector_block3_tdnnd12_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd12_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [864]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10951936)))];
            tensor<fp16, [1, 864, ?]> input_1025_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd12_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd12_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16, x = input_1023_cast_fp16)[name = tensor<string, []>("input_1025_cast_fp16")];
            tensor<fp16, [1, 864, ?]> input_1027_cast_fp16 = relu(x = input_1025_cast_fp16)[name = tensor<string, []>("input_1027_cast_fp16")];
            tensor<string, []> input_1029_pad_type_0 = const()[name = tensor<string, []>("input_1029_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1029_strides_0 = const()[name = tensor<string, []>("input_1029_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1029_pad_0 = const()[name = tensor<string, []>("input_1029_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1029_dilations_0 = const()[name = tensor<string, []>("input_1029_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1029_groups_0 = const()[name = tensor<string, []>("input_1029_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 864, 1]> const_120_to_fp16 = const()[name = tensor<string, []>("const_120_to_fp16"), val = tensor<fp16, [128, 864, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10953728)))];
            tensor<fp16, [128]> const_121_to_fp16 = const()[name = tensor<string, []>("const_121_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11174976)))];
            tensor<fp16, [1, 128, ?]> input_1031_cast_fp16 = conv(bias = const_121_to_fp16, dilations = input_1029_dilations_0, groups = input_1029_groups_0, pad = input_1029_pad_0, pad_type = input_1029_pad_type_0, strides = input_1029_strides_0, weight = const_120_to_fp16, x = input_1027_cast_fp16)[name = tensor<string, []>("input_1031_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1033_cast_fp16 = relu(x = input_1031_cast_fp16)[name = tensor<string, []>("input_1033_cast_fp16")];
            tensor<string, []> y_95_pad_type_0 = const()[name = tensor<string, []>("y_95_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_95_pad_0 = const()[name = tensor<string, []>("y_95_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_95_dilations_0 = const()[name = tensor<string, []>("y_95_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_95_strides_0 = const()[name = tensor<string, []>("y_95_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_95_groups_0 = const()[name = tensor<string, []>("y_95_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd12_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd12_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11175296)))];
            tensor<fp16, [1, 32, ?]> y_95_cast_fp16 = conv(dilations = y_95_dilations_0, groups = y_95_groups_0, pad = y_95_pad_0, pad_type = y_95_pad_type_0, strides = y_95_strides_0, weight = net_xvector_block3_tdnnd12_cam_layer_linear_local_weight_to_fp16, x = input_1033_cast_fp16)[name = tensor<string, []>("y_95_cast_fp16")];
            tensor<int32, [1]> var_3590_axes_0 = const()[name = tensor<string, []>("op_3590_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3590_keep_dims_0 = const()[name = tensor<string, []>("op_3590_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3590_cast_fp16 = reduce_mean(axes = var_3590_axes_0, keep_dims = var_3590_keep_dims_0, x = input_1033_cast_fp16)[name = tensor<string, []>("op_3590_cast_fp16")];
            tensor<int32, [1]> var_3591 = const()[name = tensor<string, []>("op_3591"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3592 = const()[name = tensor<string, []>("op_3592"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_189_pad_type_0 = const()[name = tensor<string, []>("seg_189_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_189_pad_0 = const()[name = tensor<string, []>("seg_189_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_189_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_189_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_189_ceil_mode_0 = const()[name = tensor<string, []>("seg_189_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_189_cast_fp16 = avg_pool(ceil_mode = seg_189_ceil_mode_0, exclude_padding_from_average = seg_189_exclude_padding_from_average_0, kernel_sizes = var_3591, pad = seg_189_pad_0, pad_type = seg_189_pad_type_0, strides = var_3592, x = input_1033_cast_fp16)[name = tensor<string, []>("seg_189_cast_fp16")];
            tensor<int32, [3]> var_3595_shape_cast_fp16 = shape(x = seg_189_cast_fp16)[name = tensor<string, []>("op_3595_shape_cast_fp16")];
            tensor<int32, []> gather_192 = const()[name = tensor<string, []>("gather_192"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_193 = const()[name = tensor<string, []>("gather_193"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_194_axis_0 = const()[name = tensor<string, []>("gather_194_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_194_batch_dims_0 = const()[name = tensor<string, []>("gather_194_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_194_validate_indices_0 = const()[name = tensor<string, []>("gather_194_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3595_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3595_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_194_to_uint16 = const()[name = tensor<string, []>("select_194_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3595_shape_cast_fp16_to_uint16 = cast(dtype = var_3595_shape_cast_fp16_to_uint16_dtype_0, x = var_3595_shape_cast_fp16)[name = tensor<string, []>("cast_127")];
            tensor<uint16, []> gather_194_cast_uint16 = gather(axis = gather_194_axis_0, batch_dims = gather_194_batch_dims_0, indices = select_194_to_uint16, validate_indices = gather_194_validate_indices_0, x = var_3595_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_194_cast_uint16")];
            tensor<string, []> gather_194_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_194_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3598_axes_0 = const()[name = tensor<string, []>("op_3598_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3598_cast_fp16 = expand_dims(axes = var_3598_axes_0, x = seg_189_cast_fp16)[name = tensor<string, []>("op_3598_cast_fp16")];
            tensor<int32, []> concat_95_axis_0 = const()[name = tensor<string, []>("concat_95_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_95_interleave_0 = const()[name = tensor<string, []>("concat_95_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_194_cast_uint16_to_int32 = cast(dtype = gather_194_cast_uint16_to_int32_dtype_0, x = gather_194_cast_uint16)[name = tensor<string, []>("cast_126")];
            tensor<int32, [4]> concat_95 = concat(axis = concat_95_axis_0, interleave = concat_95_interleave_0, values = (gather_192, gather_193, gather_194_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_95")];
            tensor<int32, [4]> shape_242_cast_fp16 = shape(x = var_3598_cast_fp16)[name = tensor<string, []>("shape_242_cast_fp16")];
            tensor<int32, [4]> real_div_47 = real_div(x = concat_95, y = shape_242_cast_fp16)[name = tensor<string, []>("real_div_47")];
            tensor<fp16, [?, ?, ?, ?]> var_3600_cast_fp16 = tile(reps = real_div_47, x = var_3598_cast_fp16)[name = tensor<string, []>("op_3600_cast_fp16")];
            tensor<int32, [3]> var_3601 = const()[name = tensor<string, []>("op_3601"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_191_cast_fp16 = reshape(shape = var_3601, x = var_3600_cast_fp16)[name = tensor<string, []>("seg_191_cast_fp16")];
            tensor<int32, [3]> var_3603_shape_cast_fp16 = shape(x = input_1033_cast_fp16)[name = tensor<string, []>("op_3603_shape_cast_fp16")];
            tensor<int32, []> gather_195_axis_0 = const()[name = tensor<string, []>("gather_195_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_195_batch_dims_0 = const()[name = tensor<string, []>("gather_195_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_195_validate_indices_0 = const()[name = tensor<string, []>("gather_195_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3603_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3603_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_195_to_uint16 = const()[name = tensor<string, []>("select_195_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3603_shape_cast_fp16_to_uint16 = cast(dtype = var_3603_shape_cast_fp16_to_uint16_dtype_0, x = var_3603_shape_cast_fp16)[name = tensor<string, []>("cast_125")];
            tensor<uint16, []> gather_195_cast_uint16 = gather(axis = gather_195_axis_0, batch_dims = gather_195_batch_dims_0, indices = select_195_to_uint16, validate_indices = gather_195_validate_indices_0, x = var_3603_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_195_cast_uint16")];
            tensor<string, []> gather_195_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_195_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_96_values0_0 = const()[name = tensor<string, []>("concat_96_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_96_values1_0 = const()[name = tensor<string, []>("concat_96_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_96_axis_0 = const()[name = tensor<string, []>("concat_96_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_96_interleave_0 = const()[name = tensor<string, []>("concat_96_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_195_cast_uint16_to_int32 = cast(dtype = gather_195_cast_uint16_to_int32_dtype_0, x = gather_195_cast_uint16)[name = tensor<string, []>("cast_124")];
            tensor<int32, [3]> concat_96 = concat(axis = concat_96_axis_0, interleave = concat_96_interleave_0, values = (concat_96_values0_0, concat_96_values1_0, gather_195_cast_uint16_to_int32))[name = tensor<string, []>("concat_96")];
            tensor<int32, [3]> var_3604_begin_0 = const()[name = tensor<string, []>("op_3604_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3604_end_mask_0 = const()[name = tensor<string, []>("op_3604_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3604_cast_fp16 = slice_by_index(begin = var_3604_begin_0, end = concat_96, end_mask = var_3604_end_mask_0, x = seg_191_cast_fp16)[name = tensor<string, []>("op_3604_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1035_cast_fp16 = add(x = var_3590_cast_fp16, y = var_3604_cast_fp16)[name = tensor<string, []>("input_1035_cast_fp16")];
            tensor<string, []> input_1037_pad_type_0 = const()[name = tensor<string, []>("input_1037_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1037_strides_0 = const()[name = tensor<string, []>("input_1037_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1037_pad_0 = const()[name = tensor<string, []>("input_1037_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1037_dilations_0 = const()[name = tensor<string, []>("input_1037_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1037_groups_0 = const()[name = tensor<string, []>("input_1037_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd12_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd12_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11199936)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd12_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd12_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11216384)))];
            tensor<fp16, [1, 64, ?]> input_1037_cast_fp16 = conv(bias = net_xvector_block3_tdnnd12_cam_layer_linear1_bias_to_fp16, dilations = input_1037_dilations_0, groups = input_1037_groups_0, pad = input_1037_pad_0, pad_type = input_1037_pad_type_0, strides = input_1037_strides_0, weight = net_xvector_block3_tdnnd12_cam_layer_linear1_weight_to_fp16, x = input_1035_cast_fp16)[name = tensor<string, []>("input_1037_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_1039_cast_fp16 = relu(x = input_1037_cast_fp16)[name = tensor<string, []>("input_1039_cast_fp16")];
            tensor<string, []> input_1041_pad_type_0 = const()[name = tensor<string, []>("input_1041_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1041_strides_0 = const()[name = tensor<string, []>("input_1041_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1041_pad_0 = const()[name = tensor<string, []>("input_1041_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1041_dilations_0 = const()[name = tensor<string, []>("input_1041_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1041_groups_0 = const()[name = tensor<string, []>("input_1041_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd12_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd12_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11216576)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd12_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd12_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11220736)))];
            tensor<fp16, [1, 32, ?]> input_1041_cast_fp16 = conv(bias = net_xvector_block3_tdnnd12_cam_layer_linear2_bias_to_fp16, dilations = input_1041_dilations_0, groups = input_1041_groups_0, pad = input_1041_pad_0, pad_type = input_1041_pad_type_0, strides = input_1041_strides_0, weight = net_xvector_block3_tdnnd12_cam_layer_linear2_weight_to_fp16, x = input_1039_cast_fp16)[name = tensor<string, []>("input_1041_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_95_cast_fp16 = sigmoid(x = input_1041_cast_fp16)[name = tensor<string, []>("m_95_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3622_cast_fp16 = mul(x = y_95_cast_fp16, y = m_95_cast_fp16)[name = tensor<string, []>("op_3622_cast_fp16")];
            tensor<bool, []> input_1043_interleave_0 = const()[name = tensor<string, []>("input_1043_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 896, ?]> input_1043_cast_fp16 = concat(axis = var_11, interleave = input_1043_interleave_0, values = (input_1023_cast_fp16, var_3622_cast_fp16))[name = tensor<string, []>("input_1043_cast_fp16")];
            tensor<fp16, [896]> net_xvector_block3_tdnnd13_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd13_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11220864)))];
            tensor<fp16, [896]> net_xvector_block3_tdnnd13_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd13_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11222720)))];
            tensor<fp16, [896]> net_xvector_block3_tdnnd13_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd13_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11224576)))];
            tensor<fp16, [896]> net_xvector_block3_tdnnd13_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd13_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [896]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11226432)))];
            tensor<fp16, [1, 896, ?]> input_1045_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd13_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd13_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd13_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd13_nonlinear1_batchnorm_running_var_to_fp16, x = input_1043_cast_fp16)[name = tensor<string, []>("input_1045_cast_fp16")];
            tensor<fp16, [1, 896, ?]> input_1047_cast_fp16 = relu(x = input_1045_cast_fp16)[name = tensor<string, []>("input_1047_cast_fp16")];
            tensor<string, []> input_1049_pad_type_0 = const()[name = tensor<string, []>("input_1049_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1049_strides_0 = const()[name = tensor<string, []>("input_1049_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1049_pad_0 = const()[name = tensor<string, []>("input_1049_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1049_dilations_0 = const()[name = tensor<string, []>("input_1049_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1049_groups_0 = const()[name = tensor<string, []>("input_1049_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 896, 1]> const_122_to_fp16 = const()[name = tensor<string, []>("const_122_to_fp16"), val = tensor<fp16, [128, 896, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11228288)))];
            tensor<fp16, [128]> const_123_to_fp16 = const()[name = tensor<string, []>("const_123_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11457728)))];
            tensor<fp16, [1, 128, ?]> input_1051_cast_fp16 = conv(bias = const_123_to_fp16, dilations = input_1049_dilations_0, groups = input_1049_groups_0, pad = input_1049_pad_0, pad_type = input_1049_pad_type_0, strides = input_1049_strides_0, weight = const_122_to_fp16, x = input_1047_cast_fp16)[name = tensor<string, []>("input_1051_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1053_cast_fp16 = relu(x = input_1051_cast_fp16)[name = tensor<string, []>("input_1053_cast_fp16")];
            tensor<string, []> y_97_pad_type_0 = const()[name = tensor<string, []>("y_97_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_97_pad_0 = const()[name = tensor<string, []>("y_97_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_97_dilations_0 = const()[name = tensor<string, []>("y_97_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_97_strides_0 = const()[name = tensor<string, []>("y_97_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_97_groups_0 = const()[name = tensor<string, []>("y_97_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd13_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd13_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11458048)))];
            tensor<fp16, [1, 32, ?]> y_97_cast_fp16 = conv(dilations = y_97_dilations_0, groups = y_97_groups_0, pad = y_97_pad_0, pad_type = y_97_pad_type_0, strides = y_97_strides_0, weight = net_xvector_block3_tdnnd13_cam_layer_linear_local_weight_to_fp16, x = input_1053_cast_fp16)[name = tensor<string, []>("y_97_cast_fp16")];
            tensor<int32, [1]> var_3659_axes_0 = const()[name = tensor<string, []>("op_3659_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3659_keep_dims_0 = const()[name = tensor<string, []>("op_3659_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3659_cast_fp16 = reduce_mean(axes = var_3659_axes_0, keep_dims = var_3659_keep_dims_0, x = input_1053_cast_fp16)[name = tensor<string, []>("op_3659_cast_fp16")];
            tensor<int32, [1]> var_3660 = const()[name = tensor<string, []>("op_3660"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3661 = const()[name = tensor<string, []>("op_3661"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_193_pad_type_0 = const()[name = tensor<string, []>("seg_193_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_193_pad_0 = const()[name = tensor<string, []>("seg_193_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_193_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_193_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_193_ceil_mode_0 = const()[name = tensor<string, []>("seg_193_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_193_cast_fp16 = avg_pool(ceil_mode = seg_193_ceil_mode_0, exclude_padding_from_average = seg_193_exclude_padding_from_average_0, kernel_sizes = var_3660, pad = seg_193_pad_0, pad_type = seg_193_pad_type_0, strides = var_3661, x = input_1053_cast_fp16)[name = tensor<string, []>("seg_193_cast_fp16")];
            tensor<int32, [3]> var_3664_shape_cast_fp16 = shape(x = seg_193_cast_fp16)[name = tensor<string, []>("op_3664_shape_cast_fp16")];
            tensor<int32, []> gather_196 = const()[name = tensor<string, []>("gather_196"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_197 = const()[name = tensor<string, []>("gather_197"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_198_axis_0 = const()[name = tensor<string, []>("gather_198_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_198_batch_dims_0 = const()[name = tensor<string, []>("gather_198_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_198_validate_indices_0 = const()[name = tensor<string, []>("gather_198_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3664_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3664_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_198_to_uint16 = const()[name = tensor<string, []>("select_198_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3664_shape_cast_fp16_to_uint16 = cast(dtype = var_3664_shape_cast_fp16_to_uint16_dtype_0, x = var_3664_shape_cast_fp16)[name = tensor<string, []>("cast_123")];
            tensor<uint16, []> gather_198_cast_uint16 = gather(axis = gather_198_axis_0, batch_dims = gather_198_batch_dims_0, indices = select_198_to_uint16, validate_indices = gather_198_validate_indices_0, x = var_3664_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_198_cast_uint16")];
            tensor<string, []> gather_198_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_198_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3667_axes_0 = const()[name = tensor<string, []>("op_3667_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3667_cast_fp16 = expand_dims(axes = var_3667_axes_0, x = seg_193_cast_fp16)[name = tensor<string, []>("op_3667_cast_fp16")];
            tensor<int32, []> concat_97_axis_0 = const()[name = tensor<string, []>("concat_97_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_97_interleave_0 = const()[name = tensor<string, []>("concat_97_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_198_cast_uint16_to_int32 = cast(dtype = gather_198_cast_uint16_to_int32_dtype_0, x = gather_198_cast_uint16)[name = tensor<string, []>("cast_122")];
            tensor<int32, [4]> concat_97 = concat(axis = concat_97_axis_0, interleave = concat_97_interleave_0, values = (gather_196, gather_197, gather_198_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_97")];
            tensor<int32, [4]> shape_247_cast_fp16 = shape(x = var_3667_cast_fp16)[name = tensor<string, []>("shape_247_cast_fp16")];
            tensor<int32, [4]> real_div_48 = real_div(x = concat_97, y = shape_247_cast_fp16)[name = tensor<string, []>("real_div_48")];
            tensor<fp16, [?, ?, ?, ?]> var_3669_cast_fp16 = tile(reps = real_div_48, x = var_3667_cast_fp16)[name = tensor<string, []>("op_3669_cast_fp16")];
            tensor<int32, [3]> var_3670 = const()[name = tensor<string, []>("op_3670"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_195_cast_fp16 = reshape(shape = var_3670, x = var_3669_cast_fp16)[name = tensor<string, []>("seg_195_cast_fp16")];
            tensor<int32, [3]> var_3672_shape_cast_fp16 = shape(x = input_1053_cast_fp16)[name = tensor<string, []>("op_3672_shape_cast_fp16")];
            tensor<int32, []> gather_199_axis_0 = const()[name = tensor<string, []>("gather_199_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_199_batch_dims_0 = const()[name = tensor<string, []>("gather_199_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_199_validate_indices_0 = const()[name = tensor<string, []>("gather_199_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3672_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3672_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_199_to_uint16 = const()[name = tensor<string, []>("select_199_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3672_shape_cast_fp16_to_uint16 = cast(dtype = var_3672_shape_cast_fp16_to_uint16_dtype_0, x = var_3672_shape_cast_fp16)[name = tensor<string, []>("cast_121")];
            tensor<uint16, []> gather_199_cast_uint16 = gather(axis = gather_199_axis_0, batch_dims = gather_199_batch_dims_0, indices = select_199_to_uint16, validate_indices = gather_199_validate_indices_0, x = var_3672_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_199_cast_uint16")];
            tensor<string, []> gather_199_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_199_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_98_values0_0 = const()[name = tensor<string, []>("concat_98_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_98_values1_0 = const()[name = tensor<string, []>("concat_98_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_98_axis_0 = const()[name = tensor<string, []>("concat_98_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_98_interleave_0 = const()[name = tensor<string, []>("concat_98_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_199_cast_uint16_to_int32 = cast(dtype = gather_199_cast_uint16_to_int32_dtype_0, x = gather_199_cast_uint16)[name = tensor<string, []>("cast_120")];
            tensor<int32, [3]> concat_98 = concat(axis = concat_98_axis_0, interleave = concat_98_interleave_0, values = (concat_98_values0_0, concat_98_values1_0, gather_199_cast_uint16_to_int32))[name = tensor<string, []>("concat_98")];
            tensor<int32, [3]> var_3673_begin_0 = const()[name = tensor<string, []>("op_3673_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3673_end_mask_0 = const()[name = tensor<string, []>("op_3673_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3673_cast_fp16 = slice_by_index(begin = var_3673_begin_0, end = concat_98, end_mask = var_3673_end_mask_0, x = seg_195_cast_fp16)[name = tensor<string, []>("op_3673_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1055_cast_fp16 = add(x = var_3659_cast_fp16, y = var_3673_cast_fp16)[name = tensor<string, []>("input_1055_cast_fp16")];
            tensor<string, []> input_1057_pad_type_0 = const()[name = tensor<string, []>("input_1057_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1057_strides_0 = const()[name = tensor<string, []>("input_1057_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1057_pad_0 = const()[name = tensor<string, []>("input_1057_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1057_dilations_0 = const()[name = tensor<string, []>("input_1057_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1057_groups_0 = const()[name = tensor<string, []>("input_1057_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd13_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd13_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11482688)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd13_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd13_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11499136)))];
            tensor<fp16, [1, 64, ?]> input_1057_cast_fp16 = conv(bias = net_xvector_block3_tdnnd13_cam_layer_linear1_bias_to_fp16, dilations = input_1057_dilations_0, groups = input_1057_groups_0, pad = input_1057_pad_0, pad_type = input_1057_pad_type_0, strides = input_1057_strides_0, weight = net_xvector_block3_tdnnd13_cam_layer_linear1_weight_to_fp16, x = input_1055_cast_fp16)[name = tensor<string, []>("input_1057_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_1059_cast_fp16 = relu(x = input_1057_cast_fp16)[name = tensor<string, []>("input_1059_cast_fp16")];
            tensor<string, []> input_1061_pad_type_0 = const()[name = tensor<string, []>("input_1061_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1061_strides_0 = const()[name = tensor<string, []>("input_1061_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1061_pad_0 = const()[name = tensor<string, []>("input_1061_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1061_dilations_0 = const()[name = tensor<string, []>("input_1061_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1061_groups_0 = const()[name = tensor<string, []>("input_1061_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd13_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd13_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11499328)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd13_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd13_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11503488)))];
            tensor<fp16, [1, 32, ?]> input_1061_cast_fp16 = conv(bias = net_xvector_block3_tdnnd13_cam_layer_linear2_bias_to_fp16, dilations = input_1061_dilations_0, groups = input_1061_groups_0, pad = input_1061_pad_0, pad_type = input_1061_pad_type_0, strides = input_1061_strides_0, weight = net_xvector_block3_tdnnd13_cam_layer_linear2_weight_to_fp16, x = input_1059_cast_fp16)[name = tensor<string, []>("input_1061_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_97_cast_fp16 = sigmoid(x = input_1061_cast_fp16)[name = tensor<string, []>("m_97_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3691_cast_fp16 = mul(x = y_97_cast_fp16, y = m_97_cast_fp16)[name = tensor<string, []>("op_3691_cast_fp16")];
            tensor<bool, []> input_1063_interleave_0 = const()[name = tensor<string, []>("input_1063_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 928, ?]> input_1063_cast_fp16 = concat(axis = var_11, interleave = input_1063_interleave_0, values = (input_1043_cast_fp16, var_3691_cast_fp16))[name = tensor<string, []>("input_1063_cast_fp16")];
            tensor<fp16, [928]> net_xvector_block3_tdnnd14_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd14_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [928]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11503616)))];
            tensor<fp16, [928]> net_xvector_block3_tdnnd14_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd14_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [928]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11505536)))];
            tensor<fp16, [928]> net_xvector_block3_tdnnd14_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd14_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [928]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11507456)))];
            tensor<fp16, [928]> net_xvector_block3_tdnnd14_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd14_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [928]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11509376)))];
            tensor<fp16, [1, 928, ?]> input_1065_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd14_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd14_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd14_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd14_nonlinear1_batchnorm_running_var_to_fp16, x = input_1063_cast_fp16)[name = tensor<string, []>("input_1065_cast_fp16")];
            tensor<fp16, [1, 928, ?]> input_1067_cast_fp16 = relu(x = input_1065_cast_fp16)[name = tensor<string, []>("input_1067_cast_fp16")];
            tensor<string, []> input_1069_pad_type_0 = const()[name = tensor<string, []>("input_1069_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1069_strides_0 = const()[name = tensor<string, []>("input_1069_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1069_pad_0 = const()[name = tensor<string, []>("input_1069_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1069_dilations_0 = const()[name = tensor<string, []>("input_1069_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1069_groups_0 = const()[name = tensor<string, []>("input_1069_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 928, 1]> const_124_to_fp16 = const()[name = tensor<string, []>("const_124_to_fp16"), val = tensor<fp16, [128, 928, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11511296)))];
            tensor<fp16, [128]> const_125_to_fp16 = const()[name = tensor<string, []>("const_125_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11748928)))];
            tensor<fp16, [1, 128, ?]> input_1071_cast_fp16 = conv(bias = const_125_to_fp16, dilations = input_1069_dilations_0, groups = input_1069_groups_0, pad = input_1069_pad_0, pad_type = input_1069_pad_type_0, strides = input_1069_strides_0, weight = const_124_to_fp16, x = input_1067_cast_fp16)[name = tensor<string, []>("input_1071_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1073_cast_fp16 = relu(x = input_1071_cast_fp16)[name = tensor<string, []>("input_1073_cast_fp16")];
            tensor<string, []> y_99_pad_type_0 = const()[name = tensor<string, []>("y_99_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_99_pad_0 = const()[name = tensor<string, []>("y_99_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_99_dilations_0 = const()[name = tensor<string, []>("y_99_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_99_strides_0 = const()[name = tensor<string, []>("y_99_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_99_groups_0 = const()[name = tensor<string, []>("y_99_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd14_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd14_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11749248)))];
            tensor<fp16, [1, 32, ?]> y_99_cast_fp16 = conv(dilations = y_99_dilations_0, groups = y_99_groups_0, pad = y_99_pad_0, pad_type = y_99_pad_type_0, strides = y_99_strides_0, weight = net_xvector_block3_tdnnd14_cam_layer_linear_local_weight_to_fp16, x = input_1073_cast_fp16)[name = tensor<string, []>("y_99_cast_fp16")];
            tensor<int32, [1]> var_3728_axes_0 = const()[name = tensor<string, []>("op_3728_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3728_keep_dims_0 = const()[name = tensor<string, []>("op_3728_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3728_cast_fp16 = reduce_mean(axes = var_3728_axes_0, keep_dims = var_3728_keep_dims_0, x = input_1073_cast_fp16)[name = tensor<string, []>("op_3728_cast_fp16")];
            tensor<int32, [1]> var_3729 = const()[name = tensor<string, []>("op_3729"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3730 = const()[name = tensor<string, []>("op_3730"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_197_pad_type_0 = const()[name = tensor<string, []>("seg_197_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_197_pad_0 = const()[name = tensor<string, []>("seg_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_197_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_197_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_197_ceil_mode_0 = const()[name = tensor<string, []>("seg_197_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_197_cast_fp16 = avg_pool(ceil_mode = seg_197_ceil_mode_0, exclude_padding_from_average = seg_197_exclude_padding_from_average_0, kernel_sizes = var_3729, pad = seg_197_pad_0, pad_type = seg_197_pad_type_0, strides = var_3730, x = input_1073_cast_fp16)[name = tensor<string, []>("seg_197_cast_fp16")];
            tensor<int32, [3]> var_3733_shape_cast_fp16 = shape(x = seg_197_cast_fp16)[name = tensor<string, []>("op_3733_shape_cast_fp16")];
            tensor<int32, []> gather_200 = const()[name = tensor<string, []>("gather_200"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_201 = const()[name = tensor<string, []>("gather_201"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_202_axis_0 = const()[name = tensor<string, []>("gather_202_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_202_batch_dims_0 = const()[name = tensor<string, []>("gather_202_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_202_validate_indices_0 = const()[name = tensor<string, []>("gather_202_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3733_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3733_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_202_to_uint16 = const()[name = tensor<string, []>("select_202_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3733_shape_cast_fp16_to_uint16 = cast(dtype = var_3733_shape_cast_fp16_to_uint16_dtype_0, x = var_3733_shape_cast_fp16)[name = tensor<string, []>("cast_119")];
            tensor<uint16, []> gather_202_cast_uint16 = gather(axis = gather_202_axis_0, batch_dims = gather_202_batch_dims_0, indices = select_202_to_uint16, validate_indices = gather_202_validate_indices_0, x = var_3733_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_202_cast_uint16")];
            tensor<string, []> gather_202_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_202_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3736_axes_0 = const()[name = tensor<string, []>("op_3736_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3736_cast_fp16 = expand_dims(axes = var_3736_axes_0, x = seg_197_cast_fp16)[name = tensor<string, []>("op_3736_cast_fp16")];
            tensor<int32, []> concat_99_axis_0 = const()[name = tensor<string, []>("concat_99_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_99_interleave_0 = const()[name = tensor<string, []>("concat_99_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_202_cast_uint16_to_int32 = cast(dtype = gather_202_cast_uint16_to_int32_dtype_0, x = gather_202_cast_uint16)[name = tensor<string, []>("cast_118")];
            tensor<int32, [4]> concat_99 = concat(axis = concat_99_axis_0, interleave = concat_99_interleave_0, values = (gather_200, gather_201, gather_202_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_99")];
            tensor<int32, [4]> shape_252_cast_fp16 = shape(x = var_3736_cast_fp16)[name = tensor<string, []>("shape_252_cast_fp16")];
            tensor<int32, [4]> real_div_49 = real_div(x = concat_99, y = shape_252_cast_fp16)[name = tensor<string, []>("real_div_49")];
            tensor<fp16, [?, ?, ?, ?]> var_3738_cast_fp16 = tile(reps = real_div_49, x = var_3736_cast_fp16)[name = tensor<string, []>("op_3738_cast_fp16")];
            tensor<int32, [3]> var_3739 = const()[name = tensor<string, []>("op_3739"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_199_cast_fp16 = reshape(shape = var_3739, x = var_3738_cast_fp16)[name = tensor<string, []>("seg_199_cast_fp16")];
            tensor<int32, [3]> var_3741_shape_cast_fp16 = shape(x = input_1073_cast_fp16)[name = tensor<string, []>("op_3741_shape_cast_fp16")];
            tensor<int32, []> gather_203_axis_0 = const()[name = tensor<string, []>("gather_203_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_203_batch_dims_0 = const()[name = tensor<string, []>("gather_203_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_203_validate_indices_0 = const()[name = tensor<string, []>("gather_203_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3741_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3741_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_203_to_uint16 = const()[name = tensor<string, []>("select_203_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3741_shape_cast_fp16_to_uint16 = cast(dtype = var_3741_shape_cast_fp16_to_uint16_dtype_0, x = var_3741_shape_cast_fp16)[name = tensor<string, []>("cast_117")];
            tensor<uint16, []> gather_203_cast_uint16 = gather(axis = gather_203_axis_0, batch_dims = gather_203_batch_dims_0, indices = select_203_to_uint16, validate_indices = gather_203_validate_indices_0, x = var_3741_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_203_cast_uint16")];
            tensor<string, []> gather_203_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_203_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_100_values0_0 = const()[name = tensor<string, []>("concat_100_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_100_values1_0 = const()[name = tensor<string, []>("concat_100_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_100_axis_0 = const()[name = tensor<string, []>("concat_100_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_100_interleave_0 = const()[name = tensor<string, []>("concat_100_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_203_cast_uint16_to_int32 = cast(dtype = gather_203_cast_uint16_to_int32_dtype_0, x = gather_203_cast_uint16)[name = tensor<string, []>("cast_116")];
            tensor<int32, [3]> concat_100 = concat(axis = concat_100_axis_0, interleave = concat_100_interleave_0, values = (concat_100_values0_0, concat_100_values1_0, gather_203_cast_uint16_to_int32))[name = tensor<string, []>("concat_100")];
            tensor<int32, [3]> var_3742_begin_0 = const()[name = tensor<string, []>("op_3742_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3742_end_mask_0 = const()[name = tensor<string, []>("op_3742_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3742_cast_fp16 = slice_by_index(begin = var_3742_begin_0, end = concat_100, end_mask = var_3742_end_mask_0, x = seg_199_cast_fp16)[name = tensor<string, []>("op_3742_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1075_cast_fp16 = add(x = var_3728_cast_fp16, y = var_3742_cast_fp16)[name = tensor<string, []>("input_1075_cast_fp16")];
            tensor<string, []> input_1077_pad_type_0 = const()[name = tensor<string, []>("input_1077_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1077_strides_0 = const()[name = tensor<string, []>("input_1077_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1077_pad_0 = const()[name = tensor<string, []>("input_1077_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1077_dilations_0 = const()[name = tensor<string, []>("input_1077_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1077_groups_0 = const()[name = tensor<string, []>("input_1077_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd14_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd14_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11773888)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd14_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd14_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11790336)))];
            tensor<fp16, [1, 64, ?]> input_1077_cast_fp16 = conv(bias = net_xvector_block3_tdnnd14_cam_layer_linear1_bias_to_fp16, dilations = input_1077_dilations_0, groups = input_1077_groups_0, pad = input_1077_pad_0, pad_type = input_1077_pad_type_0, strides = input_1077_strides_0, weight = net_xvector_block3_tdnnd14_cam_layer_linear1_weight_to_fp16, x = input_1075_cast_fp16)[name = tensor<string, []>("input_1077_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_1079_cast_fp16 = relu(x = input_1077_cast_fp16)[name = tensor<string, []>("input_1079_cast_fp16")];
            tensor<string, []> input_1081_pad_type_0 = const()[name = tensor<string, []>("input_1081_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1081_strides_0 = const()[name = tensor<string, []>("input_1081_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1081_pad_0 = const()[name = tensor<string, []>("input_1081_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1081_dilations_0 = const()[name = tensor<string, []>("input_1081_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1081_groups_0 = const()[name = tensor<string, []>("input_1081_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd14_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd14_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11790528)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd14_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd14_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11794688)))];
            tensor<fp16, [1, 32, ?]> input_1081_cast_fp16 = conv(bias = net_xvector_block3_tdnnd14_cam_layer_linear2_bias_to_fp16, dilations = input_1081_dilations_0, groups = input_1081_groups_0, pad = input_1081_pad_0, pad_type = input_1081_pad_type_0, strides = input_1081_strides_0, weight = net_xvector_block3_tdnnd14_cam_layer_linear2_weight_to_fp16, x = input_1079_cast_fp16)[name = tensor<string, []>("input_1081_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_99_cast_fp16 = sigmoid(x = input_1081_cast_fp16)[name = tensor<string, []>("m_99_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3760_cast_fp16 = mul(x = y_99_cast_fp16, y = m_99_cast_fp16)[name = tensor<string, []>("op_3760_cast_fp16")];
            tensor<bool, []> input_1083_interleave_0 = const()[name = tensor<string, []>("input_1083_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 960, ?]> input_1083_cast_fp16 = concat(axis = var_11, interleave = input_1083_interleave_0, values = (input_1063_cast_fp16, var_3760_cast_fp16))[name = tensor<string, []>("input_1083_cast_fp16")];
            tensor<fp16, [960]> net_xvector_block3_tdnnd15_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd15_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11794816)))];
            tensor<fp16, [960]> net_xvector_block3_tdnnd15_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd15_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11796800)))];
            tensor<fp16, [960]> net_xvector_block3_tdnnd15_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd15_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11798784)))];
            tensor<fp16, [960]> net_xvector_block3_tdnnd15_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd15_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [960]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11800768)))];
            tensor<fp16, [1, 960, ?]> input_1085_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd15_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd15_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd15_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd15_nonlinear1_batchnorm_running_var_to_fp16, x = input_1083_cast_fp16)[name = tensor<string, []>("input_1085_cast_fp16")];
            tensor<fp16, [1, 960, ?]> input_1087_cast_fp16 = relu(x = input_1085_cast_fp16)[name = tensor<string, []>("input_1087_cast_fp16")];
            tensor<string, []> input_1089_pad_type_0 = const()[name = tensor<string, []>("input_1089_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1089_strides_0 = const()[name = tensor<string, []>("input_1089_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1089_pad_0 = const()[name = tensor<string, []>("input_1089_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1089_dilations_0 = const()[name = tensor<string, []>("input_1089_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1089_groups_0 = const()[name = tensor<string, []>("input_1089_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 960, 1]> const_126_to_fp16 = const()[name = tensor<string, []>("const_126_to_fp16"), val = tensor<fp16, [128, 960, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11802752)))];
            tensor<fp16, [128]> const_127_to_fp16 = const()[name = tensor<string, []>("const_127_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12048576)))];
            tensor<fp16, [1, 128, ?]> input_1091_cast_fp16 = conv(bias = const_127_to_fp16, dilations = input_1089_dilations_0, groups = input_1089_groups_0, pad = input_1089_pad_0, pad_type = input_1089_pad_type_0, strides = input_1089_strides_0, weight = const_126_to_fp16, x = input_1087_cast_fp16)[name = tensor<string, []>("input_1091_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1093_cast_fp16 = relu(x = input_1091_cast_fp16)[name = tensor<string, []>("input_1093_cast_fp16")];
            tensor<string, []> y_101_pad_type_0 = const()[name = tensor<string, []>("y_101_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_101_pad_0 = const()[name = tensor<string, []>("y_101_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_101_dilations_0 = const()[name = tensor<string, []>("y_101_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_101_strides_0 = const()[name = tensor<string, []>("y_101_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_101_groups_0 = const()[name = tensor<string, []>("y_101_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd15_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd15_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12048896)))];
            tensor<fp16, [1, 32, ?]> y_101_cast_fp16 = conv(dilations = y_101_dilations_0, groups = y_101_groups_0, pad = y_101_pad_0, pad_type = y_101_pad_type_0, strides = y_101_strides_0, weight = net_xvector_block3_tdnnd15_cam_layer_linear_local_weight_to_fp16, x = input_1093_cast_fp16)[name = tensor<string, []>("y_101_cast_fp16")];
            tensor<int32, [1]> var_3797_axes_0 = const()[name = tensor<string, []>("op_3797_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3797_keep_dims_0 = const()[name = tensor<string, []>("op_3797_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3797_cast_fp16 = reduce_mean(axes = var_3797_axes_0, keep_dims = var_3797_keep_dims_0, x = input_1093_cast_fp16)[name = tensor<string, []>("op_3797_cast_fp16")];
            tensor<int32, [1]> var_3798 = const()[name = tensor<string, []>("op_3798"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3799 = const()[name = tensor<string, []>("op_3799"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_201_pad_type_0 = const()[name = tensor<string, []>("seg_201_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_201_pad_0 = const()[name = tensor<string, []>("seg_201_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_201_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_201_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_201_ceil_mode_0 = const()[name = tensor<string, []>("seg_201_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_201_cast_fp16 = avg_pool(ceil_mode = seg_201_ceil_mode_0, exclude_padding_from_average = seg_201_exclude_padding_from_average_0, kernel_sizes = var_3798, pad = seg_201_pad_0, pad_type = seg_201_pad_type_0, strides = var_3799, x = input_1093_cast_fp16)[name = tensor<string, []>("seg_201_cast_fp16")];
            tensor<int32, [3]> var_3802_shape_cast_fp16 = shape(x = seg_201_cast_fp16)[name = tensor<string, []>("op_3802_shape_cast_fp16")];
            tensor<int32, []> gather_204 = const()[name = tensor<string, []>("gather_204"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_205 = const()[name = tensor<string, []>("gather_205"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_206_axis_0 = const()[name = tensor<string, []>("gather_206_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_206_batch_dims_0 = const()[name = tensor<string, []>("gather_206_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_206_validate_indices_0 = const()[name = tensor<string, []>("gather_206_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3802_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3802_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_206_to_uint16 = const()[name = tensor<string, []>("select_206_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3802_shape_cast_fp16_to_uint16 = cast(dtype = var_3802_shape_cast_fp16_to_uint16_dtype_0, x = var_3802_shape_cast_fp16)[name = tensor<string, []>("cast_115")];
            tensor<uint16, []> gather_206_cast_uint16 = gather(axis = gather_206_axis_0, batch_dims = gather_206_batch_dims_0, indices = select_206_to_uint16, validate_indices = gather_206_validate_indices_0, x = var_3802_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_206_cast_uint16")];
            tensor<string, []> gather_206_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_206_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3805_axes_0 = const()[name = tensor<string, []>("op_3805_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3805_cast_fp16 = expand_dims(axes = var_3805_axes_0, x = seg_201_cast_fp16)[name = tensor<string, []>("op_3805_cast_fp16")];
            tensor<int32, []> concat_101_axis_0 = const()[name = tensor<string, []>("concat_101_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_101_interleave_0 = const()[name = tensor<string, []>("concat_101_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_206_cast_uint16_to_int32 = cast(dtype = gather_206_cast_uint16_to_int32_dtype_0, x = gather_206_cast_uint16)[name = tensor<string, []>("cast_114")];
            tensor<int32, [4]> concat_101 = concat(axis = concat_101_axis_0, interleave = concat_101_interleave_0, values = (gather_204, gather_205, gather_206_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_101")];
            tensor<int32, [4]> shape_257_cast_fp16 = shape(x = var_3805_cast_fp16)[name = tensor<string, []>("shape_257_cast_fp16")];
            tensor<int32, [4]> real_div_50 = real_div(x = concat_101, y = shape_257_cast_fp16)[name = tensor<string, []>("real_div_50")];
            tensor<fp16, [?, ?, ?, ?]> var_3807_cast_fp16 = tile(reps = real_div_50, x = var_3805_cast_fp16)[name = tensor<string, []>("op_3807_cast_fp16")];
            tensor<int32, [3]> var_3808 = const()[name = tensor<string, []>("op_3808"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_203_cast_fp16 = reshape(shape = var_3808, x = var_3807_cast_fp16)[name = tensor<string, []>("seg_203_cast_fp16")];
            tensor<int32, [3]> var_3810_shape_cast_fp16 = shape(x = input_1093_cast_fp16)[name = tensor<string, []>("op_3810_shape_cast_fp16")];
            tensor<int32, []> gather_207_axis_0 = const()[name = tensor<string, []>("gather_207_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_207_batch_dims_0 = const()[name = tensor<string, []>("gather_207_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_207_validate_indices_0 = const()[name = tensor<string, []>("gather_207_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3810_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3810_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_207_to_uint16 = const()[name = tensor<string, []>("select_207_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3810_shape_cast_fp16_to_uint16 = cast(dtype = var_3810_shape_cast_fp16_to_uint16_dtype_0, x = var_3810_shape_cast_fp16)[name = tensor<string, []>("cast_113")];
            tensor<uint16, []> gather_207_cast_uint16 = gather(axis = gather_207_axis_0, batch_dims = gather_207_batch_dims_0, indices = select_207_to_uint16, validate_indices = gather_207_validate_indices_0, x = var_3810_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_207_cast_uint16")];
            tensor<string, []> gather_207_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_207_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_102_values0_0 = const()[name = tensor<string, []>("concat_102_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_102_values1_0 = const()[name = tensor<string, []>("concat_102_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_102_axis_0 = const()[name = tensor<string, []>("concat_102_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_102_interleave_0 = const()[name = tensor<string, []>("concat_102_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_207_cast_uint16_to_int32 = cast(dtype = gather_207_cast_uint16_to_int32_dtype_0, x = gather_207_cast_uint16)[name = tensor<string, []>("cast_112")];
            tensor<int32, [3]> concat_102 = concat(axis = concat_102_axis_0, interleave = concat_102_interleave_0, values = (concat_102_values0_0, concat_102_values1_0, gather_207_cast_uint16_to_int32))[name = tensor<string, []>("concat_102")];
            tensor<int32, [3]> var_3811_begin_0 = const()[name = tensor<string, []>("op_3811_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3811_end_mask_0 = const()[name = tensor<string, []>("op_3811_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3811_cast_fp16 = slice_by_index(begin = var_3811_begin_0, end = concat_102, end_mask = var_3811_end_mask_0, x = seg_203_cast_fp16)[name = tensor<string, []>("op_3811_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1095_cast_fp16 = add(x = var_3797_cast_fp16, y = var_3811_cast_fp16)[name = tensor<string, []>("input_1095_cast_fp16")];
            tensor<string, []> input_1097_pad_type_0 = const()[name = tensor<string, []>("input_1097_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1097_strides_0 = const()[name = tensor<string, []>("input_1097_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1097_pad_0 = const()[name = tensor<string, []>("input_1097_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1097_dilations_0 = const()[name = tensor<string, []>("input_1097_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1097_groups_0 = const()[name = tensor<string, []>("input_1097_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd15_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd15_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12073536)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd15_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd15_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12089984)))];
            tensor<fp16, [1, 64, ?]> input_1097_cast_fp16 = conv(bias = net_xvector_block3_tdnnd15_cam_layer_linear1_bias_to_fp16, dilations = input_1097_dilations_0, groups = input_1097_groups_0, pad = input_1097_pad_0, pad_type = input_1097_pad_type_0, strides = input_1097_strides_0, weight = net_xvector_block3_tdnnd15_cam_layer_linear1_weight_to_fp16, x = input_1095_cast_fp16)[name = tensor<string, []>("input_1097_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_1099_cast_fp16 = relu(x = input_1097_cast_fp16)[name = tensor<string, []>("input_1099_cast_fp16")];
            tensor<string, []> input_1101_pad_type_0 = const()[name = tensor<string, []>("input_1101_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1101_strides_0 = const()[name = tensor<string, []>("input_1101_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1101_pad_0 = const()[name = tensor<string, []>("input_1101_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1101_dilations_0 = const()[name = tensor<string, []>("input_1101_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1101_groups_0 = const()[name = tensor<string, []>("input_1101_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd15_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd15_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12090176)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd15_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd15_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12094336)))];
            tensor<fp16, [1, 32, ?]> input_1101_cast_fp16 = conv(bias = net_xvector_block3_tdnnd15_cam_layer_linear2_bias_to_fp16, dilations = input_1101_dilations_0, groups = input_1101_groups_0, pad = input_1101_pad_0, pad_type = input_1101_pad_type_0, strides = input_1101_strides_0, weight = net_xvector_block3_tdnnd15_cam_layer_linear2_weight_to_fp16, x = input_1099_cast_fp16)[name = tensor<string, []>("input_1101_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_101_cast_fp16 = sigmoid(x = input_1101_cast_fp16)[name = tensor<string, []>("m_101_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3829_cast_fp16 = mul(x = y_101_cast_fp16, y = m_101_cast_fp16)[name = tensor<string, []>("op_3829_cast_fp16")];
            tensor<bool, []> input_1103_interleave_0 = const()[name = tensor<string, []>("input_1103_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 992, ?]> input_1103_cast_fp16 = concat(axis = var_11, interleave = input_1103_interleave_0, values = (input_1083_cast_fp16, var_3829_cast_fp16))[name = tensor<string, []>("input_1103_cast_fp16")];
            tensor<fp16, [992]> net_xvector_block3_tdnnd16_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd16_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [992]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12094464)))];
            tensor<fp16, [992]> net_xvector_block3_tdnnd16_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd16_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor<fp16, [992]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12096512)))];
            tensor<fp16, [992]> net_xvector_block3_tdnnd16_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd16_nonlinear1_batchnorm_weight_to_fp16"), val = tensor<fp16, [992]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12098560)))];
            tensor<fp16, [992]> net_xvector_block3_tdnnd16_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd16_nonlinear1_batchnorm_bias_to_fp16"), val = tensor<fp16, [992]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12100608)))];
            tensor<fp16, [1, 992, ?]> input_1105_cast_fp16 = batch_norm(beta = net_xvector_block3_tdnnd16_nonlinear1_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_block3_tdnnd16_nonlinear1_batchnorm_weight_to_fp16, mean = net_xvector_block3_tdnnd16_nonlinear1_batchnorm_running_mean_to_fp16, variance = net_xvector_block3_tdnnd16_nonlinear1_batchnorm_running_var_to_fp16, x = input_1103_cast_fp16)[name = tensor<string, []>("input_1105_cast_fp16")];
            tensor<fp16, [1, 992, ?]> input_1107_cast_fp16 = relu(x = input_1105_cast_fp16)[name = tensor<string, []>("input_1107_cast_fp16")];
            tensor<string, []> input_1109_pad_type_0 = const()[name = tensor<string, []>("input_1109_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1109_strides_0 = const()[name = tensor<string, []>("input_1109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1109_pad_0 = const()[name = tensor<string, []>("input_1109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1109_dilations_0 = const()[name = tensor<string, []>("input_1109_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1109_groups_0 = const()[name = tensor<string, []>("input_1109_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [128, 992, 1]> const_128_to_fp16 = const()[name = tensor<string, []>("const_128_to_fp16"), val = tensor<fp16, [128, 992, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12102656)))];
            tensor<fp16, [128]> const_129_to_fp16 = const()[name = tensor<string, []>("const_129_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12356672)))];
            tensor<fp16, [1, 128, ?]> input_1111_cast_fp16 = conv(bias = const_129_to_fp16, dilations = input_1109_dilations_0, groups = input_1109_groups_0, pad = input_1109_pad_0, pad_type = input_1109_pad_type_0, strides = input_1109_strides_0, weight = const_128_to_fp16, x = input_1107_cast_fp16)[name = tensor<string, []>("input_1111_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1113_cast_fp16 = relu(x = input_1111_cast_fp16)[name = tensor<string, []>("input_1113_cast_fp16")];
            tensor<string, []> y_pad_type_0 = const()[name = tensor<string, []>("y_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> y_pad_0 = const()[name = tensor<string, []>("y_pad_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [1]> y_dilations_0 = const()[name = tensor<string, []>("y_dilations_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> y_strides_0 = const()[name = tensor<string, []>("y_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> y_groups_0 = const()[name = tensor<string, []>("y_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 128, 3]> net_xvector_block3_tdnnd16_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd16_cam_layer_linear_local_weight_to_fp16"), val = tensor<fp16, [32, 128, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12356992)))];
            tensor<fp16, [1, 32, ?]> y_cast_fp16 = conv(dilations = y_dilations_0, groups = y_groups_0, pad = y_pad_0, pad_type = y_pad_type_0, strides = y_strides_0, weight = net_xvector_block3_tdnnd16_cam_layer_linear_local_weight_to_fp16, x = input_1113_cast_fp16)[name = tensor<string, []>("y_cast_fp16")];
            tensor<int32, [1]> var_3866_axes_0 = const()[name = tensor<string, []>("op_3866_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_3866_keep_dims_0 = const()[name = tensor<string, []>("op_3866_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, 1]> var_3866_cast_fp16 = reduce_mean(axes = var_3866_axes_0, keep_dims = var_3866_keep_dims_0, x = input_1113_cast_fp16)[name = tensor<string, []>("op_3866_cast_fp16")];
            tensor<int32, [1]> var_3867 = const()[name = tensor<string, []>("op_3867"), val = tensor<int32, [1]>([100])];
            tensor<int32, [1]> var_3868 = const()[name = tensor<string, []>("op_3868"), val = tensor<int32, [1]>([100])];
            tensor<string, []> seg_205_pad_type_0 = const()[name = tensor<string, []>("seg_205_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [2]> seg_205_pad_0 = const()[name = tensor<string, []>("seg_205_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<bool, []> seg_205_exclude_padding_from_average_0 = const()[name = tensor<string, []>("seg_205_exclude_padding_from_average_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> seg_205_ceil_mode_0 = const()[name = tensor<string, []>("seg_205_ceil_mode_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 128, ?]> seg_205_cast_fp16 = avg_pool(ceil_mode = seg_205_ceil_mode_0, exclude_padding_from_average = seg_205_exclude_padding_from_average_0, kernel_sizes = var_3867, pad = seg_205_pad_0, pad_type = seg_205_pad_type_0, strides = var_3868, x = input_1113_cast_fp16)[name = tensor<string, []>("seg_205_cast_fp16")];
            tensor<int32, [3]> var_3871_shape_cast_fp16 = shape(x = seg_205_cast_fp16)[name = tensor<string, []>("op_3871_shape_cast_fp16")];
            tensor<int32, []> gather_208 = const()[name = tensor<string, []>("gather_208"), val = tensor<int32, []>(1)];
            tensor<int32, []> gather_209 = const()[name = tensor<string, []>("gather_209"), val = tensor<int32, []>(128)];
            tensor<int32, []> gather_210_axis_0 = const()[name = tensor<string, []>("gather_210_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_210_batch_dims_0 = const()[name = tensor<string, []>("gather_210_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_210_validate_indices_0 = const()[name = tensor<string, []>("gather_210_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3871_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3871_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_210_to_uint16 = const()[name = tensor<string, []>("select_210_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3871_shape_cast_fp16_to_uint16 = cast(dtype = var_3871_shape_cast_fp16_to_uint16_dtype_0, x = var_3871_shape_cast_fp16)[name = tensor<string, []>("cast_111")];
            tensor<uint16, []> gather_210_cast_uint16 = gather(axis = gather_210_axis_0, batch_dims = gather_210_batch_dims_0, indices = select_210_to_uint16, validate_indices = gather_210_validate_indices_0, x = var_3871_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_210_cast_uint16")];
            tensor<string, []> gather_210_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_210_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1]> var_3874_axes_0 = const()[name = tensor<string, []>("op_3874_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 128, ?, 1]> var_3874_cast_fp16 = expand_dims(axes = var_3874_axes_0, x = seg_205_cast_fp16)[name = tensor<string, []>("op_3874_cast_fp16")];
            tensor<int32, []> concat_103_axis_0 = const()[name = tensor<string, []>("concat_103_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_103_interleave_0 = const()[name = tensor<string, []>("concat_103_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_210_cast_uint16_to_int32 = cast(dtype = gather_210_cast_uint16_to_int32_dtype_0, x = gather_210_cast_uint16)[name = tensor<string, []>("cast_110")];
            tensor<int32, [4]> concat_103 = concat(axis = concat_103_axis_0, interleave = concat_103_interleave_0, values = (gather_208, gather_209, gather_210_cast_uint16_to_int32, var_3))[name = tensor<string, []>("concat_103")];
            tensor<int32, [4]> shape_262_cast_fp16 = shape(x = var_3874_cast_fp16)[name = tensor<string, []>("shape_262_cast_fp16")];
            tensor<int32, [4]> real_div_51 = real_div(x = concat_103, y = shape_262_cast_fp16)[name = tensor<string, []>("real_div_51")];
            tensor<fp16, [?, ?, ?, ?]> var_3876_cast_fp16 = tile(reps = real_div_51, x = var_3874_cast_fp16)[name = tensor<string, []>("op_3876_cast_fp16")];
            tensor<int32, [3]> var_3877 = const()[name = tensor<string, []>("op_3877"), val = tensor<int32, [3]>([1, 128, -1])];
            tensor<fp16, [1, 128, ?]> seg_cast_fp16 = reshape(shape = var_3877, x = var_3876_cast_fp16)[name = tensor<string, []>("seg_cast_fp16")];
            tensor<int32, [3]> var_3879_shape_cast_fp16 = shape(x = input_1113_cast_fp16)[name = tensor<string, []>("op_3879_shape_cast_fp16")];
            tensor<int32, []> gather_211_axis_0 = const()[name = tensor<string, []>("gather_211_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> gather_211_batch_dims_0 = const()[name = tensor<string, []>("gather_211_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> gather_211_validate_indices_0 = const()[name = tensor<string, []>("gather_211_validate_indices_0"), val = tensor<bool, []>(false)];
            tensor<string, []> var_3879_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor<string, []>("op_3879_shape_cast_fp16_to_uint16_dtype_0"), val = tensor<string, []>("uint16")];
            tensor<uint16, []> select_211_to_uint16 = const()[name = tensor<string, []>("select_211_to_uint16"), val = tensor<uint16, []>(2)];
            tensor<uint16, [3]> var_3879_shape_cast_fp16_to_uint16 = cast(dtype = var_3879_shape_cast_fp16_to_uint16_dtype_0, x = var_3879_shape_cast_fp16)[name = tensor<string, []>("cast_109")];
            tensor<uint16, []> gather_211_cast_uint16 = gather(axis = gather_211_axis_0, batch_dims = gather_211_batch_dims_0, indices = select_211_to_uint16, validate_indices = gather_211_validate_indices_0, x = var_3879_shape_cast_fp16_to_uint16)[name = tensor<string, []>("gather_211_cast_uint16")];
            tensor<string, []> gather_211_cast_uint16_to_int32_dtype_0 = const()[name = tensor<string, []>("gather_211_cast_uint16_to_int32_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, []> concat_104_values0_0 = const()[name = tensor<string, []>("concat_104_values0_0"), val = tensor<int32, []>(1)];
            tensor<int32, []> concat_104_values1_0 = const()[name = tensor<string, []>("concat_104_values1_0"), val = tensor<int32, []>(128)];
            tensor<int32, []> concat_104_axis_0 = const()[name = tensor<string, []>("concat_104_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_104_interleave_0 = const()[name = tensor<string, []>("concat_104_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> gather_211_cast_uint16_to_int32 = cast(dtype = gather_211_cast_uint16_to_int32_dtype_0, x = gather_211_cast_uint16)[name = tensor<string, []>("cast_108")];
            tensor<int32, [3]> concat_104 = concat(axis = concat_104_axis_0, interleave = concat_104_interleave_0, values = (concat_104_values0_0, concat_104_values1_0, gather_211_cast_uint16_to_int32))[name = tensor<string, []>("concat_104")];
            tensor<int32, [3]> var_3880_begin_0 = const()[name = tensor<string, []>("op_3880_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> var_3880_end_mask_0 = const()[name = tensor<string, []>("op_3880_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 128, ?]> var_3880_cast_fp16 = slice_by_index(begin = var_3880_begin_0, end = concat_104, end_mask = var_3880_end_mask_0, x = seg_cast_fp16)[name = tensor<string, []>("op_3880_cast_fp16")];
            tensor<fp16, [1, 128, ?]> input_1115_cast_fp16 = add(x = var_3866_cast_fp16, y = var_3880_cast_fp16)[name = tensor<string, []>("input_1115_cast_fp16")];
            tensor<string, []> input_1117_pad_type_0 = const()[name = tensor<string, []>("input_1117_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1117_strides_0 = const()[name = tensor<string, []>("input_1117_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1117_pad_0 = const()[name = tensor<string, []>("input_1117_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1117_dilations_0 = const()[name = tensor<string, []>("input_1117_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1117_groups_0 = const()[name = tensor<string, []>("input_1117_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [64, 128, 1]> net_xvector_block3_tdnnd16_cam_layer_linear1_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd16_cam_layer_linear1_weight_to_fp16"), val = tensor<fp16, [64, 128, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12381632)))];
            tensor<fp16, [64]> net_xvector_block3_tdnnd16_cam_layer_linear1_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd16_cam_layer_linear1_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12398080)))];
            tensor<fp16, [1, 64, ?]> input_1117_cast_fp16 = conv(bias = net_xvector_block3_tdnnd16_cam_layer_linear1_bias_to_fp16, dilations = input_1117_dilations_0, groups = input_1117_groups_0, pad = input_1117_pad_0, pad_type = input_1117_pad_type_0, strides = input_1117_strides_0, weight = net_xvector_block3_tdnnd16_cam_layer_linear1_weight_to_fp16, x = input_1115_cast_fp16)[name = tensor<string, []>("input_1117_cast_fp16")];
            tensor<fp16, [1, 64, ?]> input_1119_cast_fp16 = relu(x = input_1117_cast_fp16)[name = tensor<string, []>("input_1119_cast_fp16")];
            tensor<string, []> input_1121_pad_type_0 = const()[name = tensor<string, []>("input_1121_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1121_strides_0 = const()[name = tensor<string, []>("input_1121_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1121_pad_0 = const()[name = tensor<string, []>("input_1121_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1121_dilations_0 = const()[name = tensor<string, []>("input_1121_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1121_groups_0 = const()[name = tensor<string, []>("input_1121_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [32, 64, 1]> net_xvector_block3_tdnnd16_cam_layer_linear2_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd16_cam_layer_linear2_weight_to_fp16"), val = tensor<fp16, [32, 64, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12398272)))];
            tensor<fp16, [32]> net_xvector_block3_tdnnd16_cam_layer_linear2_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_block3_tdnnd16_cam_layer_linear2_bias_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12402432)))];
            tensor<fp16, [1, 32, ?]> input_1121_cast_fp16 = conv(bias = net_xvector_block3_tdnnd16_cam_layer_linear2_bias_to_fp16, dilations = input_1121_dilations_0, groups = input_1121_groups_0, pad = input_1121_pad_0, pad_type = input_1121_pad_type_0, strides = input_1121_strides_0, weight = net_xvector_block3_tdnnd16_cam_layer_linear2_weight_to_fp16, x = input_1119_cast_fp16)[name = tensor<string, []>("input_1121_cast_fp16")];
            tensor<fp16, [1, 32, ?]> m_cast_fp16 = sigmoid(x = input_1121_cast_fp16)[name = tensor<string, []>("m_cast_fp16")];
            tensor<fp16, [1, 32, ?]> var_3898_cast_fp16 = mul(x = y_cast_fp16, y = m_cast_fp16)[name = tensor<string, []>("op_3898_cast_fp16")];
            tensor<bool, []> input_1123_interleave_0 = const()[name = tensor<string, []>("input_1123_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 1024, ?]> input_1123_cast_fp16 = concat(axis = var_11, interleave = input_1123_interleave_0, values = (input_1103_cast_fp16, var_3898_cast_fp16))[name = tensor<string, []>("input_1123_cast_fp16")];
            tensor<fp16, [1024]> net_xvector_transit3_nonlinear_batchnorm_running_mean_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit3_nonlinear_batchnorm_running_mean_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12402560)))];
            tensor<fp16, [1024]> net_xvector_transit3_nonlinear_batchnorm_running_var_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit3_nonlinear_batchnorm_running_var_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12404672)))];
            tensor<fp16, [1024]> net_xvector_transit3_nonlinear_batchnorm_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit3_nonlinear_batchnorm_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12406784)))];
            tensor<fp16, [1024]> net_xvector_transit3_nonlinear_batchnorm_bias_to_fp16 = const()[name = tensor<string, []>("net_xvector_transit3_nonlinear_batchnorm_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12408896)))];
            tensor<fp16, [1, 1024, ?]> input_1125_cast_fp16 = batch_norm(beta = net_xvector_transit3_nonlinear_batchnorm_bias_to_fp16, epsilon = var_8_to_fp16, gamma = net_xvector_transit3_nonlinear_batchnorm_weight_to_fp16, mean = net_xvector_transit3_nonlinear_batchnorm_running_mean_to_fp16, variance = net_xvector_transit3_nonlinear_batchnorm_running_var_to_fp16, x = input_1123_cast_fp16)[name = tensor<string, []>("input_1125_cast_fp16")];
            tensor<fp16, [1, 1024, ?]> input_1127_cast_fp16 = relu(x = input_1125_cast_fp16)[name = tensor<string, []>("input_1127_cast_fp16")];
            tensor<string, []> input_1129_pad_type_0 = const()[name = tensor<string, []>("input_1129_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1129_strides_0 = const()[name = tensor<string, []>("input_1129_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1129_pad_0 = const()[name = tensor<string, []>("input_1129_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1129_dilations_0 = const()[name = tensor<string, []>("input_1129_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1129_groups_0 = const()[name = tensor<string, []>("input_1129_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 1024, 1]> const_130_to_fp16 = const()[name = tensor<string, []>("const_130_to_fp16"), val = tensor<fp16, [512, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12411008)))];
            tensor<fp16, [512]> const_131_to_fp16 = const()[name = tensor<string, []>("const_131_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13459648)))];
            tensor<fp16, [1, 512, ?]> input_1131_cast_fp16 = conv(bias = const_131_to_fp16, dilations = input_1129_dilations_0, groups = input_1129_groups_0, pad = input_1129_pad_0, pad_type = input_1129_pad_type_0, strides = input_1129_strides_0, weight = const_130_to_fp16, x = input_1127_cast_fp16)[name = tensor<string, []>("input_1131_cast_fp16")];
            tensor<fp16, [1, 512, ?]> x_3_cast_fp16 = relu(x = input_1131_cast_fp16)[name = tensor<string, []>("x_3_cast_fp16")];
            tensor<int32, [1]> mean_axes_0 = const()[name = tensor<string, []>("mean_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> mean_keep_dims_0 = const()[name = tensor<string, []>("mean_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 512]> mean_cast_fp16 = reduce_mean(axes = mean_axes_0, keep_dims = mean_keep_dims_0, x = x_3_cast_fp16)[name = tensor<string, []>("mean_cast_fp16")];
            tensor<int32, [1]> reduce_mean_0_axes_0 = const()[name = tensor<string, []>("reduce_mean_0_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> reduce_mean_0_keep_dims_0 = const()[name = tensor<string, []>("reduce_mean_0_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp16, [1, 512, 1]> reduce_mean_0_cast_fp16 = reduce_mean(axes = reduce_mean_0_axes_0, keep_dims = reduce_mean_0_keep_dims_0, x = x_3_cast_fp16)[name = tensor<string, []>("reduce_mean_0_cast_fp16")];
            tensor<fp16, [1, 512, ?]> sub_0_cast_fp16 = sub(x = x_3_cast_fp16, y = reduce_mean_0_cast_fp16)[name = tensor<string, []>("sub_0_cast_fp16")];
            tensor<fp16, [1, 512, ?]> square_0_cast_fp16 = square(x = sub_0_cast_fp16)[name = tensor<string, []>("square_0_cast_fp16")];
            tensor<int32, [1]> reduce_mean_1_axes_0 = const()[name = tensor<string, []>("reduce_mean_1_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> reduce_mean_1_keep_dims_0 = const()[name = tensor<string, []>("reduce_mean_1_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 512]> reduce_mean_1_cast_fp16 = reduce_mean(axes = reduce_mean_1_axes_0, keep_dims = reduce_mean_1_keep_dims_0, x = square_0_cast_fp16)[name = tensor<string, []>("reduce_mean_1_cast_fp16")];
            tensor<int32, [3]> shape_264_cast_fp16 = shape(x = x_3_cast_fp16)[name = tensor<string, []>("shape_264_cast_fp16")];
            tensor<int32, [1]> slice_by_index_212_begin_0 = const()[name = tensor<string, []>("slice_by_index_212_begin_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [1]> slice_by_index_212_end_0 = const()[name = tensor<string, []>("slice_by_index_212_end_0"), val = tensor<int32, [1]>([0])];
            tensor<bool, [1]> slice_by_index_212_squeeze_mask_0 = const()[name = tensor<string, []>("slice_by_index_212_squeeze_mask_0"), val = tensor<bool, [1]>([true])];
            tensor<int32, []> slice_by_index_212 = slice_by_index(begin = slice_by_index_212_begin_0, end = slice_by_index_212_end_0, squeeze_mask = slice_by_index_212_squeeze_mask_0, x = shape_264_cast_fp16)[name = tensor<string, []>("slice_by_index_212")];
            tensor<int32, []> concat_105_axis_0 = const()[name = tensor<string, []>("concat_105_axis_0"), val = tensor<int32, []>(0)];
            tensor<bool, []> concat_105_interleave_0 = const()[name = tensor<string, []>("concat_105_interleave_0"), val = tensor<bool, []>(false)];
            tensor<int32, [1]> concat_105 = concat(axis = concat_105_axis_0, interleave = concat_105_interleave_0, values = slice_by_index_212)[name = tensor<string, []>("concat_105")];
            tensor<bool, []> reduce_prod_0_keep_dims_0 = const()[name = tensor<string, []>("reduce_prod_0_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<int32, []> reduce_prod_0 = reduce_prod(keep_dims = reduce_prod_0_keep_dims_0, x = concat_105)[name = tensor<string, []>("reduce_prod_0")];
            tensor<string, []> cast_105_to_fp16_dtype_0 = const()[name = tensor<string, []>("cast_105_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, []> sub_1_y_0_to_fp16 = const()[name = tensor<string, []>("sub_1_y_0_to_fp16"), val = tensor<fp16, []>(0x1p+0)];
            tensor<fp16, []> reduce_prod_0_to_fp16 = cast(dtype = cast_105_to_fp16_dtype_0, x = reduce_prod_0)[name = tensor<string, []>("cast_107")];
            tensor<fp16, []> sub_1_cast_fp16 = sub(x = reduce_prod_0_to_fp16, y = sub_1_y_0_to_fp16)[name = tensor<string, []>("sub_1_cast_fp16")];
            tensor<fp16, []> real_div_52_cast_fp16 = real_div(x = reduce_prod_0_to_fp16, y = sub_1_cast_fp16)[name = tensor<string, []>("real_div_52_cast_fp16")];
            tensor<fp16, [1, 512]> mul_0_cast_fp16 = mul(x = reduce_mean_1_cast_fp16, y = real_div_52_cast_fp16)[name = tensor<string, []>("mul_0_cast_fp16")];
            tensor<fp16, [1, 512]> sqrt_0_cast_fp16 = sqrt(x = mul_0_cast_fp16)[name = tensor<string, []>("sqrt_0_cast_fp16")];
            tensor<bool, []> x_interleave_0 = const()[name = tensor<string, []>("x_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 1024]> x_cast_fp16 = concat(axis = var_4, interleave = x_interleave_0, values = (mean_cast_fp16, sqrt_0_cast_fp16))[name = tensor<string, []>("x_cast_fp16")];
            tensor<int32, [1]> input_1133_axes_0 = const()[name = tensor<string, []>("input_1133_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 1024, 1]> input_1133_cast_fp16 = expand_dims(axes = input_1133_axes_0, x = x_cast_fp16)[name = tensor<string, []>("input_1133_cast_fp16")];
            tensor<string, []> var_3937_pad_type_0 = const()[name = tensor<string, []>("op_3937_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> var_3937_strides_0 = const()[name = tensor<string, []>("op_3937_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> var_3937_pad_0 = const()[name = tensor<string, []>("op_3937_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> var_3937_dilations_0 = const()[name = tensor<string, []>("op_3937_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> var_3937_groups_0 = const()[name = tensor<string, []>("op_3937_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [192, 1024, 1]> net_xvector_dense_linear_weight_to_fp16 = const()[name = tensor<string, []>("net_xvector_dense_linear_weight_to_fp16"), val = tensor<fp16, [192, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13460736)))];
            tensor<fp16, [1, 192, 1]> var_3937_cast_fp16 = conv(dilations = var_3937_dilations_0, groups = var_3937_groups_0, pad = var_3937_pad_0, pad_type = var_3937_pad_type_0, strides = var_3937_strides_0, weight = net_xvector_dense_linear_weight_to_fp16, x = input_1133_cast_fp16)[name = tensor<string, []>("op_3937_cast_fp16")];
            tensor<int32, [1]> input_axes_0 = const()[name = tensor<string, []>("input_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 192]> input_cast_fp16 = squeeze(axes = input_axes_0, x = var_3937_cast_fp16)[name = tensor<string, []>("input_cast_fp16")];
            tensor<fp16, [1, 192]> reshape_0_to_fp16 = const()[name = tensor<string, []>("reshape_0_to_fp16"), val = tensor<fp16, [1, 192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13854016)))];
            tensor<fp16, [1, 192]> sub_2_cast_fp16 = sub(x = input_cast_fp16, y = reshape_0_to_fp16)[name = tensor<string, []>("sub_2_cast_fp16")];
            tensor<fp16, [1, 192]> _inversed_3942_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_3942_y_0_to_fp16"), val = tensor<fp16, [1, 192]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13854464)))];
            tensor<fp16, [1, 192]> embedding = mul(x = sub_2_cast_fp16, y = _inversed_3942_y_0_to_fp16)[name = tensor<string, []>("_inversed_3942_cast_fp16")];
        } -> (embedding);
}