diff --git "a/CamPlusPlus.mlmodelc/model.mil" "b/CamPlusPlus.mlmodelc/model.mil" new file mode 100644--- /dev/null +++ "b/CamPlusPlus.mlmodelc/model.mil" @@ -0,0 +1,3328 @@ +program(1.0) +[buildInfo = dict, tensor>({{"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(tensor feats) { + tensor var_4 = const()[name = tensor("op_4"), val = tensor(-1)]; + tensor var_11 = const()[name = tensor("op_11"), val = tensor(1)]; + tensor var_16 = const()[name = tensor("op_16"), val = tensor([0, 2, 1])]; + tensor feats_to_fp16_dtype_0 = const()[name = tensor("feats_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor input_1_axes_0 = const()[name = tensor("input_1_axes_0"), val = tensor([1])]; + tensor feats_to_fp16 = cast(dtype = feats_to_fp16_dtype_0, x = feats)[name = tensor("cast_55")]; + tensor x_1_cast_fp16 = transpose(perm = var_16, x = feats_to_fp16)[name = tensor("transpose_0")]; + tensor input_1_cast_fp16 = expand_dims(axes = input_1_axes_0, x = x_1_cast_fp16)[name = tensor("input_1_cast_fp16")]; + tensor input_3_pad_type_0 = const()[name = tensor("input_3_pad_type_0"), val = tensor("custom")]; + tensor input_3_pad_0 = const()[name = tensor("input_3_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_3_strides_0 = const()[name = tensor("input_3_strides_0"), val = tensor([1, 1])]; + tensor input_3_dilations_0 = const()[name = tensor("input_3_dilations_0"), val = tensor([1, 1])]; + tensor input_3_groups_0 = const()[name = tensor("input_3_groups_0"), val = tensor(1)]; + tensor const_212_to_fp16 = const()[name = tensor("const_212_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor const_213_to_fp16 = const()[name = tensor("const_213_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(704)))]; + tensor input_5_cast_fp16 = conv(bias = const_213_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_212_to_fp16, x = input_1_cast_fp16)[name = tensor("input_5_cast_fp16")]; + tensor input_7_cast_fp16 = relu(x = input_5_cast_fp16)[name = tensor("input_7_cast_fp16")]; + tensor input_9_pad_type_0 = const()[name = tensor("input_9_pad_type_0"), val = tensor("custom")]; + tensor input_9_pad_0 = const()[name = tensor("input_9_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_9_strides_0 = const()[name = tensor("input_9_strides_0"), val = tensor([2, 1])]; + tensor input_9_dilations_0 = const()[name = tensor("input_9_dilations_0"), val = tensor([1, 1])]; + tensor input_9_groups_0 = const()[name = tensor("input_9_groups_0"), val = tensor(1)]; + tensor const_214_to_fp16 = const()[name = tensor("const_214_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(832)))]; + tensor const_215_to_fp16 = const()[name = tensor("const_215_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19328)))]; + tensor input_11_cast_fp16 = conv(bias = const_215_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_214_to_fp16, x = input_7_cast_fp16)[name = tensor("input_11_cast_fp16")]; + tensor input_13_cast_fp16 = relu(x = input_11_cast_fp16)[name = tensor("input_13_cast_fp16")]; + tensor input_15_pad_type_0 = const()[name = tensor("input_15_pad_type_0"), val = tensor("custom")]; + tensor input_15_pad_0 = const()[name = tensor("input_15_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_15_strides_0 = const()[name = tensor("input_15_strides_0"), val = tensor([1, 1])]; + tensor input_15_dilations_0 = const()[name = tensor("input_15_dilations_0"), val = tensor([1, 1])]; + tensor input_15_groups_0 = const()[name = tensor("input_15_groups_0"), val = tensor(1)]; + tensor const_216_to_fp16 = const()[name = tensor("const_216_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19456)))]; + tensor const_217_to_fp16 = const()[name = tensor("const_217_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37952)))]; + tensor out_1_cast_fp16 = conv(bias = const_217_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_216_to_fp16, x = input_13_cast_fp16)[name = tensor("out_1_cast_fp16")]; + tensor input_17_pad_type_0 = const()[name = tensor("input_17_pad_type_0"), val = tensor("valid")]; + tensor input_17_strides_0 = const()[name = tensor("input_17_strides_0"), val = tensor([2, 1])]; + tensor input_17_pad_0 = const()[name = tensor("input_17_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_17_dilations_0 = const()[name = tensor("input_17_dilations_0"), val = tensor([1, 1])]; + tensor input_17_groups_0 = const()[name = tensor("input_17_groups_0"), val = tensor(1)]; + tensor const_218_to_fp16 = const()[name = tensor("const_218_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38080)))]; + tensor const_219_to_fp16 = const()[name = tensor("const_219_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40192)))]; + tensor var_79_cast_fp16 = conv(bias = const_219_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_218_to_fp16, x = input_7_cast_fp16)[name = tensor("op_79_cast_fp16")]; + tensor input_19_cast_fp16 = add(x = out_1_cast_fp16, y = var_79_cast_fp16)[name = tensor("input_19_cast_fp16")]; + tensor input_21_cast_fp16 = relu(x = input_19_cast_fp16)[name = tensor("input_21_cast_fp16")]; + tensor input_23_pad_type_0 = const()[name = tensor("input_23_pad_type_0"), val = tensor("custom")]; + tensor input_23_pad_0 = const()[name = tensor("input_23_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_23_strides_0 = const()[name = tensor("input_23_strides_0"), val = tensor([1, 1])]; + tensor input_23_dilations_0 = const()[name = tensor("input_23_dilations_0"), val = tensor([1, 1])]; + tensor input_23_groups_0 = const()[name = tensor("input_23_groups_0"), val = tensor(1)]; + tensor const_220_to_fp16 = const()[name = tensor("const_220_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40320)))]; + tensor const_221_to_fp16 = const()[name = tensor("const_221_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58816)))]; + tensor input_25_cast_fp16 = conv(bias = const_221_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_220_to_fp16, x = input_21_cast_fp16)[name = tensor("input_25_cast_fp16")]; + tensor input_27_cast_fp16 = relu(x = input_25_cast_fp16)[name = tensor("input_27_cast_fp16")]; + tensor input_29_pad_type_0 = const()[name = tensor("input_29_pad_type_0"), val = tensor("custom")]; + tensor input_29_pad_0 = const()[name = tensor("input_29_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_29_strides_0 = const()[name = tensor("input_29_strides_0"), val = tensor([1, 1])]; + tensor input_29_dilations_0 = const()[name = tensor("input_29_dilations_0"), val = tensor([1, 1])]; + tensor input_29_groups_0 = const()[name = tensor("input_29_groups_0"), val = tensor(1)]; + tensor const_222_to_fp16 = const()[name = tensor("const_222_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58944)))]; + tensor const_223_to_fp16 = const()[name = tensor("const_223_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77440)))]; + tensor out_3_cast_fp16 = conv(bias = const_223_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_222_to_fp16, x = input_27_cast_fp16)[name = tensor("out_3_cast_fp16")]; + tensor input_31_cast_fp16 = add(x = out_3_cast_fp16, y = input_21_cast_fp16)[name = tensor("input_31_cast_fp16")]; + tensor input_33_cast_fp16 = relu(x = input_31_cast_fp16)[name = tensor("input_33_cast_fp16")]; + tensor input_35_pad_type_0 = const()[name = tensor("input_35_pad_type_0"), val = tensor("custom")]; + tensor input_35_pad_0 = const()[name = tensor("input_35_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_35_strides_0 = const()[name = tensor("input_35_strides_0"), val = tensor([2, 1])]; + tensor input_35_dilations_0 = const()[name = tensor("input_35_dilations_0"), val = tensor([1, 1])]; + tensor input_35_groups_0 = const()[name = tensor("input_35_groups_0"), val = tensor(1)]; + tensor const_224_to_fp16 = const()[name = tensor("const_224_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77568)))]; + tensor const_225_to_fp16 = const()[name = tensor("const_225_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96064)))]; + tensor input_37_cast_fp16 = conv(bias = const_225_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_224_to_fp16, x = input_33_cast_fp16)[name = tensor("input_37_cast_fp16")]; + tensor input_39_cast_fp16 = relu(x = input_37_cast_fp16)[name = tensor("input_39_cast_fp16")]; + tensor input_41_pad_type_0 = const()[name = tensor("input_41_pad_type_0"), val = tensor("custom")]; + tensor input_41_pad_0 = const()[name = tensor("input_41_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_41_strides_0 = const()[name = tensor("input_41_strides_0"), val = tensor([1, 1])]; + tensor input_41_dilations_0 = const()[name = tensor("input_41_dilations_0"), val = tensor([1, 1])]; + tensor input_41_groups_0 = const()[name = tensor("input_41_groups_0"), val = tensor(1)]; + tensor const_226_to_fp16 = const()[name = tensor("const_226_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96192)))]; + tensor const_227_to_fp16 = const()[name = tensor("const_227_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114688)))]; + tensor out_5_cast_fp16 = conv(bias = const_227_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_226_to_fp16, x = input_39_cast_fp16)[name = tensor("out_5_cast_fp16")]; + tensor input_43_pad_type_0 = const()[name = tensor("input_43_pad_type_0"), val = tensor("valid")]; + tensor input_43_strides_0 = const()[name = tensor("input_43_strides_0"), val = tensor([2, 1])]; + tensor input_43_pad_0 = const()[name = tensor("input_43_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_43_dilations_0 = const()[name = tensor("input_43_dilations_0"), val = tensor([1, 1])]; + tensor input_43_groups_0 = const()[name = tensor("input_43_groups_0"), val = tensor(1)]; + tensor const_228_to_fp16 = const()[name = tensor("const_228_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114816)))]; + tensor const_229_to_fp16 = const()[name = tensor("const_229_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116928)))]; + tensor var_153_cast_fp16 = conv(bias = const_229_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_228_to_fp16, x = input_33_cast_fp16)[name = tensor("op_153_cast_fp16")]; + tensor input_45_cast_fp16 = add(x = out_5_cast_fp16, y = var_153_cast_fp16)[name = tensor("input_45_cast_fp16")]; + tensor input_47_cast_fp16 = relu(x = input_45_cast_fp16)[name = tensor("input_47_cast_fp16")]; + tensor input_49_pad_type_0 = const()[name = tensor("input_49_pad_type_0"), val = tensor("custom")]; + tensor input_49_pad_0 = const()[name = tensor("input_49_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_49_strides_0 = const()[name = tensor("input_49_strides_0"), val = tensor([1, 1])]; + tensor input_49_dilations_0 = const()[name = tensor("input_49_dilations_0"), val = tensor([1, 1])]; + tensor input_49_groups_0 = const()[name = tensor("input_49_groups_0"), val = tensor(1)]; + tensor const_230_to_fp16 = const()[name = tensor("const_230_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(117056)))]; + tensor const_231_to_fp16 = const()[name = tensor("const_231_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135552)))]; + tensor input_51_cast_fp16 = conv(bias = const_231_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_230_to_fp16, x = input_47_cast_fp16)[name = tensor("input_51_cast_fp16")]; + tensor input_53_cast_fp16 = relu(x = input_51_cast_fp16)[name = tensor("input_53_cast_fp16")]; + tensor input_55_pad_type_0 = const()[name = tensor("input_55_pad_type_0"), val = tensor("custom")]; + tensor input_55_pad_0 = const()[name = tensor("input_55_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_55_strides_0 = const()[name = tensor("input_55_strides_0"), val = tensor([1, 1])]; + tensor input_55_dilations_0 = const()[name = tensor("input_55_dilations_0"), val = tensor([1, 1])]; + tensor input_55_groups_0 = const()[name = tensor("input_55_groups_0"), val = tensor(1)]; + tensor const_232_to_fp16 = const()[name = tensor("const_232_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135680)))]; + tensor const_233_to_fp16 = const()[name = tensor("const_233_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154176)))]; + tensor out_7_cast_fp16 = conv(bias = const_233_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_232_to_fp16, x = input_53_cast_fp16)[name = tensor("out_7_cast_fp16")]; + tensor input_57_cast_fp16 = add(x = out_7_cast_fp16, y = input_47_cast_fp16)[name = tensor("input_57_cast_fp16")]; + tensor input_59_cast_fp16 = relu(x = input_57_cast_fp16)[name = tensor("input_59_cast_fp16")]; + tensor input_61_pad_type_0 = const()[name = tensor("input_61_pad_type_0"), val = tensor("custom")]; + tensor input_61_pad_0 = const()[name = tensor("input_61_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_61_strides_0 = const()[name = tensor("input_61_strides_0"), val = tensor([2, 1])]; + tensor input_61_dilations_0 = const()[name = tensor("input_61_dilations_0"), val = tensor([1, 1])]; + tensor input_61_groups_0 = const()[name = tensor("input_61_groups_0"), val = tensor(1)]; + tensor const_234_to_fp16 = const()[name = tensor("const_234_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154304)))]; + tensor const_235_to_fp16 = const()[name = tensor("const_235_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172800)))]; + tensor input_63_cast_fp16 = conv(bias = const_235_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_234_to_fp16, x = input_59_cast_fp16)[name = tensor("input_63_cast_fp16")]; + tensor out_cast_fp16 = relu(x = input_63_cast_fp16)[name = tensor("out_cast_fp16")]; + tensor var_205 = const()[name = tensor("op_205"), val = tensor([1, 320, 1000])]; + tensor input_65_cast_fp16 = reshape(shape = var_205, x = out_cast_fp16)[name = tensor("input_65_cast_fp16")]; + tensor input_67_pad_type_0 = const()[name = tensor("input_67_pad_type_0"), val = tensor("custom")]; + tensor input_67_pad_0 = const()[name = tensor("input_67_pad_0"), val = tensor([2, 2])]; + tensor input_67_strides_0 = const()[name = tensor("input_67_strides_0"), val = tensor([2])]; + tensor input_67_dilations_0 = const()[name = tensor("input_67_dilations_0"), val = tensor([1])]; + tensor input_67_groups_0 = const()[name = tensor("input_67_groups_0"), val = tensor(1)]; + tensor const_236_to_fp16 = const()[name = tensor("const_236_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(172928)))]; + tensor const_237_to_fp16 = const()[name = tensor("const_237_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(582592)))]; + tensor input_69_cast_fp16 = conv(bias = const_237_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_236_to_fp16, x = input_65_cast_fp16)[name = tensor("input_69_cast_fp16")]; + tensor input_71_cast_fp16 = relu(x = input_69_cast_fp16)[name = tensor("input_71_cast_fp16")]; + tensor net_xvector_block1_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(582912)))]; + tensor net_xvector_block1_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(583232)))]; + tensor net_xvector_block1_tdnnd1_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd1_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(583552)))]; + tensor net_xvector_block1_tdnnd1_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd1_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(583872)))]; + tensor var_8_to_fp16 = const()[name = tensor("op_8_to_fp16"), val = tensor(0x1.5p-17)]; + tensor 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("input_73_cast_fp16")]; + tensor input_75_cast_fp16 = relu(x = input_73_cast_fp16)[name = tensor("input_75_cast_fp16")]; + tensor input_77_pad_type_0 = const()[name = tensor("input_77_pad_type_0"), val = tensor("valid")]; + tensor input_77_strides_0 = const()[name = tensor("input_77_strides_0"), val = tensor([1])]; + tensor input_77_pad_0 = const()[name = tensor("input_77_pad_0"), val = tensor([0, 0])]; + tensor input_77_dilations_0 = const()[name = tensor("input_77_dilations_0"), val = tensor([1])]; + tensor input_77_groups_0 = const()[name = tensor("input_77_groups_0"), val = tensor(1)]; + tensor const_238_to_fp16 = const()[name = tensor("const_238_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(584192)))]; + tensor const_239_to_fp16 = const()[name = tensor("const_239_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(617024)))]; + tensor input_79_cast_fp16 = conv(bias = const_239_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_238_to_fp16, x = input_75_cast_fp16)[name = tensor("input_79_cast_fp16")]; + tensor input_81_cast_fp16 = relu(x = input_79_cast_fp16)[name = tensor("input_81_cast_fp16")]; + tensor y_1_pad_type_0 = const()[name = tensor("y_1_pad_type_0"), val = tensor("custom")]; + tensor y_1_pad_0 = const()[name = tensor("y_1_pad_0"), val = tensor([1, 1])]; + tensor y_1_strides_0 = const()[name = tensor("y_1_strides_0"), val = tensor([1])]; + tensor y_1_dilations_0 = const()[name = tensor("y_1_dilations_0"), val = tensor([1])]; + tensor y_1_groups_0 = const()[name = tensor("y_1_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd1_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd1_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(617344)))]; + tensor 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("y_1_cast_fp16")]; + tensor var_277_axes_0 = const()[name = tensor("op_277_axes_0"), val = tensor([-1])]; + tensor var_277_keep_dims_0 = const()[name = tensor("op_277_keep_dims_0"), val = tensor(true)]; + tensor 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("op_277_cast_fp16")]; + tensor var_278 = const()[name = tensor("op_278"), val = tensor([100])]; + tensor var_279 = const()[name = tensor("op_279"), val = tensor([100])]; + tensor seg_1_pad_type_0 = const()[name = tensor("seg_1_pad_type_0"), val = tensor("custom")]; + tensor seg_1_pad_0 = const()[name = tensor("seg_1_pad_0"), val = tensor([0, 0])]; + tensor seg_1_exclude_padding_from_average_0 = const()[name = tensor("seg_1_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_1_ceil_mode_0 = const()[name = tensor("seg_1_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_1_cast_fp16")]; + tensor var_285_axes_0 = const()[name = tensor("op_285_axes_0"), val = tensor([-1])]; + tensor var_285_cast_fp16 = expand_dims(axes = var_285_axes_0, x = seg_1_cast_fp16)[name = tensor("op_285_cast_fp16")]; + tensor var_287_reps_0 = const()[name = tensor("op_287_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_287_cast_fp16 = tile(reps = var_287_reps_0, x = var_285_cast_fp16)[name = tensor("op_287_cast_fp16")]; + tensor var_288 = const()[name = tensor("op_288"), val = tensor([1, 128, -1])]; + tensor seg_3_cast_fp16 = reshape(shape = var_288, x = var_287_cast_fp16)[name = tensor("seg_3_cast_fp16")]; + tensor input_83_cast_fp16 = add(x = var_277_cast_fp16, y = seg_3_cast_fp16)[name = tensor("input_83_cast_fp16")]; + tensor input_85_pad_type_0 = const()[name = tensor("input_85_pad_type_0"), val = tensor("valid")]; + tensor input_85_strides_0 = const()[name = tensor("input_85_strides_0"), val = tensor([1])]; + tensor input_85_pad_0 = const()[name = tensor("input_85_pad_0"), val = tensor([0, 0])]; + tensor input_85_dilations_0 = const()[name = tensor("input_85_dilations_0"), val = tensor([1])]; + tensor input_85_groups_0 = const()[name = tensor("input_85_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd1_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd1_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(641984)))]; + tensor net_xvector_block1_tdnnd1_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd1_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(658432)))]; + tensor 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("input_85_cast_fp16")]; + tensor input_87_cast_fp16 = relu(x = input_85_cast_fp16)[name = tensor("input_87_cast_fp16")]; + tensor input_89_pad_type_0 = const()[name = tensor("input_89_pad_type_0"), val = tensor("valid")]; + tensor input_89_strides_0 = const()[name = tensor("input_89_strides_0"), val = tensor([1])]; + tensor input_89_pad_0 = const()[name = tensor("input_89_pad_0"), val = tensor([0, 0])]; + tensor input_89_dilations_0 = const()[name = tensor("input_89_dilations_0"), val = tensor([1])]; + tensor input_89_groups_0 = const()[name = tensor("input_89_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd1_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd1_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(658624)))]; + tensor net_xvector_block1_tdnnd1_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd1_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(662784)))]; + tensor 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("input_89_cast_fp16")]; + tensor m_1_cast_fp16 = sigmoid(x = input_89_cast_fp16)[name = tensor("m_1_cast_fp16")]; + tensor var_309_cast_fp16 = mul(x = y_1_cast_fp16, y = m_1_cast_fp16)[name = tensor("op_309_cast_fp16")]; + tensor input_91_interleave_0 = const()[name = tensor("input_91_interleave_0"), val = tensor(false)]; + tensor input_91_cast_fp16 = concat(axis = var_11, interleave = input_91_interleave_0, values = (input_71_cast_fp16, var_309_cast_fp16))[name = tensor("input_91_cast_fp16")]; + tensor net_xvector_block1_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(662912)))]; + tensor net_xvector_block1_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(663296)))]; + tensor net_xvector_block1_tdnnd2_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd2_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(663680)))]; + tensor net_xvector_block1_tdnnd2_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd2_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(664064)))]; + tensor 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("input_93_cast_fp16")]; + tensor input_95_cast_fp16 = relu(x = input_93_cast_fp16)[name = tensor("input_95_cast_fp16")]; + tensor input_97_pad_type_0 = const()[name = tensor("input_97_pad_type_0"), val = tensor("valid")]; + tensor input_97_strides_0 = const()[name = tensor("input_97_strides_0"), val = tensor([1])]; + tensor input_97_pad_0 = const()[name = tensor("input_97_pad_0"), val = tensor([0, 0])]; + tensor input_97_dilations_0 = const()[name = tensor("input_97_dilations_0"), val = tensor([1])]; + tensor input_97_groups_0 = const()[name = tensor("input_97_groups_0"), val = tensor(1)]; + tensor const_240_to_fp16 = const()[name = tensor("const_240_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(664448)))]; + tensor const_241_to_fp16 = const()[name = tensor("const_241_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(705472)))]; + tensor input_99_cast_fp16 = conv(bias = const_241_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_240_to_fp16, x = input_95_cast_fp16)[name = tensor("input_99_cast_fp16")]; + tensor input_101_cast_fp16 = relu(x = input_99_cast_fp16)[name = tensor("input_101_cast_fp16")]; + tensor y_3_pad_type_0 = const()[name = tensor("y_3_pad_type_0"), val = tensor("custom")]; + tensor y_3_pad_0 = const()[name = tensor("y_3_pad_0"), val = tensor([1, 1])]; + tensor y_3_strides_0 = const()[name = tensor("y_3_strides_0"), val = tensor([1])]; + tensor y_3_dilations_0 = const()[name = tensor("y_3_dilations_0"), val = tensor([1])]; + tensor y_3_groups_0 = const()[name = tensor("y_3_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd2_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd2_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(705792)))]; + tensor 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("y_3_cast_fp16")]; + tensor var_346_axes_0 = const()[name = tensor("op_346_axes_0"), val = tensor([-1])]; + tensor var_346_keep_dims_0 = const()[name = tensor("op_346_keep_dims_0"), val = tensor(true)]; + tensor 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("op_346_cast_fp16")]; + tensor var_347 = const()[name = tensor("op_347"), val = tensor([100])]; + tensor var_348 = const()[name = tensor("op_348"), val = tensor([100])]; + tensor seg_5_pad_type_0 = const()[name = tensor("seg_5_pad_type_0"), val = tensor("custom")]; + tensor seg_5_pad_0 = const()[name = tensor("seg_5_pad_0"), val = tensor([0, 0])]; + tensor seg_5_exclude_padding_from_average_0 = const()[name = tensor("seg_5_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_5_ceil_mode_0 = const()[name = tensor("seg_5_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_5_cast_fp16")]; + tensor var_354_axes_0 = const()[name = tensor("op_354_axes_0"), val = tensor([-1])]; + tensor var_354_cast_fp16 = expand_dims(axes = var_354_axes_0, x = seg_5_cast_fp16)[name = tensor("op_354_cast_fp16")]; + tensor var_356_reps_0 = const()[name = tensor("op_356_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_356_cast_fp16 = tile(reps = var_356_reps_0, x = var_354_cast_fp16)[name = tensor("op_356_cast_fp16")]; + tensor var_357 = const()[name = tensor("op_357"), val = tensor([1, 128, -1])]; + tensor seg_7_cast_fp16 = reshape(shape = var_357, x = var_356_cast_fp16)[name = tensor("seg_7_cast_fp16")]; + tensor input_103_cast_fp16 = add(x = var_346_cast_fp16, y = seg_7_cast_fp16)[name = tensor("input_103_cast_fp16")]; + tensor input_105_pad_type_0 = const()[name = tensor("input_105_pad_type_0"), val = tensor("valid")]; + tensor input_105_strides_0 = const()[name = tensor("input_105_strides_0"), val = tensor([1])]; + tensor input_105_pad_0 = const()[name = tensor("input_105_pad_0"), val = tensor([0, 0])]; + tensor input_105_dilations_0 = const()[name = tensor("input_105_dilations_0"), val = tensor([1])]; + tensor input_105_groups_0 = const()[name = tensor("input_105_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd2_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd2_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(730432)))]; + tensor net_xvector_block1_tdnnd2_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd2_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(746880)))]; + tensor 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("input_105_cast_fp16")]; + tensor input_107_cast_fp16 = relu(x = input_105_cast_fp16)[name = tensor("input_107_cast_fp16")]; + tensor input_109_pad_type_0 = const()[name = tensor("input_109_pad_type_0"), val = tensor("valid")]; + tensor input_109_strides_0 = const()[name = tensor("input_109_strides_0"), val = tensor([1])]; + tensor input_109_pad_0 = const()[name = tensor("input_109_pad_0"), val = tensor([0, 0])]; + tensor input_109_dilations_0 = const()[name = tensor("input_109_dilations_0"), val = tensor([1])]; + tensor input_109_groups_0 = const()[name = tensor("input_109_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd2_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd2_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(747072)))]; + tensor net_xvector_block1_tdnnd2_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd2_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(751232)))]; + tensor 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("input_109_cast_fp16")]; + tensor m_3_cast_fp16 = sigmoid(x = input_109_cast_fp16)[name = tensor("m_3_cast_fp16")]; + tensor var_378_cast_fp16 = mul(x = y_3_cast_fp16, y = m_3_cast_fp16)[name = tensor("op_378_cast_fp16")]; + tensor input_111_interleave_0 = const()[name = tensor("input_111_interleave_0"), val = tensor(false)]; + tensor input_111_cast_fp16 = concat(axis = var_11, interleave = input_111_interleave_0, values = (input_91_cast_fp16, var_378_cast_fp16))[name = tensor("input_111_cast_fp16")]; + tensor net_xvector_block1_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(751360)))]; + tensor net_xvector_block1_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(751808)))]; + tensor net_xvector_block1_tdnnd3_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd3_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(752256)))]; + tensor net_xvector_block1_tdnnd3_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd3_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(752704)))]; + tensor 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("input_113_cast_fp16")]; + tensor input_115_cast_fp16 = relu(x = input_113_cast_fp16)[name = tensor("input_115_cast_fp16")]; + tensor input_117_pad_type_0 = const()[name = tensor("input_117_pad_type_0"), val = tensor("valid")]; + tensor input_117_strides_0 = const()[name = tensor("input_117_strides_0"), val = tensor([1])]; + tensor input_117_pad_0 = const()[name = tensor("input_117_pad_0"), val = tensor([0, 0])]; + tensor input_117_dilations_0 = const()[name = tensor("input_117_dilations_0"), val = tensor([1])]; + tensor input_117_groups_0 = const()[name = tensor("input_117_groups_0"), val = tensor(1)]; + tensor const_242_to_fp16 = const()[name = tensor("const_242_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(753152)))]; + tensor const_243_to_fp16 = const()[name = tensor("const_243_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(802368)))]; + tensor input_119_cast_fp16 = conv(bias = const_243_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_242_to_fp16, x = input_115_cast_fp16)[name = tensor("input_119_cast_fp16")]; + tensor input_121_cast_fp16 = relu(x = input_119_cast_fp16)[name = tensor("input_121_cast_fp16")]; + tensor y_5_pad_type_0 = const()[name = tensor("y_5_pad_type_0"), val = tensor("custom")]; + tensor y_5_pad_0 = const()[name = tensor("y_5_pad_0"), val = tensor([1, 1])]; + tensor y_5_strides_0 = const()[name = tensor("y_5_strides_0"), val = tensor([1])]; + tensor y_5_dilations_0 = const()[name = tensor("y_5_dilations_0"), val = tensor([1])]; + tensor y_5_groups_0 = const()[name = tensor("y_5_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd3_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd3_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(802688)))]; + tensor 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("y_5_cast_fp16")]; + tensor var_415_axes_0 = const()[name = tensor("op_415_axes_0"), val = tensor([-1])]; + tensor var_415_keep_dims_0 = const()[name = tensor("op_415_keep_dims_0"), val = tensor(true)]; + tensor 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("op_415_cast_fp16")]; + tensor var_416 = const()[name = tensor("op_416"), val = tensor([100])]; + tensor var_417 = const()[name = tensor("op_417"), val = tensor([100])]; + tensor seg_9_pad_type_0 = const()[name = tensor("seg_9_pad_type_0"), val = tensor("custom")]; + tensor seg_9_pad_0 = const()[name = tensor("seg_9_pad_0"), val = tensor([0, 0])]; + tensor seg_9_exclude_padding_from_average_0 = const()[name = tensor("seg_9_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_9_ceil_mode_0 = const()[name = tensor("seg_9_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_9_cast_fp16")]; + tensor var_423_axes_0 = const()[name = tensor("op_423_axes_0"), val = tensor([-1])]; + tensor var_423_cast_fp16 = expand_dims(axes = var_423_axes_0, x = seg_9_cast_fp16)[name = tensor("op_423_cast_fp16")]; + tensor var_425_reps_0 = const()[name = tensor("op_425_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_425_cast_fp16 = tile(reps = var_425_reps_0, x = var_423_cast_fp16)[name = tensor("op_425_cast_fp16")]; + tensor var_426 = const()[name = tensor("op_426"), val = tensor([1, 128, -1])]; + tensor seg_11_cast_fp16 = reshape(shape = var_426, x = var_425_cast_fp16)[name = tensor("seg_11_cast_fp16")]; + tensor input_123_cast_fp16 = add(x = var_415_cast_fp16, y = seg_11_cast_fp16)[name = tensor("input_123_cast_fp16")]; + tensor input_125_pad_type_0 = const()[name = tensor("input_125_pad_type_0"), val = tensor("valid")]; + tensor input_125_strides_0 = const()[name = tensor("input_125_strides_0"), val = tensor([1])]; + tensor input_125_pad_0 = const()[name = tensor("input_125_pad_0"), val = tensor([0, 0])]; + tensor input_125_dilations_0 = const()[name = tensor("input_125_dilations_0"), val = tensor([1])]; + tensor input_125_groups_0 = const()[name = tensor("input_125_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd3_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd3_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(827328)))]; + tensor net_xvector_block1_tdnnd3_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd3_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(843776)))]; + tensor 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("input_125_cast_fp16")]; + tensor input_127_cast_fp16 = relu(x = input_125_cast_fp16)[name = tensor("input_127_cast_fp16")]; + tensor input_129_pad_type_0 = const()[name = tensor("input_129_pad_type_0"), val = tensor("valid")]; + tensor input_129_strides_0 = const()[name = tensor("input_129_strides_0"), val = tensor([1])]; + tensor input_129_pad_0 = const()[name = tensor("input_129_pad_0"), val = tensor([0, 0])]; + tensor input_129_dilations_0 = const()[name = tensor("input_129_dilations_0"), val = tensor([1])]; + tensor input_129_groups_0 = const()[name = tensor("input_129_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd3_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd3_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(843968)))]; + tensor net_xvector_block1_tdnnd3_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd3_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(848128)))]; + tensor 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("input_129_cast_fp16")]; + tensor m_5_cast_fp16 = sigmoid(x = input_129_cast_fp16)[name = tensor("m_5_cast_fp16")]; + tensor var_447_cast_fp16 = mul(x = y_5_cast_fp16, y = m_5_cast_fp16)[name = tensor("op_447_cast_fp16")]; + tensor input_131_interleave_0 = const()[name = tensor("input_131_interleave_0"), val = tensor(false)]; + tensor input_131_cast_fp16 = concat(axis = var_11, interleave = input_131_interleave_0, values = (input_111_cast_fp16, var_447_cast_fp16))[name = tensor("input_131_cast_fp16")]; + tensor net_xvector_block1_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(848256)))]; + tensor net_xvector_block1_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(848768)))]; + tensor net_xvector_block1_tdnnd4_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd4_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(849280)))]; + tensor net_xvector_block1_tdnnd4_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd4_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(849792)))]; + tensor 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("input_133_cast_fp16")]; + tensor input_135_cast_fp16 = relu(x = input_133_cast_fp16)[name = tensor("input_135_cast_fp16")]; + tensor input_137_pad_type_0 = const()[name = tensor("input_137_pad_type_0"), val = tensor("valid")]; + tensor input_137_strides_0 = const()[name = tensor("input_137_strides_0"), val = tensor([1])]; + tensor input_137_pad_0 = const()[name = tensor("input_137_pad_0"), val = tensor([0, 0])]; + tensor input_137_dilations_0 = const()[name = tensor("input_137_dilations_0"), val = tensor([1])]; + tensor input_137_groups_0 = const()[name = tensor("input_137_groups_0"), val = tensor(1)]; + tensor const_244_to_fp16 = const()[name = tensor("const_244_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(850304)))]; + tensor const_245_to_fp16 = const()[name = tensor("const_245_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(907712)))]; + tensor input_139_cast_fp16 = conv(bias = const_245_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_244_to_fp16, x = input_135_cast_fp16)[name = tensor("input_139_cast_fp16")]; + tensor input_141_cast_fp16 = relu(x = input_139_cast_fp16)[name = tensor("input_141_cast_fp16")]; + tensor y_7_pad_type_0 = const()[name = tensor("y_7_pad_type_0"), val = tensor("custom")]; + tensor y_7_pad_0 = const()[name = tensor("y_7_pad_0"), val = tensor([1, 1])]; + tensor y_7_strides_0 = const()[name = tensor("y_7_strides_0"), val = tensor([1])]; + tensor y_7_dilations_0 = const()[name = tensor("y_7_dilations_0"), val = tensor([1])]; + tensor y_7_groups_0 = const()[name = tensor("y_7_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd4_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd4_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(908032)))]; + tensor 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("y_7_cast_fp16")]; + tensor var_484_axes_0 = const()[name = tensor("op_484_axes_0"), val = tensor([-1])]; + tensor var_484_keep_dims_0 = const()[name = tensor("op_484_keep_dims_0"), val = tensor(true)]; + tensor 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("op_484_cast_fp16")]; + tensor var_485 = const()[name = tensor("op_485"), val = tensor([100])]; + tensor var_486 = const()[name = tensor("op_486"), val = tensor([100])]; + tensor seg_13_pad_type_0 = const()[name = tensor("seg_13_pad_type_0"), val = tensor("custom")]; + tensor seg_13_pad_0 = const()[name = tensor("seg_13_pad_0"), val = tensor([0, 0])]; + tensor seg_13_exclude_padding_from_average_0 = const()[name = tensor("seg_13_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_13_ceil_mode_0 = const()[name = tensor("seg_13_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_13_cast_fp16")]; + tensor var_492_axes_0 = const()[name = tensor("op_492_axes_0"), val = tensor([-1])]; + tensor var_492_cast_fp16 = expand_dims(axes = var_492_axes_0, x = seg_13_cast_fp16)[name = tensor("op_492_cast_fp16")]; + tensor var_494_reps_0 = const()[name = tensor("op_494_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_494_cast_fp16 = tile(reps = var_494_reps_0, x = var_492_cast_fp16)[name = tensor("op_494_cast_fp16")]; + tensor var_495 = const()[name = tensor("op_495"), val = tensor([1, 128, -1])]; + tensor seg_15_cast_fp16 = reshape(shape = var_495, x = var_494_cast_fp16)[name = tensor("seg_15_cast_fp16")]; + tensor input_143_cast_fp16 = add(x = var_484_cast_fp16, y = seg_15_cast_fp16)[name = tensor("input_143_cast_fp16")]; + tensor input_145_pad_type_0 = const()[name = tensor("input_145_pad_type_0"), val = tensor("valid")]; + tensor input_145_strides_0 = const()[name = tensor("input_145_strides_0"), val = tensor([1])]; + tensor input_145_pad_0 = const()[name = tensor("input_145_pad_0"), val = tensor([0, 0])]; + tensor input_145_dilations_0 = const()[name = tensor("input_145_dilations_0"), val = tensor([1])]; + tensor input_145_groups_0 = const()[name = tensor("input_145_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd4_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd4_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(932672)))]; + tensor net_xvector_block1_tdnnd4_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd4_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(949120)))]; + tensor 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("input_145_cast_fp16")]; + tensor input_147_cast_fp16 = relu(x = input_145_cast_fp16)[name = tensor("input_147_cast_fp16")]; + tensor input_149_pad_type_0 = const()[name = tensor("input_149_pad_type_0"), val = tensor("valid")]; + tensor input_149_strides_0 = const()[name = tensor("input_149_strides_0"), val = tensor([1])]; + tensor input_149_pad_0 = const()[name = tensor("input_149_pad_0"), val = tensor([0, 0])]; + tensor input_149_dilations_0 = const()[name = tensor("input_149_dilations_0"), val = tensor([1])]; + tensor input_149_groups_0 = const()[name = tensor("input_149_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd4_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd4_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(949312)))]; + tensor net_xvector_block1_tdnnd4_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd4_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(953472)))]; + tensor 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("input_149_cast_fp16")]; + tensor m_7_cast_fp16 = sigmoid(x = input_149_cast_fp16)[name = tensor("m_7_cast_fp16")]; + tensor var_516_cast_fp16 = mul(x = y_7_cast_fp16, y = m_7_cast_fp16)[name = tensor("op_516_cast_fp16")]; + tensor input_151_interleave_0 = const()[name = tensor("input_151_interleave_0"), val = tensor(false)]; + tensor input_151_cast_fp16 = concat(axis = var_11, interleave = input_151_interleave_0, values = (input_131_cast_fp16, var_516_cast_fp16))[name = tensor("input_151_cast_fp16")]; + tensor net_xvector_block1_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(953600)))]; + tensor net_xvector_block1_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(954176)))]; + tensor net_xvector_block1_tdnnd5_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd5_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(954752)))]; + tensor net_xvector_block1_tdnnd5_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd5_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(955328)))]; + tensor 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("input_153_cast_fp16")]; + tensor input_155_cast_fp16 = relu(x = input_153_cast_fp16)[name = tensor("input_155_cast_fp16")]; + tensor input_157_pad_type_0 = const()[name = tensor("input_157_pad_type_0"), val = tensor("valid")]; + tensor input_157_strides_0 = const()[name = tensor("input_157_strides_0"), val = tensor([1])]; + tensor input_157_pad_0 = const()[name = tensor("input_157_pad_0"), val = tensor([0, 0])]; + tensor input_157_dilations_0 = const()[name = tensor("input_157_dilations_0"), val = tensor([1])]; + tensor input_157_groups_0 = const()[name = tensor("input_157_groups_0"), val = tensor(1)]; + tensor const_246_to_fp16 = const()[name = tensor("const_246_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(955904)))]; + tensor const_247_to_fp16 = const()[name = tensor("const_247_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1021504)))]; + tensor input_159_cast_fp16 = conv(bias = const_247_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_246_to_fp16, x = input_155_cast_fp16)[name = tensor("input_159_cast_fp16")]; + tensor input_161_cast_fp16 = relu(x = input_159_cast_fp16)[name = tensor("input_161_cast_fp16")]; + tensor y_9_pad_type_0 = const()[name = tensor("y_9_pad_type_0"), val = tensor("custom")]; + tensor y_9_pad_0 = const()[name = tensor("y_9_pad_0"), val = tensor([1, 1])]; + tensor y_9_strides_0 = const()[name = tensor("y_9_strides_0"), val = tensor([1])]; + tensor y_9_dilations_0 = const()[name = tensor("y_9_dilations_0"), val = tensor([1])]; + tensor y_9_groups_0 = const()[name = tensor("y_9_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd5_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd5_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1021824)))]; + tensor 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("y_9_cast_fp16")]; + tensor var_553_axes_0 = const()[name = tensor("op_553_axes_0"), val = tensor([-1])]; + tensor var_553_keep_dims_0 = const()[name = tensor("op_553_keep_dims_0"), val = tensor(true)]; + tensor 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("op_553_cast_fp16")]; + tensor var_554 = const()[name = tensor("op_554"), val = tensor([100])]; + tensor var_555 = const()[name = tensor("op_555"), val = tensor([100])]; + tensor seg_17_pad_type_0 = const()[name = tensor("seg_17_pad_type_0"), val = tensor("custom")]; + tensor seg_17_pad_0 = const()[name = tensor("seg_17_pad_0"), val = tensor([0, 0])]; + tensor seg_17_exclude_padding_from_average_0 = const()[name = tensor("seg_17_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_17_ceil_mode_0 = const()[name = tensor("seg_17_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_17_cast_fp16")]; + tensor var_561_axes_0 = const()[name = tensor("op_561_axes_0"), val = tensor([-1])]; + tensor var_561_cast_fp16 = expand_dims(axes = var_561_axes_0, x = seg_17_cast_fp16)[name = tensor("op_561_cast_fp16")]; + tensor var_563_reps_0 = const()[name = tensor("op_563_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_563_cast_fp16 = tile(reps = var_563_reps_0, x = var_561_cast_fp16)[name = tensor("op_563_cast_fp16")]; + tensor var_564 = const()[name = tensor("op_564"), val = tensor([1, 128, -1])]; + tensor seg_19_cast_fp16 = reshape(shape = var_564, x = var_563_cast_fp16)[name = tensor("seg_19_cast_fp16")]; + tensor input_163_cast_fp16 = add(x = var_553_cast_fp16, y = seg_19_cast_fp16)[name = tensor("input_163_cast_fp16")]; + tensor input_165_pad_type_0 = const()[name = tensor("input_165_pad_type_0"), val = tensor("valid")]; + tensor input_165_strides_0 = const()[name = tensor("input_165_strides_0"), val = tensor([1])]; + tensor input_165_pad_0 = const()[name = tensor("input_165_pad_0"), val = tensor([0, 0])]; + tensor input_165_dilations_0 = const()[name = tensor("input_165_dilations_0"), val = tensor([1])]; + tensor input_165_groups_0 = const()[name = tensor("input_165_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd5_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd5_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1046464)))]; + tensor net_xvector_block1_tdnnd5_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd5_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1062912)))]; + tensor 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("input_165_cast_fp16")]; + tensor input_167_cast_fp16 = relu(x = input_165_cast_fp16)[name = tensor("input_167_cast_fp16")]; + tensor input_169_pad_type_0 = const()[name = tensor("input_169_pad_type_0"), val = tensor("valid")]; + tensor input_169_strides_0 = const()[name = tensor("input_169_strides_0"), val = tensor([1])]; + tensor input_169_pad_0 = const()[name = tensor("input_169_pad_0"), val = tensor([0, 0])]; + tensor input_169_dilations_0 = const()[name = tensor("input_169_dilations_0"), val = tensor([1])]; + tensor input_169_groups_0 = const()[name = tensor("input_169_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd5_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd5_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1063104)))]; + tensor net_xvector_block1_tdnnd5_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd5_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1067264)))]; + tensor 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("input_169_cast_fp16")]; + tensor m_9_cast_fp16 = sigmoid(x = input_169_cast_fp16)[name = tensor("m_9_cast_fp16")]; + tensor var_585_cast_fp16 = mul(x = y_9_cast_fp16, y = m_9_cast_fp16)[name = tensor("op_585_cast_fp16")]; + tensor input_171_interleave_0 = const()[name = tensor("input_171_interleave_0"), val = tensor(false)]; + tensor input_171_cast_fp16 = concat(axis = var_11, interleave = input_171_interleave_0, values = (input_151_cast_fp16, var_585_cast_fp16))[name = tensor("input_171_cast_fp16")]; + tensor net_xvector_block1_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1067392)))]; + tensor net_xvector_block1_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1068032)))]; + tensor net_xvector_block1_tdnnd6_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd6_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1068672)))]; + tensor net_xvector_block1_tdnnd6_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd6_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1069312)))]; + tensor 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("input_173_cast_fp16")]; + tensor input_175_cast_fp16 = relu(x = input_173_cast_fp16)[name = tensor("input_175_cast_fp16")]; + tensor input_177_pad_type_0 = const()[name = tensor("input_177_pad_type_0"), val = tensor("valid")]; + tensor input_177_strides_0 = const()[name = tensor("input_177_strides_0"), val = tensor([1])]; + tensor input_177_pad_0 = const()[name = tensor("input_177_pad_0"), val = tensor([0, 0])]; + tensor input_177_dilations_0 = const()[name = tensor("input_177_dilations_0"), val = tensor([1])]; + tensor input_177_groups_0 = const()[name = tensor("input_177_groups_0"), val = tensor(1)]; + tensor const_248_to_fp16 = const()[name = tensor("const_248_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1069952)))]; + tensor const_249_to_fp16 = const()[name = tensor("const_249_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1143744)))]; + tensor input_179_cast_fp16 = conv(bias = const_249_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_248_to_fp16, x = input_175_cast_fp16)[name = tensor("input_179_cast_fp16")]; + tensor input_181_cast_fp16 = relu(x = input_179_cast_fp16)[name = tensor("input_181_cast_fp16")]; + tensor y_11_pad_type_0 = const()[name = tensor("y_11_pad_type_0"), val = tensor("custom")]; + tensor y_11_pad_0 = const()[name = tensor("y_11_pad_0"), val = tensor([1, 1])]; + tensor y_11_strides_0 = const()[name = tensor("y_11_strides_0"), val = tensor([1])]; + tensor y_11_dilations_0 = const()[name = tensor("y_11_dilations_0"), val = tensor([1])]; + tensor y_11_groups_0 = const()[name = tensor("y_11_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd6_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd6_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1144064)))]; + tensor 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("y_11_cast_fp16")]; + tensor var_622_axes_0 = const()[name = tensor("op_622_axes_0"), val = tensor([-1])]; + tensor var_622_keep_dims_0 = const()[name = tensor("op_622_keep_dims_0"), val = tensor(true)]; + tensor 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("op_622_cast_fp16")]; + tensor var_623 = const()[name = tensor("op_623"), val = tensor([100])]; + tensor var_624 = const()[name = tensor("op_624"), val = tensor([100])]; + tensor seg_21_pad_type_0 = const()[name = tensor("seg_21_pad_type_0"), val = tensor("custom")]; + tensor seg_21_pad_0 = const()[name = tensor("seg_21_pad_0"), val = tensor([0, 0])]; + tensor seg_21_exclude_padding_from_average_0 = const()[name = tensor("seg_21_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_21_ceil_mode_0 = const()[name = tensor("seg_21_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_21_cast_fp16")]; + tensor var_630_axes_0 = const()[name = tensor("op_630_axes_0"), val = tensor([-1])]; + tensor var_630_cast_fp16 = expand_dims(axes = var_630_axes_0, x = seg_21_cast_fp16)[name = tensor("op_630_cast_fp16")]; + tensor var_632_reps_0 = const()[name = tensor("op_632_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_632_cast_fp16 = tile(reps = var_632_reps_0, x = var_630_cast_fp16)[name = tensor("op_632_cast_fp16")]; + tensor var_633 = const()[name = tensor("op_633"), val = tensor([1, 128, -1])]; + tensor seg_23_cast_fp16 = reshape(shape = var_633, x = var_632_cast_fp16)[name = tensor("seg_23_cast_fp16")]; + tensor input_183_cast_fp16 = add(x = var_622_cast_fp16, y = seg_23_cast_fp16)[name = tensor("input_183_cast_fp16")]; + tensor input_185_pad_type_0 = const()[name = tensor("input_185_pad_type_0"), val = tensor("valid")]; + tensor input_185_strides_0 = const()[name = tensor("input_185_strides_0"), val = tensor([1])]; + tensor input_185_pad_0 = const()[name = tensor("input_185_pad_0"), val = tensor([0, 0])]; + tensor input_185_dilations_0 = const()[name = tensor("input_185_dilations_0"), val = tensor([1])]; + tensor input_185_groups_0 = const()[name = tensor("input_185_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd6_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd6_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1168704)))]; + tensor net_xvector_block1_tdnnd6_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd6_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1185152)))]; + tensor 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("input_185_cast_fp16")]; + tensor input_187_cast_fp16 = relu(x = input_185_cast_fp16)[name = tensor("input_187_cast_fp16")]; + tensor input_189_pad_type_0 = const()[name = tensor("input_189_pad_type_0"), val = tensor("valid")]; + tensor input_189_strides_0 = const()[name = tensor("input_189_strides_0"), val = tensor([1])]; + tensor input_189_pad_0 = const()[name = tensor("input_189_pad_0"), val = tensor([0, 0])]; + tensor input_189_dilations_0 = const()[name = tensor("input_189_dilations_0"), val = tensor([1])]; + tensor input_189_groups_0 = const()[name = tensor("input_189_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd6_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd6_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1185344)))]; + tensor net_xvector_block1_tdnnd6_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd6_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1189504)))]; + tensor 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("input_189_cast_fp16")]; + tensor m_11_cast_fp16 = sigmoid(x = input_189_cast_fp16)[name = tensor("m_11_cast_fp16")]; + tensor var_654_cast_fp16 = mul(x = y_11_cast_fp16, y = m_11_cast_fp16)[name = tensor("op_654_cast_fp16")]; + tensor input_191_interleave_0 = const()[name = tensor("input_191_interleave_0"), val = tensor(false)]; + tensor input_191_cast_fp16 = concat(axis = var_11, interleave = input_191_interleave_0, values = (input_171_cast_fp16, var_654_cast_fp16))[name = tensor("input_191_cast_fp16")]; + tensor net_xvector_block1_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1189632)))]; + tensor net_xvector_block1_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1190336)))]; + tensor net_xvector_block1_tdnnd7_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd7_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1191040)))]; + tensor net_xvector_block1_tdnnd7_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd7_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1191744)))]; + tensor 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("input_193_cast_fp16")]; + tensor input_195_cast_fp16 = relu(x = input_193_cast_fp16)[name = tensor("input_195_cast_fp16")]; + tensor input_197_pad_type_0 = const()[name = tensor("input_197_pad_type_0"), val = tensor("valid")]; + tensor input_197_strides_0 = const()[name = tensor("input_197_strides_0"), val = tensor([1])]; + tensor input_197_pad_0 = const()[name = tensor("input_197_pad_0"), val = tensor([0, 0])]; + tensor input_197_dilations_0 = const()[name = tensor("input_197_dilations_0"), val = tensor([1])]; + tensor input_197_groups_0 = const()[name = tensor("input_197_groups_0"), val = tensor(1)]; + tensor const_250_to_fp16 = const()[name = tensor("const_250_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1192448)))]; + tensor const_251_to_fp16 = const()[name = tensor("const_251_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1274432)))]; + tensor input_199_cast_fp16 = conv(bias = const_251_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_250_to_fp16, x = input_195_cast_fp16)[name = tensor("input_199_cast_fp16")]; + tensor input_201_cast_fp16 = relu(x = input_199_cast_fp16)[name = tensor("input_201_cast_fp16")]; + tensor y_13_pad_type_0 = const()[name = tensor("y_13_pad_type_0"), val = tensor("custom")]; + tensor y_13_pad_0 = const()[name = tensor("y_13_pad_0"), val = tensor([1, 1])]; + tensor y_13_strides_0 = const()[name = tensor("y_13_strides_0"), val = tensor([1])]; + tensor y_13_dilations_0 = const()[name = tensor("y_13_dilations_0"), val = tensor([1])]; + tensor y_13_groups_0 = const()[name = tensor("y_13_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd7_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd7_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1274752)))]; + tensor 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("y_13_cast_fp16")]; + tensor var_691_axes_0 = const()[name = tensor("op_691_axes_0"), val = tensor([-1])]; + tensor var_691_keep_dims_0 = const()[name = tensor("op_691_keep_dims_0"), val = tensor(true)]; + tensor 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("op_691_cast_fp16")]; + tensor var_692 = const()[name = tensor("op_692"), val = tensor([100])]; + tensor var_693 = const()[name = tensor("op_693"), val = tensor([100])]; + tensor seg_25_pad_type_0 = const()[name = tensor("seg_25_pad_type_0"), val = tensor("custom")]; + tensor seg_25_pad_0 = const()[name = tensor("seg_25_pad_0"), val = tensor([0, 0])]; + tensor seg_25_exclude_padding_from_average_0 = const()[name = tensor("seg_25_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_25_ceil_mode_0 = const()[name = tensor("seg_25_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_25_cast_fp16")]; + tensor var_699_axes_0 = const()[name = tensor("op_699_axes_0"), val = tensor([-1])]; + tensor var_699_cast_fp16 = expand_dims(axes = var_699_axes_0, x = seg_25_cast_fp16)[name = tensor("op_699_cast_fp16")]; + tensor var_701_reps_0 = const()[name = tensor("op_701_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_701_cast_fp16 = tile(reps = var_701_reps_0, x = var_699_cast_fp16)[name = tensor("op_701_cast_fp16")]; + tensor var_702 = const()[name = tensor("op_702"), val = tensor([1, 128, -1])]; + tensor seg_27_cast_fp16 = reshape(shape = var_702, x = var_701_cast_fp16)[name = tensor("seg_27_cast_fp16")]; + tensor input_203_cast_fp16 = add(x = var_691_cast_fp16, y = seg_27_cast_fp16)[name = tensor("input_203_cast_fp16")]; + tensor input_205_pad_type_0 = const()[name = tensor("input_205_pad_type_0"), val = tensor("valid")]; + tensor input_205_strides_0 = const()[name = tensor("input_205_strides_0"), val = tensor([1])]; + tensor input_205_pad_0 = const()[name = tensor("input_205_pad_0"), val = tensor([0, 0])]; + tensor input_205_dilations_0 = const()[name = tensor("input_205_dilations_0"), val = tensor([1])]; + tensor input_205_groups_0 = const()[name = tensor("input_205_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd7_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd7_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1299392)))]; + tensor net_xvector_block1_tdnnd7_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd7_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1315840)))]; + tensor 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("input_205_cast_fp16")]; + tensor input_207_cast_fp16 = relu(x = input_205_cast_fp16)[name = tensor("input_207_cast_fp16")]; + tensor input_209_pad_type_0 = const()[name = tensor("input_209_pad_type_0"), val = tensor("valid")]; + tensor input_209_strides_0 = const()[name = tensor("input_209_strides_0"), val = tensor([1])]; + tensor input_209_pad_0 = const()[name = tensor("input_209_pad_0"), val = tensor([0, 0])]; + tensor input_209_dilations_0 = const()[name = tensor("input_209_dilations_0"), val = tensor([1])]; + tensor input_209_groups_0 = const()[name = tensor("input_209_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd7_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd7_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1316032)))]; + tensor net_xvector_block1_tdnnd7_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd7_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1320192)))]; + tensor 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("input_209_cast_fp16")]; + tensor m_13_cast_fp16 = sigmoid(x = input_209_cast_fp16)[name = tensor("m_13_cast_fp16")]; + tensor var_723_cast_fp16 = mul(x = y_13_cast_fp16, y = m_13_cast_fp16)[name = tensor("op_723_cast_fp16")]; + tensor input_211_interleave_0 = const()[name = tensor("input_211_interleave_0"), val = tensor(false)]; + tensor input_211_cast_fp16 = concat(axis = var_11, interleave = input_211_interleave_0, values = (input_191_cast_fp16, var_723_cast_fp16))[name = tensor("input_211_cast_fp16")]; + tensor net_xvector_block1_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1320320)))]; + tensor net_xvector_block1_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1321088)))]; + tensor net_xvector_block1_tdnnd8_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd8_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1321856)))]; + tensor net_xvector_block1_tdnnd8_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd8_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1322624)))]; + tensor 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("input_213_cast_fp16")]; + tensor input_215_cast_fp16 = relu(x = input_213_cast_fp16)[name = tensor("input_215_cast_fp16")]; + tensor input_217_pad_type_0 = const()[name = tensor("input_217_pad_type_0"), val = tensor("valid")]; + tensor input_217_strides_0 = const()[name = tensor("input_217_strides_0"), val = tensor([1])]; + tensor input_217_pad_0 = const()[name = tensor("input_217_pad_0"), val = tensor([0, 0])]; + tensor input_217_dilations_0 = const()[name = tensor("input_217_dilations_0"), val = tensor([1])]; + tensor input_217_groups_0 = const()[name = tensor("input_217_groups_0"), val = tensor(1)]; + tensor const_252_to_fp16 = const()[name = tensor("const_252_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1323392)))]; + tensor const_253_to_fp16 = const()[name = tensor("const_253_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1413568)))]; + tensor input_219_cast_fp16 = conv(bias = const_253_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_252_to_fp16, x = input_215_cast_fp16)[name = tensor("input_219_cast_fp16")]; + tensor input_221_cast_fp16 = relu(x = input_219_cast_fp16)[name = tensor("input_221_cast_fp16")]; + tensor y_15_pad_type_0 = const()[name = tensor("y_15_pad_type_0"), val = tensor("custom")]; + tensor y_15_pad_0 = const()[name = tensor("y_15_pad_0"), val = tensor([1, 1])]; + tensor y_15_strides_0 = const()[name = tensor("y_15_strides_0"), val = tensor([1])]; + tensor y_15_dilations_0 = const()[name = tensor("y_15_dilations_0"), val = tensor([1])]; + tensor y_15_groups_0 = const()[name = tensor("y_15_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd8_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd8_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1413888)))]; + tensor 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("y_15_cast_fp16")]; + tensor var_760_axes_0 = const()[name = tensor("op_760_axes_0"), val = tensor([-1])]; + tensor var_760_keep_dims_0 = const()[name = tensor("op_760_keep_dims_0"), val = tensor(true)]; + tensor 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("op_760_cast_fp16")]; + tensor var_761 = const()[name = tensor("op_761"), val = tensor([100])]; + tensor var_762 = const()[name = tensor("op_762"), val = tensor([100])]; + tensor seg_29_pad_type_0 = const()[name = tensor("seg_29_pad_type_0"), val = tensor("custom")]; + tensor seg_29_pad_0 = const()[name = tensor("seg_29_pad_0"), val = tensor([0, 0])]; + tensor seg_29_exclude_padding_from_average_0 = const()[name = tensor("seg_29_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_29_ceil_mode_0 = const()[name = tensor("seg_29_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_29_cast_fp16")]; + tensor var_768_axes_0 = const()[name = tensor("op_768_axes_0"), val = tensor([-1])]; + tensor var_768_cast_fp16 = expand_dims(axes = var_768_axes_0, x = seg_29_cast_fp16)[name = tensor("op_768_cast_fp16")]; + tensor var_770_reps_0 = const()[name = tensor("op_770_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_770_cast_fp16 = tile(reps = var_770_reps_0, x = var_768_cast_fp16)[name = tensor("op_770_cast_fp16")]; + tensor var_771 = const()[name = tensor("op_771"), val = tensor([1, 128, -1])]; + tensor seg_31_cast_fp16 = reshape(shape = var_771, x = var_770_cast_fp16)[name = tensor("seg_31_cast_fp16")]; + tensor input_223_cast_fp16 = add(x = var_760_cast_fp16, y = seg_31_cast_fp16)[name = tensor("input_223_cast_fp16")]; + tensor input_225_pad_type_0 = const()[name = tensor("input_225_pad_type_0"), val = tensor("valid")]; + tensor input_225_strides_0 = const()[name = tensor("input_225_strides_0"), val = tensor([1])]; + tensor input_225_pad_0 = const()[name = tensor("input_225_pad_0"), val = tensor([0, 0])]; + tensor input_225_dilations_0 = const()[name = tensor("input_225_dilations_0"), val = tensor([1])]; + tensor input_225_groups_0 = const()[name = tensor("input_225_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd8_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd8_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1438528)))]; + tensor net_xvector_block1_tdnnd8_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd8_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1454976)))]; + tensor 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("input_225_cast_fp16")]; + tensor input_227_cast_fp16 = relu(x = input_225_cast_fp16)[name = tensor("input_227_cast_fp16")]; + tensor input_229_pad_type_0 = const()[name = tensor("input_229_pad_type_0"), val = tensor("valid")]; + tensor input_229_strides_0 = const()[name = tensor("input_229_strides_0"), val = tensor([1])]; + tensor input_229_pad_0 = const()[name = tensor("input_229_pad_0"), val = tensor([0, 0])]; + tensor input_229_dilations_0 = const()[name = tensor("input_229_dilations_0"), val = tensor([1])]; + tensor input_229_groups_0 = const()[name = tensor("input_229_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd8_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd8_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1455168)))]; + tensor net_xvector_block1_tdnnd8_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd8_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1459328)))]; + tensor 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("input_229_cast_fp16")]; + tensor m_15_cast_fp16 = sigmoid(x = input_229_cast_fp16)[name = tensor("m_15_cast_fp16")]; + tensor var_792_cast_fp16 = mul(x = y_15_cast_fp16, y = m_15_cast_fp16)[name = tensor("op_792_cast_fp16")]; + tensor input_231_interleave_0 = const()[name = tensor("input_231_interleave_0"), val = tensor(false)]; + tensor input_231_cast_fp16 = concat(axis = var_11, interleave = input_231_interleave_0, values = (input_211_cast_fp16, var_792_cast_fp16))[name = tensor("input_231_cast_fp16")]; + tensor net_xvector_block1_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1459456)))]; + tensor net_xvector_block1_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1460288)))]; + tensor net_xvector_block1_tdnnd9_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd9_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1461120)))]; + tensor net_xvector_block1_tdnnd9_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd9_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1461952)))]; + tensor 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("input_233_cast_fp16")]; + tensor input_235_cast_fp16 = relu(x = input_233_cast_fp16)[name = tensor("input_235_cast_fp16")]; + tensor input_237_pad_type_0 = const()[name = tensor("input_237_pad_type_0"), val = tensor("valid")]; + tensor input_237_strides_0 = const()[name = tensor("input_237_strides_0"), val = tensor([1])]; + tensor input_237_pad_0 = const()[name = tensor("input_237_pad_0"), val = tensor([0, 0])]; + tensor input_237_dilations_0 = const()[name = tensor("input_237_dilations_0"), val = tensor([1])]; + tensor input_237_groups_0 = const()[name = tensor("input_237_groups_0"), val = tensor(1)]; + tensor const_254_to_fp16 = const()[name = tensor("const_254_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1462784)))]; + tensor const_255_to_fp16 = const()[name = tensor("const_255_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1561152)))]; + tensor input_239_cast_fp16 = conv(bias = const_255_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_254_to_fp16, x = input_235_cast_fp16)[name = tensor("input_239_cast_fp16")]; + tensor input_241_cast_fp16 = relu(x = input_239_cast_fp16)[name = tensor("input_241_cast_fp16")]; + tensor y_17_pad_type_0 = const()[name = tensor("y_17_pad_type_0"), val = tensor("custom")]; + tensor y_17_pad_0 = const()[name = tensor("y_17_pad_0"), val = tensor([1, 1])]; + tensor y_17_strides_0 = const()[name = tensor("y_17_strides_0"), val = tensor([1])]; + tensor y_17_dilations_0 = const()[name = tensor("y_17_dilations_0"), val = tensor([1])]; + tensor y_17_groups_0 = const()[name = tensor("y_17_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd9_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd9_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1561472)))]; + tensor 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("y_17_cast_fp16")]; + tensor var_829_axes_0 = const()[name = tensor("op_829_axes_0"), val = tensor([-1])]; + tensor var_829_keep_dims_0 = const()[name = tensor("op_829_keep_dims_0"), val = tensor(true)]; + tensor 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("op_829_cast_fp16")]; + tensor var_830 = const()[name = tensor("op_830"), val = tensor([100])]; + tensor var_831 = const()[name = tensor("op_831"), val = tensor([100])]; + tensor seg_33_pad_type_0 = const()[name = tensor("seg_33_pad_type_0"), val = tensor("custom")]; + tensor seg_33_pad_0 = const()[name = tensor("seg_33_pad_0"), val = tensor([0, 0])]; + tensor seg_33_exclude_padding_from_average_0 = const()[name = tensor("seg_33_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_33_ceil_mode_0 = const()[name = tensor("seg_33_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_33_cast_fp16")]; + tensor var_837_axes_0 = const()[name = tensor("op_837_axes_0"), val = tensor([-1])]; + tensor var_837_cast_fp16 = expand_dims(axes = var_837_axes_0, x = seg_33_cast_fp16)[name = tensor("op_837_cast_fp16")]; + tensor var_839_reps_0 = const()[name = tensor("op_839_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_839_cast_fp16 = tile(reps = var_839_reps_0, x = var_837_cast_fp16)[name = tensor("op_839_cast_fp16")]; + tensor var_840 = const()[name = tensor("op_840"), val = tensor([1, 128, -1])]; + tensor seg_35_cast_fp16 = reshape(shape = var_840, x = var_839_cast_fp16)[name = tensor("seg_35_cast_fp16")]; + tensor input_243_cast_fp16 = add(x = var_829_cast_fp16, y = seg_35_cast_fp16)[name = tensor("input_243_cast_fp16")]; + tensor input_245_pad_type_0 = const()[name = tensor("input_245_pad_type_0"), val = tensor("valid")]; + tensor input_245_strides_0 = const()[name = tensor("input_245_strides_0"), val = tensor([1])]; + tensor input_245_pad_0 = const()[name = tensor("input_245_pad_0"), val = tensor([0, 0])]; + tensor input_245_dilations_0 = const()[name = tensor("input_245_dilations_0"), val = tensor([1])]; + tensor input_245_groups_0 = const()[name = tensor("input_245_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd9_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd9_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1586112)))]; + tensor net_xvector_block1_tdnnd9_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd9_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1602560)))]; + tensor 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("input_245_cast_fp16")]; + tensor input_247_cast_fp16 = relu(x = input_245_cast_fp16)[name = tensor("input_247_cast_fp16")]; + tensor input_249_pad_type_0 = const()[name = tensor("input_249_pad_type_0"), val = tensor("valid")]; + tensor input_249_strides_0 = const()[name = tensor("input_249_strides_0"), val = tensor([1])]; + tensor input_249_pad_0 = const()[name = tensor("input_249_pad_0"), val = tensor([0, 0])]; + tensor input_249_dilations_0 = const()[name = tensor("input_249_dilations_0"), val = tensor([1])]; + tensor input_249_groups_0 = const()[name = tensor("input_249_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd9_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd9_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1602752)))]; + tensor net_xvector_block1_tdnnd9_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd9_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1606912)))]; + tensor 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("input_249_cast_fp16")]; + tensor m_17_cast_fp16 = sigmoid(x = input_249_cast_fp16)[name = tensor("m_17_cast_fp16")]; + tensor var_861_cast_fp16 = mul(x = y_17_cast_fp16, y = m_17_cast_fp16)[name = tensor("op_861_cast_fp16")]; + tensor input_251_interleave_0 = const()[name = tensor("input_251_interleave_0"), val = tensor(false)]; + tensor input_251_cast_fp16 = concat(axis = var_11, interleave = input_251_interleave_0, values = (input_231_cast_fp16, var_861_cast_fp16))[name = tensor("input_251_cast_fp16")]; + tensor net_xvector_block1_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1607040)))]; + tensor net_xvector_block1_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1607936)))]; + tensor net_xvector_block1_tdnnd10_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd10_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1608832)))]; + tensor net_xvector_block1_tdnnd10_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd10_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1609728)))]; + tensor 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("input_253_cast_fp16")]; + tensor input_255_cast_fp16 = relu(x = input_253_cast_fp16)[name = tensor("input_255_cast_fp16")]; + tensor input_257_pad_type_0 = const()[name = tensor("input_257_pad_type_0"), val = tensor("valid")]; + tensor input_257_strides_0 = const()[name = tensor("input_257_strides_0"), val = tensor([1])]; + tensor input_257_pad_0 = const()[name = tensor("input_257_pad_0"), val = tensor([0, 0])]; + tensor input_257_dilations_0 = const()[name = tensor("input_257_dilations_0"), val = tensor([1])]; + tensor input_257_groups_0 = const()[name = tensor("input_257_groups_0"), val = tensor(1)]; + tensor const_256_to_fp16 = const()[name = tensor("const_256_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1610624)))]; + tensor const_257_to_fp16 = const()[name = tensor("const_257_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1717184)))]; + tensor input_259_cast_fp16 = conv(bias = const_257_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_256_to_fp16, x = input_255_cast_fp16)[name = tensor("input_259_cast_fp16")]; + tensor input_261_cast_fp16 = relu(x = input_259_cast_fp16)[name = tensor("input_261_cast_fp16")]; + tensor y_19_pad_type_0 = const()[name = tensor("y_19_pad_type_0"), val = tensor("custom")]; + tensor y_19_pad_0 = const()[name = tensor("y_19_pad_0"), val = tensor([1, 1])]; + tensor y_19_strides_0 = const()[name = tensor("y_19_strides_0"), val = tensor([1])]; + tensor y_19_dilations_0 = const()[name = tensor("y_19_dilations_0"), val = tensor([1])]; + tensor y_19_groups_0 = const()[name = tensor("y_19_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd10_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd10_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1717504)))]; + tensor 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("y_19_cast_fp16")]; + tensor var_898_axes_0 = const()[name = tensor("op_898_axes_0"), val = tensor([-1])]; + tensor var_898_keep_dims_0 = const()[name = tensor("op_898_keep_dims_0"), val = tensor(true)]; + tensor 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("op_898_cast_fp16")]; + tensor var_899 = const()[name = tensor("op_899"), val = tensor([100])]; + tensor var_900 = const()[name = tensor("op_900"), val = tensor([100])]; + tensor seg_37_pad_type_0 = const()[name = tensor("seg_37_pad_type_0"), val = tensor("custom")]; + tensor seg_37_pad_0 = const()[name = tensor("seg_37_pad_0"), val = tensor([0, 0])]; + tensor seg_37_exclude_padding_from_average_0 = const()[name = tensor("seg_37_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_37_ceil_mode_0 = const()[name = tensor("seg_37_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_37_cast_fp16")]; + tensor var_906_axes_0 = const()[name = tensor("op_906_axes_0"), val = tensor([-1])]; + tensor var_906_cast_fp16 = expand_dims(axes = var_906_axes_0, x = seg_37_cast_fp16)[name = tensor("op_906_cast_fp16")]; + tensor var_908_reps_0 = const()[name = tensor("op_908_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_908_cast_fp16 = tile(reps = var_908_reps_0, x = var_906_cast_fp16)[name = tensor("op_908_cast_fp16")]; + tensor var_909 = const()[name = tensor("op_909"), val = tensor([1, 128, -1])]; + tensor seg_39_cast_fp16 = reshape(shape = var_909, x = var_908_cast_fp16)[name = tensor("seg_39_cast_fp16")]; + tensor input_263_cast_fp16 = add(x = var_898_cast_fp16, y = seg_39_cast_fp16)[name = tensor("input_263_cast_fp16")]; + tensor input_265_pad_type_0 = const()[name = tensor("input_265_pad_type_0"), val = tensor("valid")]; + tensor input_265_strides_0 = const()[name = tensor("input_265_strides_0"), val = tensor([1])]; + tensor input_265_pad_0 = const()[name = tensor("input_265_pad_0"), val = tensor([0, 0])]; + tensor input_265_dilations_0 = const()[name = tensor("input_265_dilations_0"), val = tensor([1])]; + tensor input_265_groups_0 = const()[name = tensor("input_265_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd10_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd10_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1742144)))]; + tensor net_xvector_block1_tdnnd10_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd10_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1758592)))]; + tensor 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("input_265_cast_fp16")]; + tensor input_267_cast_fp16 = relu(x = input_265_cast_fp16)[name = tensor("input_267_cast_fp16")]; + tensor input_269_pad_type_0 = const()[name = tensor("input_269_pad_type_0"), val = tensor("valid")]; + tensor input_269_strides_0 = const()[name = tensor("input_269_strides_0"), val = tensor([1])]; + tensor input_269_pad_0 = const()[name = tensor("input_269_pad_0"), val = tensor([0, 0])]; + tensor input_269_dilations_0 = const()[name = tensor("input_269_dilations_0"), val = tensor([1])]; + tensor input_269_groups_0 = const()[name = tensor("input_269_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd10_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd10_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1758784)))]; + tensor net_xvector_block1_tdnnd10_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd10_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1762944)))]; + tensor 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("input_269_cast_fp16")]; + tensor m_19_cast_fp16 = sigmoid(x = input_269_cast_fp16)[name = tensor("m_19_cast_fp16")]; + tensor var_930_cast_fp16 = mul(x = y_19_cast_fp16, y = m_19_cast_fp16)[name = tensor("op_930_cast_fp16")]; + tensor input_271_interleave_0 = const()[name = tensor("input_271_interleave_0"), val = tensor(false)]; + tensor input_271_cast_fp16 = concat(axis = var_11, interleave = input_271_interleave_0, values = (input_251_cast_fp16, var_930_cast_fp16))[name = tensor("input_271_cast_fp16")]; + tensor net_xvector_block1_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1763072)))]; + tensor net_xvector_block1_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1764032)))]; + tensor net_xvector_block1_tdnnd11_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd11_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1764992)))]; + tensor net_xvector_block1_tdnnd11_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd11_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1765952)))]; + tensor 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("input_273_cast_fp16")]; + tensor input_275_cast_fp16 = relu(x = input_273_cast_fp16)[name = tensor("input_275_cast_fp16")]; + tensor input_277_pad_type_0 = const()[name = tensor("input_277_pad_type_0"), val = tensor("valid")]; + tensor input_277_strides_0 = const()[name = tensor("input_277_strides_0"), val = tensor([1])]; + tensor input_277_pad_0 = const()[name = tensor("input_277_pad_0"), val = tensor([0, 0])]; + tensor input_277_dilations_0 = const()[name = tensor("input_277_dilations_0"), val = tensor([1])]; + tensor input_277_groups_0 = const()[name = tensor("input_277_groups_0"), val = tensor(1)]; + tensor const_258_to_fp16 = const()[name = tensor("const_258_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1766912)))]; + tensor const_259_to_fp16 = const()[name = tensor("const_259_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1881664)))]; + tensor input_279_cast_fp16 = conv(bias = const_259_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_258_to_fp16, x = input_275_cast_fp16)[name = tensor("input_279_cast_fp16")]; + tensor input_281_cast_fp16 = relu(x = input_279_cast_fp16)[name = tensor("input_281_cast_fp16")]; + tensor y_21_pad_type_0 = const()[name = tensor("y_21_pad_type_0"), val = tensor("custom")]; + tensor y_21_pad_0 = const()[name = tensor("y_21_pad_0"), val = tensor([1, 1])]; + tensor y_21_strides_0 = const()[name = tensor("y_21_strides_0"), val = tensor([1])]; + tensor y_21_dilations_0 = const()[name = tensor("y_21_dilations_0"), val = tensor([1])]; + tensor y_21_groups_0 = const()[name = tensor("y_21_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd11_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd11_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1881984)))]; + tensor 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("y_21_cast_fp16")]; + tensor var_967_axes_0 = const()[name = tensor("op_967_axes_0"), val = tensor([-1])]; + tensor var_967_keep_dims_0 = const()[name = tensor("op_967_keep_dims_0"), val = tensor(true)]; + tensor 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("op_967_cast_fp16")]; + tensor var_968 = const()[name = tensor("op_968"), val = tensor([100])]; + tensor var_969 = const()[name = tensor("op_969"), val = tensor([100])]; + tensor seg_41_pad_type_0 = const()[name = tensor("seg_41_pad_type_0"), val = tensor("custom")]; + tensor seg_41_pad_0 = const()[name = tensor("seg_41_pad_0"), val = tensor([0, 0])]; + tensor seg_41_exclude_padding_from_average_0 = const()[name = tensor("seg_41_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_41_ceil_mode_0 = const()[name = tensor("seg_41_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_41_cast_fp16")]; + tensor var_975_axes_0 = const()[name = tensor("op_975_axes_0"), val = tensor([-1])]; + tensor var_975_cast_fp16 = expand_dims(axes = var_975_axes_0, x = seg_41_cast_fp16)[name = tensor("op_975_cast_fp16")]; + tensor var_977_reps_0 = const()[name = tensor("op_977_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_977_cast_fp16 = tile(reps = var_977_reps_0, x = var_975_cast_fp16)[name = tensor("op_977_cast_fp16")]; + tensor var_978 = const()[name = tensor("op_978"), val = tensor([1, 128, -1])]; + tensor seg_43_cast_fp16 = reshape(shape = var_978, x = var_977_cast_fp16)[name = tensor("seg_43_cast_fp16")]; + tensor input_283_cast_fp16 = add(x = var_967_cast_fp16, y = seg_43_cast_fp16)[name = tensor("input_283_cast_fp16")]; + tensor input_285_pad_type_0 = const()[name = tensor("input_285_pad_type_0"), val = tensor("valid")]; + tensor input_285_strides_0 = const()[name = tensor("input_285_strides_0"), val = tensor([1])]; + tensor input_285_pad_0 = const()[name = tensor("input_285_pad_0"), val = tensor([0, 0])]; + tensor input_285_dilations_0 = const()[name = tensor("input_285_dilations_0"), val = tensor([1])]; + tensor input_285_groups_0 = const()[name = tensor("input_285_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd11_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd11_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1906624)))]; + tensor net_xvector_block1_tdnnd11_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd11_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1923072)))]; + tensor 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("input_285_cast_fp16")]; + tensor input_287_cast_fp16 = relu(x = input_285_cast_fp16)[name = tensor("input_287_cast_fp16")]; + tensor input_289_pad_type_0 = const()[name = tensor("input_289_pad_type_0"), val = tensor("valid")]; + tensor input_289_strides_0 = const()[name = tensor("input_289_strides_0"), val = tensor([1])]; + tensor input_289_pad_0 = const()[name = tensor("input_289_pad_0"), val = tensor([0, 0])]; + tensor input_289_dilations_0 = const()[name = tensor("input_289_dilations_0"), val = tensor([1])]; + tensor input_289_groups_0 = const()[name = tensor("input_289_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd11_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd11_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1923264)))]; + tensor net_xvector_block1_tdnnd11_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd11_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1927424)))]; + tensor 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("input_289_cast_fp16")]; + tensor m_21_cast_fp16 = sigmoid(x = input_289_cast_fp16)[name = tensor("m_21_cast_fp16")]; + tensor var_999_cast_fp16 = mul(x = y_21_cast_fp16, y = m_21_cast_fp16)[name = tensor("op_999_cast_fp16")]; + tensor input_291_interleave_0 = const()[name = tensor("input_291_interleave_0"), val = tensor(false)]; + tensor input_291_cast_fp16 = concat(axis = var_11, interleave = input_291_interleave_0, values = (input_271_cast_fp16, var_999_cast_fp16))[name = tensor("input_291_cast_fp16")]; + tensor net_xvector_block1_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1927552)))]; + tensor net_xvector_block1_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1928576)))]; + tensor net_xvector_block1_tdnnd12_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd12_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1929600)))]; + tensor net_xvector_block1_tdnnd12_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd12_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1930624)))]; + tensor 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("input_293_cast_fp16")]; + tensor input_295_cast_fp16 = relu(x = input_293_cast_fp16)[name = tensor("input_295_cast_fp16")]; + tensor input_297_pad_type_0 = const()[name = tensor("input_297_pad_type_0"), val = tensor("valid")]; + tensor input_297_strides_0 = const()[name = tensor("input_297_strides_0"), val = tensor([1])]; + tensor input_297_pad_0 = const()[name = tensor("input_297_pad_0"), val = tensor([0, 0])]; + tensor input_297_dilations_0 = const()[name = tensor("input_297_dilations_0"), val = tensor([1])]; + tensor input_297_groups_0 = const()[name = tensor("input_297_groups_0"), val = tensor(1)]; + tensor const_260_to_fp16 = const()[name = tensor("const_260_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1931648)))]; + tensor const_261_to_fp16 = const()[name = tensor("const_261_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2054592)))]; + tensor input_299_cast_fp16 = conv(bias = const_261_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_260_to_fp16, x = input_295_cast_fp16)[name = tensor("input_299_cast_fp16")]; + tensor input_301_cast_fp16 = relu(x = input_299_cast_fp16)[name = tensor("input_301_cast_fp16")]; + tensor y_23_pad_type_0 = const()[name = tensor("y_23_pad_type_0"), val = tensor("custom")]; + tensor y_23_pad_0 = const()[name = tensor("y_23_pad_0"), val = tensor([1, 1])]; + tensor y_23_strides_0 = const()[name = tensor("y_23_strides_0"), val = tensor([1])]; + tensor y_23_dilations_0 = const()[name = tensor("y_23_dilations_0"), val = tensor([1])]; + tensor y_23_groups_0 = const()[name = tensor("y_23_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd12_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd12_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2054912)))]; + tensor 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("y_23_cast_fp16")]; + tensor var_1036_axes_0 = const()[name = tensor("op_1036_axes_0"), val = tensor([-1])]; + tensor var_1036_keep_dims_0 = const()[name = tensor("op_1036_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1036_cast_fp16")]; + tensor var_1037 = const()[name = tensor("op_1037"), val = tensor([100])]; + tensor var_1038 = const()[name = tensor("op_1038"), val = tensor([100])]; + tensor seg_45_pad_type_0 = const()[name = tensor("seg_45_pad_type_0"), val = tensor("custom")]; + tensor seg_45_pad_0 = const()[name = tensor("seg_45_pad_0"), val = tensor([0, 0])]; + tensor seg_45_exclude_padding_from_average_0 = const()[name = tensor("seg_45_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_45_ceil_mode_0 = const()[name = tensor("seg_45_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_45_cast_fp16")]; + tensor var_1044_axes_0 = const()[name = tensor("op_1044_axes_0"), val = tensor([-1])]; + tensor var_1044_cast_fp16 = expand_dims(axes = var_1044_axes_0, x = seg_45_cast_fp16)[name = tensor("op_1044_cast_fp16")]; + tensor var_1046_reps_0 = const()[name = tensor("op_1046_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1046_cast_fp16 = tile(reps = var_1046_reps_0, x = var_1044_cast_fp16)[name = tensor("op_1046_cast_fp16")]; + tensor var_1047 = const()[name = tensor("op_1047"), val = tensor([1, 128, -1])]; + tensor seg_47_cast_fp16 = reshape(shape = var_1047, x = var_1046_cast_fp16)[name = tensor("seg_47_cast_fp16")]; + tensor input_303_cast_fp16 = add(x = var_1036_cast_fp16, y = seg_47_cast_fp16)[name = tensor("input_303_cast_fp16")]; + tensor input_305_pad_type_0 = const()[name = tensor("input_305_pad_type_0"), val = tensor("valid")]; + tensor input_305_strides_0 = const()[name = tensor("input_305_strides_0"), val = tensor([1])]; + tensor input_305_pad_0 = const()[name = tensor("input_305_pad_0"), val = tensor([0, 0])]; + tensor input_305_dilations_0 = const()[name = tensor("input_305_dilations_0"), val = tensor([1])]; + tensor input_305_groups_0 = const()[name = tensor("input_305_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd12_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd12_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2079552)))]; + tensor net_xvector_block1_tdnnd12_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd12_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2096000)))]; + tensor 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("input_305_cast_fp16")]; + tensor input_307_cast_fp16 = relu(x = input_305_cast_fp16)[name = tensor("input_307_cast_fp16")]; + tensor input_309_pad_type_0 = const()[name = tensor("input_309_pad_type_0"), val = tensor("valid")]; + tensor input_309_strides_0 = const()[name = tensor("input_309_strides_0"), val = tensor([1])]; + tensor input_309_pad_0 = const()[name = tensor("input_309_pad_0"), val = tensor([0, 0])]; + tensor input_309_dilations_0 = const()[name = tensor("input_309_dilations_0"), val = tensor([1])]; + tensor input_309_groups_0 = const()[name = tensor("input_309_groups_0"), val = tensor(1)]; + tensor net_xvector_block1_tdnnd12_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd12_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2096192)))]; + tensor net_xvector_block1_tdnnd12_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block1_tdnnd12_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2100352)))]; + tensor 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("input_309_cast_fp16")]; + tensor m_23_cast_fp16 = sigmoid(x = input_309_cast_fp16)[name = tensor("m_23_cast_fp16")]; + tensor var_1068_cast_fp16 = mul(x = y_23_cast_fp16, y = m_23_cast_fp16)[name = tensor("op_1068_cast_fp16")]; + tensor input_311_interleave_0 = const()[name = tensor("input_311_interleave_0"), val = tensor(false)]; + tensor input_311_cast_fp16 = concat(axis = var_11, interleave = input_311_interleave_0, values = (input_291_cast_fp16, var_1068_cast_fp16))[name = tensor("input_311_cast_fp16")]; + tensor net_xvector_transit1_nonlinear_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_transit1_nonlinear_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2100480)))]; + tensor net_xvector_transit1_nonlinear_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_transit1_nonlinear_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2101568)))]; + tensor net_xvector_transit1_nonlinear_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_transit1_nonlinear_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2102656)))]; + tensor net_xvector_transit1_nonlinear_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_transit1_nonlinear_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2103744)))]; + tensor 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("input_313_cast_fp16")]; + tensor input_315_cast_fp16 = relu(x = input_313_cast_fp16)[name = tensor("input_315_cast_fp16")]; + tensor input_317_pad_type_0 = const()[name = tensor("input_317_pad_type_0"), val = tensor("valid")]; + tensor input_317_strides_0 = const()[name = tensor("input_317_strides_0"), val = tensor([1])]; + tensor input_317_pad_0 = const()[name = tensor("input_317_pad_0"), val = tensor([0, 0])]; + tensor input_317_dilations_0 = const()[name = tensor("input_317_dilations_0"), val = tensor([1])]; + tensor input_317_groups_0 = const()[name = tensor("input_317_groups_0"), val = tensor(1)]; + tensor net_xvector_transit1_linear_weight_to_fp16 = const()[name = tensor("net_xvector_transit1_linear_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2104832)))]; + tensor 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("input_317_cast_fp16")]; + tensor net_xvector_block2_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2367040)))]; + tensor net_xvector_block2_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2367616)))]; + tensor net_xvector_block2_tdnnd1_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd1_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2368192)))]; + tensor net_xvector_block2_tdnnd1_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd1_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2368768)))]; + tensor 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("input_319_cast_fp16")]; + tensor input_321_cast_fp16 = relu(x = input_319_cast_fp16)[name = tensor("input_321_cast_fp16")]; + tensor input_323_pad_type_0 = const()[name = tensor("input_323_pad_type_0"), val = tensor("valid")]; + tensor input_323_strides_0 = const()[name = tensor("input_323_strides_0"), val = tensor([1])]; + tensor input_323_pad_0 = const()[name = tensor("input_323_pad_0"), val = tensor([0, 0])]; + tensor input_323_dilations_0 = const()[name = tensor("input_323_dilations_0"), val = tensor([1])]; + tensor input_323_groups_0 = const()[name = tensor("input_323_groups_0"), val = tensor(1)]; + tensor const_262_to_fp16 = const()[name = tensor("const_262_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2369344)))]; + tensor const_263_to_fp16 = const()[name = tensor("const_263_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2434944)))]; + tensor input_325_cast_fp16 = conv(bias = const_263_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_262_to_fp16, x = input_321_cast_fp16)[name = tensor("input_325_cast_fp16")]; + tensor input_327_cast_fp16 = relu(x = input_325_cast_fp16)[name = tensor("input_327_cast_fp16")]; + tensor y_25_pad_type_0 = const()[name = tensor("y_25_pad_type_0"), val = tensor("custom")]; + tensor y_25_pad_0 = const()[name = tensor("y_25_pad_0"), val = tensor([2, 2])]; + tensor y_25_dilations_0 = const()[name = tensor("y_25_dilations_0"), val = tensor([2])]; + tensor y_25_strides_0 = const()[name = tensor("y_25_strides_0"), val = tensor([1])]; + tensor y_25_groups_0 = const()[name = tensor("y_25_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd1_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd1_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2435264)))]; + tensor 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("y_25_cast_fp16")]; + tensor var_1144_axes_0 = const()[name = tensor("op_1144_axes_0"), val = tensor([-1])]; + tensor var_1144_keep_dims_0 = const()[name = tensor("op_1144_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1144_cast_fp16")]; + tensor var_1145 = const()[name = tensor("op_1145"), val = tensor([100])]; + tensor var_1146 = const()[name = tensor("op_1146"), val = tensor([100])]; + tensor seg_49_pad_type_0 = const()[name = tensor("seg_49_pad_type_0"), val = tensor("custom")]; + tensor seg_49_pad_0 = const()[name = tensor("seg_49_pad_0"), val = tensor([0, 0])]; + tensor seg_49_exclude_padding_from_average_0 = const()[name = tensor("seg_49_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_49_ceil_mode_0 = const()[name = tensor("seg_49_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_49_cast_fp16")]; + tensor var_1152_axes_0 = const()[name = tensor("op_1152_axes_0"), val = tensor([-1])]; + tensor var_1152_cast_fp16 = expand_dims(axes = var_1152_axes_0, x = seg_49_cast_fp16)[name = tensor("op_1152_cast_fp16")]; + tensor var_1154_reps_0 = const()[name = tensor("op_1154_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1154_cast_fp16 = tile(reps = var_1154_reps_0, x = var_1152_cast_fp16)[name = tensor("op_1154_cast_fp16")]; + tensor var_1155 = const()[name = tensor("op_1155"), val = tensor([1, 128, -1])]; + tensor seg_51_cast_fp16 = reshape(shape = var_1155, x = var_1154_cast_fp16)[name = tensor("seg_51_cast_fp16")]; + tensor input_329_cast_fp16 = add(x = var_1144_cast_fp16, y = seg_51_cast_fp16)[name = tensor("input_329_cast_fp16")]; + tensor input_331_pad_type_0 = const()[name = tensor("input_331_pad_type_0"), val = tensor("valid")]; + tensor input_331_strides_0 = const()[name = tensor("input_331_strides_0"), val = tensor([1])]; + tensor input_331_pad_0 = const()[name = tensor("input_331_pad_0"), val = tensor([0, 0])]; + tensor input_331_dilations_0 = const()[name = tensor("input_331_dilations_0"), val = tensor([1])]; + tensor input_331_groups_0 = const()[name = tensor("input_331_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd1_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd1_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2459904)))]; + tensor net_xvector_block2_tdnnd1_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd1_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2476352)))]; + tensor 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("input_331_cast_fp16")]; + tensor input_333_cast_fp16 = relu(x = input_331_cast_fp16)[name = tensor("input_333_cast_fp16")]; + tensor input_335_pad_type_0 = const()[name = tensor("input_335_pad_type_0"), val = tensor("valid")]; + tensor input_335_strides_0 = const()[name = tensor("input_335_strides_0"), val = tensor([1])]; + tensor input_335_pad_0 = const()[name = tensor("input_335_pad_0"), val = tensor([0, 0])]; + tensor input_335_dilations_0 = const()[name = tensor("input_335_dilations_0"), val = tensor([1])]; + tensor input_335_groups_0 = const()[name = tensor("input_335_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd1_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd1_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2476544)))]; + tensor net_xvector_block2_tdnnd1_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd1_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2480704)))]; + tensor 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("input_335_cast_fp16")]; + tensor m_25_cast_fp16 = sigmoid(x = input_335_cast_fp16)[name = tensor("m_25_cast_fp16")]; + tensor var_1176_cast_fp16 = mul(x = y_25_cast_fp16, y = m_25_cast_fp16)[name = tensor("op_1176_cast_fp16")]; + tensor input_337_interleave_0 = const()[name = tensor("input_337_interleave_0"), val = tensor(false)]; + tensor input_337_cast_fp16 = concat(axis = var_11, interleave = input_337_interleave_0, values = (input_317_cast_fp16, var_1176_cast_fp16))[name = tensor("input_337_cast_fp16")]; + tensor net_xvector_block2_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2480832)))]; + tensor net_xvector_block2_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2481472)))]; + tensor net_xvector_block2_tdnnd2_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd2_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2482112)))]; + tensor net_xvector_block2_tdnnd2_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd2_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2482752)))]; + tensor 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("input_339_cast_fp16")]; + tensor input_341_cast_fp16 = relu(x = input_339_cast_fp16)[name = tensor("input_341_cast_fp16")]; + tensor input_343_pad_type_0 = const()[name = tensor("input_343_pad_type_0"), val = tensor("valid")]; + tensor input_343_strides_0 = const()[name = tensor("input_343_strides_0"), val = tensor([1])]; + tensor input_343_pad_0 = const()[name = tensor("input_343_pad_0"), val = tensor([0, 0])]; + tensor input_343_dilations_0 = const()[name = tensor("input_343_dilations_0"), val = tensor([1])]; + tensor input_343_groups_0 = const()[name = tensor("input_343_groups_0"), val = tensor(1)]; + tensor const_264_to_fp16 = const()[name = tensor("const_264_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2483392)))]; + tensor const_265_to_fp16 = const()[name = tensor("const_265_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2557184)))]; + tensor input_345_cast_fp16 = conv(bias = const_265_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_264_to_fp16, x = input_341_cast_fp16)[name = tensor("input_345_cast_fp16")]; + tensor input_347_cast_fp16 = relu(x = input_345_cast_fp16)[name = tensor("input_347_cast_fp16")]; + tensor y_27_pad_type_0 = const()[name = tensor("y_27_pad_type_0"), val = tensor("custom")]; + tensor y_27_pad_0 = const()[name = tensor("y_27_pad_0"), val = tensor([2, 2])]; + tensor y_27_dilations_0 = const()[name = tensor("y_27_dilations_0"), val = tensor([2])]; + tensor y_27_strides_0 = const()[name = tensor("y_27_strides_0"), val = tensor([1])]; + tensor y_27_groups_0 = const()[name = tensor("y_27_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd2_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd2_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2557504)))]; + tensor 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("y_27_cast_fp16")]; + tensor var_1213_axes_0 = const()[name = tensor("op_1213_axes_0"), val = tensor([-1])]; + tensor var_1213_keep_dims_0 = const()[name = tensor("op_1213_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1213_cast_fp16")]; + tensor var_1214 = const()[name = tensor("op_1214"), val = tensor([100])]; + tensor var_1215 = const()[name = tensor("op_1215"), val = tensor([100])]; + tensor seg_53_pad_type_0 = const()[name = tensor("seg_53_pad_type_0"), val = tensor("custom")]; + tensor seg_53_pad_0 = const()[name = tensor("seg_53_pad_0"), val = tensor([0, 0])]; + tensor seg_53_exclude_padding_from_average_0 = const()[name = tensor("seg_53_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_53_ceil_mode_0 = const()[name = tensor("seg_53_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_53_cast_fp16")]; + tensor var_1221_axes_0 = const()[name = tensor("op_1221_axes_0"), val = tensor([-1])]; + tensor var_1221_cast_fp16 = expand_dims(axes = var_1221_axes_0, x = seg_53_cast_fp16)[name = tensor("op_1221_cast_fp16")]; + tensor var_1223_reps_0 = const()[name = tensor("op_1223_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1223_cast_fp16 = tile(reps = var_1223_reps_0, x = var_1221_cast_fp16)[name = tensor("op_1223_cast_fp16")]; + tensor var_1224 = const()[name = tensor("op_1224"), val = tensor([1, 128, -1])]; + tensor seg_55_cast_fp16 = reshape(shape = var_1224, x = var_1223_cast_fp16)[name = tensor("seg_55_cast_fp16")]; + tensor input_349_cast_fp16 = add(x = var_1213_cast_fp16, y = seg_55_cast_fp16)[name = tensor("input_349_cast_fp16")]; + tensor input_351_pad_type_0 = const()[name = tensor("input_351_pad_type_0"), val = tensor("valid")]; + tensor input_351_strides_0 = const()[name = tensor("input_351_strides_0"), val = tensor([1])]; + tensor input_351_pad_0 = const()[name = tensor("input_351_pad_0"), val = tensor([0, 0])]; + tensor input_351_dilations_0 = const()[name = tensor("input_351_dilations_0"), val = tensor([1])]; + tensor input_351_groups_0 = const()[name = tensor("input_351_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd2_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd2_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2582144)))]; + tensor net_xvector_block2_tdnnd2_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd2_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2598592)))]; + tensor 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("input_351_cast_fp16")]; + tensor input_353_cast_fp16 = relu(x = input_351_cast_fp16)[name = tensor("input_353_cast_fp16")]; + tensor input_355_pad_type_0 = const()[name = tensor("input_355_pad_type_0"), val = tensor("valid")]; + tensor input_355_strides_0 = const()[name = tensor("input_355_strides_0"), val = tensor([1])]; + tensor input_355_pad_0 = const()[name = tensor("input_355_pad_0"), val = tensor([0, 0])]; + tensor input_355_dilations_0 = const()[name = tensor("input_355_dilations_0"), val = tensor([1])]; + tensor input_355_groups_0 = const()[name = tensor("input_355_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd2_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd2_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2598784)))]; + tensor net_xvector_block2_tdnnd2_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd2_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2602944)))]; + tensor 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("input_355_cast_fp16")]; + tensor m_27_cast_fp16 = sigmoid(x = input_355_cast_fp16)[name = tensor("m_27_cast_fp16")]; + tensor var_1245_cast_fp16 = mul(x = y_27_cast_fp16, y = m_27_cast_fp16)[name = tensor("op_1245_cast_fp16")]; + tensor input_357_interleave_0 = const()[name = tensor("input_357_interleave_0"), val = tensor(false)]; + tensor input_357_cast_fp16 = concat(axis = var_11, interleave = input_357_interleave_0, values = (input_337_cast_fp16, var_1245_cast_fp16))[name = tensor("input_357_cast_fp16")]; + tensor net_xvector_block2_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2603072)))]; + tensor net_xvector_block2_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2603776)))]; + tensor net_xvector_block2_tdnnd3_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd3_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2604480)))]; + tensor net_xvector_block2_tdnnd3_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd3_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2605184)))]; + tensor 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("input_359_cast_fp16")]; + tensor input_361_cast_fp16 = relu(x = input_359_cast_fp16)[name = tensor("input_361_cast_fp16")]; + tensor input_363_pad_type_0 = const()[name = tensor("input_363_pad_type_0"), val = tensor("valid")]; + tensor input_363_strides_0 = const()[name = tensor("input_363_strides_0"), val = tensor([1])]; + tensor input_363_pad_0 = const()[name = tensor("input_363_pad_0"), val = tensor([0, 0])]; + tensor input_363_dilations_0 = const()[name = tensor("input_363_dilations_0"), val = tensor([1])]; + tensor input_363_groups_0 = const()[name = tensor("input_363_groups_0"), val = tensor(1)]; + tensor const_266_to_fp16 = const()[name = tensor("const_266_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2605888)))]; + tensor const_267_to_fp16 = const()[name = tensor("const_267_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2687872)))]; + tensor input_365_cast_fp16 = conv(bias = const_267_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_266_to_fp16, x = input_361_cast_fp16)[name = tensor("input_365_cast_fp16")]; + tensor input_367_cast_fp16 = relu(x = input_365_cast_fp16)[name = tensor("input_367_cast_fp16")]; + tensor y_29_pad_type_0 = const()[name = tensor("y_29_pad_type_0"), val = tensor("custom")]; + tensor y_29_pad_0 = const()[name = tensor("y_29_pad_0"), val = tensor([2, 2])]; + tensor y_29_dilations_0 = const()[name = tensor("y_29_dilations_0"), val = tensor([2])]; + tensor y_29_strides_0 = const()[name = tensor("y_29_strides_0"), val = tensor([1])]; + tensor y_29_groups_0 = const()[name = tensor("y_29_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd3_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd3_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2688192)))]; + tensor 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("y_29_cast_fp16")]; + tensor var_1282_axes_0 = const()[name = tensor("op_1282_axes_0"), val = tensor([-1])]; + tensor var_1282_keep_dims_0 = const()[name = tensor("op_1282_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1282_cast_fp16")]; + tensor var_1283 = const()[name = tensor("op_1283"), val = tensor([100])]; + tensor var_1284 = const()[name = tensor("op_1284"), val = tensor([100])]; + tensor seg_57_pad_type_0 = const()[name = tensor("seg_57_pad_type_0"), val = tensor("custom")]; + tensor seg_57_pad_0 = const()[name = tensor("seg_57_pad_0"), val = tensor([0, 0])]; + tensor seg_57_exclude_padding_from_average_0 = const()[name = tensor("seg_57_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_57_ceil_mode_0 = const()[name = tensor("seg_57_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_57_cast_fp16")]; + tensor var_1290_axes_0 = const()[name = tensor("op_1290_axes_0"), val = tensor([-1])]; + tensor var_1290_cast_fp16 = expand_dims(axes = var_1290_axes_0, x = seg_57_cast_fp16)[name = tensor("op_1290_cast_fp16")]; + tensor var_1292_reps_0 = const()[name = tensor("op_1292_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1292_cast_fp16 = tile(reps = var_1292_reps_0, x = var_1290_cast_fp16)[name = tensor("op_1292_cast_fp16")]; + tensor var_1293 = const()[name = tensor("op_1293"), val = tensor([1, 128, -1])]; + tensor seg_59_cast_fp16 = reshape(shape = var_1293, x = var_1292_cast_fp16)[name = tensor("seg_59_cast_fp16")]; + tensor input_369_cast_fp16 = add(x = var_1282_cast_fp16, y = seg_59_cast_fp16)[name = tensor("input_369_cast_fp16")]; + tensor input_371_pad_type_0 = const()[name = tensor("input_371_pad_type_0"), val = tensor("valid")]; + tensor input_371_strides_0 = const()[name = tensor("input_371_strides_0"), val = tensor([1])]; + tensor input_371_pad_0 = const()[name = tensor("input_371_pad_0"), val = tensor([0, 0])]; + tensor input_371_dilations_0 = const()[name = tensor("input_371_dilations_0"), val = tensor([1])]; + tensor input_371_groups_0 = const()[name = tensor("input_371_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd3_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd3_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2712832)))]; + tensor net_xvector_block2_tdnnd3_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd3_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2729280)))]; + tensor 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("input_371_cast_fp16")]; + tensor input_373_cast_fp16 = relu(x = input_371_cast_fp16)[name = tensor("input_373_cast_fp16")]; + tensor input_375_pad_type_0 = const()[name = tensor("input_375_pad_type_0"), val = tensor("valid")]; + tensor input_375_strides_0 = const()[name = tensor("input_375_strides_0"), val = tensor([1])]; + tensor input_375_pad_0 = const()[name = tensor("input_375_pad_0"), val = tensor([0, 0])]; + tensor input_375_dilations_0 = const()[name = tensor("input_375_dilations_0"), val = tensor([1])]; + tensor input_375_groups_0 = const()[name = tensor("input_375_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd3_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd3_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2729472)))]; + tensor net_xvector_block2_tdnnd3_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd3_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2733632)))]; + tensor 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("input_375_cast_fp16")]; + tensor m_29_cast_fp16 = sigmoid(x = input_375_cast_fp16)[name = tensor("m_29_cast_fp16")]; + tensor var_1314_cast_fp16 = mul(x = y_29_cast_fp16, y = m_29_cast_fp16)[name = tensor("op_1314_cast_fp16")]; + tensor input_377_interleave_0 = const()[name = tensor("input_377_interleave_0"), val = tensor(false)]; + tensor input_377_cast_fp16 = concat(axis = var_11, interleave = input_377_interleave_0, values = (input_357_cast_fp16, var_1314_cast_fp16))[name = tensor("input_377_cast_fp16")]; + tensor net_xvector_block2_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2733760)))]; + tensor net_xvector_block2_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2734528)))]; + tensor net_xvector_block2_tdnnd4_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd4_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2735296)))]; + tensor net_xvector_block2_tdnnd4_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd4_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2736064)))]; + tensor 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("input_379_cast_fp16")]; + tensor input_381_cast_fp16 = relu(x = input_379_cast_fp16)[name = tensor("input_381_cast_fp16")]; + tensor input_383_pad_type_0 = const()[name = tensor("input_383_pad_type_0"), val = tensor("valid")]; + tensor input_383_strides_0 = const()[name = tensor("input_383_strides_0"), val = tensor([1])]; + tensor input_383_pad_0 = const()[name = tensor("input_383_pad_0"), val = tensor([0, 0])]; + tensor input_383_dilations_0 = const()[name = tensor("input_383_dilations_0"), val = tensor([1])]; + tensor input_383_groups_0 = const()[name = tensor("input_383_groups_0"), val = tensor(1)]; + tensor const_268_to_fp16 = const()[name = tensor("const_268_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2736832)))]; + tensor const_269_to_fp16 = const()[name = tensor("const_269_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2827008)))]; + tensor input_385_cast_fp16 = conv(bias = const_269_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_268_to_fp16, x = input_381_cast_fp16)[name = tensor("input_385_cast_fp16")]; + tensor input_387_cast_fp16 = relu(x = input_385_cast_fp16)[name = tensor("input_387_cast_fp16")]; + tensor y_31_pad_type_0 = const()[name = tensor("y_31_pad_type_0"), val = tensor("custom")]; + tensor y_31_pad_0 = const()[name = tensor("y_31_pad_0"), val = tensor([2, 2])]; + tensor y_31_dilations_0 = const()[name = tensor("y_31_dilations_0"), val = tensor([2])]; + tensor y_31_strides_0 = const()[name = tensor("y_31_strides_0"), val = tensor([1])]; + tensor y_31_groups_0 = const()[name = tensor("y_31_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd4_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd4_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2827328)))]; + tensor 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("y_31_cast_fp16")]; + tensor var_1351_axes_0 = const()[name = tensor("op_1351_axes_0"), val = tensor([-1])]; + tensor var_1351_keep_dims_0 = const()[name = tensor("op_1351_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1351_cast_fp16")]; + tensor var_1352 = const()[name = tensor("op_1352"), val = tensor([100])]; + tensor var_1353 = const()[name = tensor("op_1353"), val = tensor([100])]; + tensor seg_61_pad_type_0 = const()[name = tensor("seg_61_pad_type_0"), val = tensor("custom")]; + tensor seg_61_pad_0 = const()[name = tensor("seg_61_pad_0"), val = tensor([0, 0])]; + tensor seg_61_exclude_padding_from_average_0 = const()[name = tensor("seg_61_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_61_ceil_mode_0 = const()[name = tensor("seg_61_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_61_cast_fp16")]; + tensor var_1359_axes_0 = const()[name = tensor("op_1359_axes_0"), val = tensor([-1])]; + tensor var_1359_cast_fp16 = expand_dims(axes = var_1359_axes_0, x = seg_61_cast_fp16)[name = tensor("op_1359_cast_fp16")]; + tensor var_1361_reps_0 = const()[name = tensor("op_1361_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1361_cast_fp16 = tile(reps = var_1361_reps_0, x = var_1359_cast_fp16)[name = tensor("op_1361_cast_fp16")]; + tensor var_1362 = const()[name = tensor("op_1362"), val = tensor([1, 128, -1])]; + tensor seg_63_cast_fp16 = reshape(shape = var_1362, x = var_1361_cast_fp16)[name = tensor("seg_63_cast_fp16")]; + tensor input_389_cast_fp16 = add(x = var_1351_cast_fp16, y = seg_63_cast_fp16)[name = tensor("input_389_cast_fp16")]; + tensor input_391_pad_type_0 = const()[name = tensor("input_391_pad_type_0"), val = tensor("valid")]; + tensor input_391_strides_0 = const()[name = tensor("input_391_strides_0"), val = tensor([1])]; + tensor input_391_pad_0 = const()[name = tensor("input_391_pad_0"), val = tensor([0, 0])]; + tensor input_391_dilations_0 = const()[name = tensor("input_391_dilations_0"), val = tensor([1])]; + tensor input_391_groups_0 = const()[name = tensor("input_391_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd4_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd4_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2851968)))]; + tensor net_xvector_block2_tdnnd4_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd4_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2868416)))]; + tensor 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("input_391_cast_fp16")]; + tensor input_393_cast_fp16 = relu(x = input_391_cast_fp16)[name = tensor("input_393_cast_fp16")]; + tensor input_395_pad_type_0 = const()[name = tensor("input_395_pad_type_0"), val = tensor("valid")]; + tensor input_395_strides_0 = const()[name = tensor("input_395_strides_0"), val = tensor([1])]; + tensor input_395_pad_0 = const()[name = tensor("input_395_pad_0"), val = tensor([0, 0])]; + tensor input_395_dilations_0 = const()[name = tensor("input_395_dilations_0"), val = tensor([1])]; + tensor input_395_groups_0 = const()[name = tensor("input_395_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd4_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd4_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2868608)))]; + tensor net_xvector_block2_tdnnd4_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd4_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2872768)))]; + tensor 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("input_395_cast_fp16")]; + tensor m_31_cast_fp16 = sigmoid(x = input_395_cast_fp16)[name = tensor("m_31_cast_fp16")]; + tensor var_1383_cast_fp16 = mul(x = y_31_cast_fp16, y = m_31_cast_fp16)[name = tensor("op_1383_cast_fp16")]; + tensor input_397_interleave_0 = const()[name = tensor("input_397_interleave_0"), val = tensor(false)]; + tensor input_397_cast_fp16 = concat(axis = var_11, interleave = input_397_interleave_0, values = (input_377_cast_fp16, var_1383_cast_fp16))[name = tensor("input_397_cast_fp16")]; + tensor net_xvector_block2_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2872896)))]; + tensor net_xvector_block2_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2873728)))]; + tensor net_xvector_block2_tdnnd5_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd5_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2874560)))]; + tensor net_xvector_block2_tdnnd5_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd5_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2875392)))]; + tensor 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("input_399_cast_fp16")]; + tensor input_401_cast_fp16 = relu(x = input_399_cast_fp16)[name = tensor("input_401_cast_fp16")]; + tensor input_403_pad_type_0 = const()[name = tensor("input_403_pad_type_0"), val = tensor("valid")]; + tensor input_403_strides_0 = const()[name = tensor("input_403_strides_0"), val = tensor([1])]; + tensor input_403_pad_0 = const()[name = tensor("input_403_pad_0"), val = tensor([0, 0])]; + tensor input_403_dilations_0 = const()[name = tensor("input_403_dilations_0"), val = tensor([1])]; + tensor input_403_groups_0 = const()[name = tensor("input_403_groups_0"), val = tensor(1)]; + tensor const_270_to_fp16 = const()[name = tensor("const_270_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2876224)))]; + tensor const_271_to_fp16 = const()[name = tensor("const_271_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2974592)))]; + tensor input_405_cast_fp16 = conv(bias = const_271_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_270_to_fp16, x = input_401_cast_fp16)[name = tensor("input_405_cast_fp16")]; + tensor input_407_cast_fp16 = relu(x = input_405_cast_fp16)[name = tensor("input_407_cast_fp16")]; + tensor y_33_pad_type_0 = const()[name = tensor("y_33_pad_type_0"), val = tensor("custom")]; + tensor y_33_pad_0 = const()[name = tensor("y_33_pad_0"), val = tensor([2, 2])]; + tensor y_33_dilations_0 = const()[name = tensor("y_33_dilations_0"), val = tensor([2])]; + tensor y_33_strides_0 = const()[name = tensor("y_33_strides_0"), val = tensor([1])]; + tensor y_33_groups_0 = const()[name = tensor("y_33_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd5_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd5_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2974912)))]; + tensor 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("y_33_cast_fp16")]; + tensor var_1420_axes_0 = const()[name = tensor("op_1420_axes_0"), val = tensor([-1])]; + tensor var_1420_keep_dims_0 = const()[name = tensor("op_1420_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1420_cast_fp16")]; + tensor var_1421 = const()[name = tensor("op_1421"), val = tensor([100])]; + tensor var_1422 = const()[name = tensor("op_1422"), val = tensor([100])]; + tensor seg_65_pad_type_0 = const()[name = tensor("seg_65_pad_type_0"), val = tensor("custom")]; + tensor seg_65_pad_0 = const()[name = tensor("seg_65_pad_0"), val = tensor([0, 0])]; + tensor seg_65_exclude_padding_from_average_0 = const()[name = tensor("seg_65_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_65_ceil_mode_0 = const()[name = tensor("seg_65_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_65_cast_fp16")]; + tensor var_1428_axes_0 = const()[name = tensor("op_1428_axes_0"), val = tensor([-1])]; + tensor var_1428_cast_fp16 = expand_dims(axes = var_1428_axes_0, x = seg_65_cast_fp16)[name = tensor("op_1428_cast_fp16")]; + tensor var_1430_reps_0 = const()[name = tensor("op_1430_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1430_cast_fp16 = tile(reps = var_1430_reps_0, x = var_1428_cast_fp16)[name = tensor("op_1430_cast_fp16")]; + tensor var_1431 = const()[name = tensor("op_1431"), val = tensor([1, 128, -1])]; + tensor seg_67_cast_fp16 = reshape(shape = var_1431, x = var_1430_cast_fp16)[name = tensor("seg_67_cast_fp16")]; + tensor input_409_cast_fp16 = add(x = var_1420_cast_fp16, y = seg_67_cast_fp16)[name = tensor("input_409_cast_fp16")]; + tensor input_411_pad_type_0 = const()[name = tensor("input_411_pad_type_0"), val = tensor("valid")]; + tensor input_411_strides_0 = const()[name = tensor("input_411_strides_0"), val = tensor([1])]; + tensor input_411_pad_0 = const()[name = tensor("input_411_pad_0"), val = tensor([0, 0])]; + tensor input_411_dilations_0 = const()[name = tensor("input_411_dilations_0"), val = tensor([1])]; + tensor input_411_groups_0 = const()[name = tensor("input_411_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd5_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd5_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2999552)))]; + tensor net_xvector_block2_tdnnd5_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd5_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3016000)))]; + tensor 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("input_411_cast_fp16")]; + tensor input_413_cast_fp16 = relu(x = input_411_cast_fp16)[name = tensor("input_413_cast_fp16")]; + tensor input_415_pad_type_0 = const()[name = tensor("input_415_pad_type_0"), val = tensor("valid")]; + tensor input_415_strides_0 = const()[name = tensor("input_415_strides_0"), val = tensor([1])]; + tensor input_415_pad_0 = const()[name = tensor("input_415_pad_0"), val = tensor([0, 0])]; + tensor input_415_dilations_0 = const()[name = tensor("input_415_dilations_0"), val = tensor([1])]; + tensor input_415_groups_0 = const()[name = tensor("input_415_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd5_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd5_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3016192)))]; + tensor net_xvector_block2_tdnnd5_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd5_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3020352)))]; + tensor 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("input_415_cast_fp16")]; + tensor m_33_cast_fp16 = sigmoid(x = input_415_cast_fp16)[name = tensor("m_33_cast_fp16")]; + tensor var_1452_cast_fp16 = mul(x = y_33_cast_fp16, y = m_33_cast_fp16)[name = tensor("op_1452_cast_fp16")]; + tensor input_417_interleave_0 = const()[name = tensor("input_417_interleave_0"), val = tensor(false)]; + tensor input_417_cast_fp16 = concat(axis = var_11, interleave = input_417_interleave_0, values = (input_397_cast_fp16, var_1452_cast_fp16))[name = tensor("input_417_cast_fp16")]; + tensor net_xvector_block2_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3020480)))]; + tensor net_xvector_block2_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3021376)))]; + tensor net_xvector_block2_tdnnd6_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd6_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3022272)))]; + tensor net_xvector_block2_tdnnd6_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd6_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3023168)))]; + tensor 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("input_419_cast_fp16")]; + tensor input_421_cast_fp16 = relu(x = input_419_cast_fp16)[name = tensor("input_421_cast_fp16")]; + tensor input_423_pad_type_0 = const()[name = tensor("input_423_pad_type_0"), val = tensor("valid")]; + tensor input_423_strides_0 = const()[name = tensor("input_423_strides_0"), val = tensor([1])]; + tensor input_423_pad_0 = const()[name = tensor("input_423_pad_0"), val = tensor([0, 0])]; + tensor input_423_dilations_0 = const()[name = tensor("input_423_dilations_0"), val = tensor([1])]; + tensor input_423_groups_0 = const()[name = tensor("input_423_groups_0"), val = tensor(1)]; + tensor const_272_to_fp16 = const()[name = tensor("const_272_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3024064)))]; + tensor const_273_to_fp16 = const()[name = tensor("const_273_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3130624)))]; + tensor input_425_cast_fp16 = conv(bias = const_273_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_272_to_fp16, x = input_421_cast_fp16)[name = tensor("input_425_cast_fp16")]; + tensor input_427_cast_fp16 = relu(x = input_425_cast_fp16)[name = tensor("input_427_cast_fp16")]; + tensor y_35_pad_type_0 = const()[name = tensor("y_35_pad_type_0"), val = tensor("custom")]; + tensor y_35_pad_0 = const()[name = tensor("y_35_pad_0"), val = tensor([2, 2])]; + tensor y_35_dilations_0 = const()[name = tensor("y_35_dilations_0"), val = tensor([2])]; + tensor y_35_strides_0 = const()[name = tensor("y_35_strides_0"), val = tensor([1])]; + tensor y_35_groups_0 = const()[name = tensor("y_35_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd6_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd6_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3130944)))]; + tensor 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("y_35_cast_fp16")]; + tensor var_1489_axes_0 = const()[name = tensor("op_1489_axes_0"), val = tensor([-1])]; + tensor var_1489_keep_dims_0 = const()[name = tensor("op_1489_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1489_cast_fp16")]; + tensor var_1490 = const()[name = tensor("op_1490"), val = tensor([100])]; + tensor var_1491 = const()[name = tensor("op_1491"), val = tensor([100])]; + tensor seg_69_pad_type_0 = const()[name = tensor("seg_69_pad_type_0"), val = tensor("custom")]; + tensor seg_69_pad_0 = const()[name = tensor("seg_69_pad_0"), val = tensor([0, 0])]; + tensor seg_69_exclude_padding_from_average_0 = const()[name = tensor("seg_69_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_69_ceil_mode_0 = const()[name = tensor("seg_69_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_69_cast_fp16")]; + tensor var_1497_axes_0 = const()[name = tensor("op_1497_axes_0"), val = tensor([-1])]; + tensor var_1497_cast_fp16 = expand_dims(axes = var_1497_axes_0, x = seg_69_cast_fp16)[name = tensor("op_1497_cast_fp16")]; + tensor var_1499_reps_0 = const()[name = tensor("op_1499_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1499_cast_fp16 = tile(reps = var_1499_reps_0, x = var_1497_cast_fp16)[name = tensor("op_1499_cast_fp16")]; + tensor var_1500 = const()[name = tensor("op_1500"), val = tensor([1, 128, -1])]; + tensor seg_71_cast_fp16 = reshape(shape = var_1500, x = var_1499_cast_fp16)[name = tensor("seg_71_cast_fp16")]; + tensor input_429_cast_fp16 = add(x = var_1489_cast_fp16, y = seg_71_cast_fp16)[name = tensor("input_429_cast_fp16")]; + tensor input_431_pad_type_0 = const()[name = tensor("input_431_pad_type_0"), val = tensor("valid")]; + tensor input_431_strides_0 = const()[name = tensor("input_431_strides_0"), val = tensor([1])]; + tensor input_431_pad_0 = const()[name = tensor("input_431_pad_0"), val = tensor([0, 0])]; + tensor input_431_dilations_0 = const()[name = tensor("input_431_dilations_0"), val = tensor([1])]; + tensor input_431_groups_0 = const()[name = tensor("input_431_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd6_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd6_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3155584)))]; + tensor net_xvector_block2_tdnnd6_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd6_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3172032)))]; + tensor 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("input_431_cast_fp16")]; + tensor input_433_cast_fp16 = relu(x = input_431_cast_fp16)[name = tensor("input_433_cast_fp16")]; + tensor input_435_pad_type_0 = const()[name = tensor("input_435_pad_type_0"), val = tensor("valid")]; + tensor input_435_strides_0 = const()[name = tensor("input_435_strides_0"), val = tensor([1])]; + tensor input_435_pad_0 = const()[name = tensor("input_435_pad_0"), val = tensor([0, 0])]; + tensor input_435_dilations_0 = const()[name = tensor("input_435_dilations_0"), val = tensor([1])]; + tensor input_435_groups_0 = const()[name = tensor("input_435_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd6_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd6_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3172224)))]; + tensor net_xvector_block2_tdnnd6_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd6_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3176384)))]; + tensor 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("input_435_cast_fp16")]; + tensor m_35_cast_fp16 = sigmoid(x = input_435_cast_fp16)[name = tensor("m_35_cast_fp16")]; + tensor var_1521_cast_fp16 = mul(x = y_35_cast_fp16, y = m_35_cast_fp16)[name = tensor("op_1521_cast_fp16")]; + tensor input_437_interleave_0 = const()[name = tensor("input_437_interleave_0"), val = tensor(false)]; + tensor input_437_cast_fp16 = concat(axis = var_11, interleave = input_437_interleave_0, values = (input_417_cast_fp16, var_1521_cast_fp16))[name = tensor("input_437_cast_fp16")]; + tensor net_xvector_block2_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3176512)))]; + tensor net_xvector_block2_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3177472)))]; + tensor net_xvector_block2_tdnnd7_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd7_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3178432)))]; + tensor net_xvector_block2_tdnnd7_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd7_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3179392)))]; + tensor 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("input_439_cast_fp16")]; + tensor input_441_cast_fp16 = relu(x = input_439_cast_fp16)[name = tensor("input_441_cast_fp16")]; + tensor input_443_pad_type_0 = const()[name = tensor("input_443_pad_type_0"), val = tensor("valid")]; + tensor input_443_strides_0 = const()[name = tensor("input_443_strides_0"), val = tensor([1])]; + tensor input_443_pad_0 = const()[name = tensor("input_443_pad_0"), val = tensor([0, 0])]; + tensor input_443_dilations_0 = const()[name = tensor("input_443_dilations_0"), val = tensor([1])]; + tensor input_443_groups_0 = const()[name = tensor("input_443_groups_0"), val = tensor(1)]; + tensor const_274_to_fp16 = const()[name = tensor("const_274_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3180352)))]; + tensor const_275_to_fp16 = const()[name = tensor("const_275_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3295104)))]; + tensor input_445_cast_fp16 = conv(bias = const_275_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_274_to_fp16, x = input_441_cast_fp16)[name = tensor("input_445_cast_fp16")]; + tensor input_447_cast_fp16 = relu(x = input_445_cast_fp16)[name = tensor("input_447_cast_fp16")]; + tensor y_37_pad_type_0 = const()[name = tensor("y_37_pad_type_0"), val = tensor("custom")]; + tensor y_37_pad_0 = const()[name = tensor("y_37_pad_0"), val = tensor([2, 2])]; + tensor y_37_dilations_0 = const()[name = tensor("y_37_dilations_0"), val = tensor([2])]; + tensor y_37_strides_0 = const()[name = tensor("y_37_strides_0"), val = tensor([1])]; + tensor y_37_groups_0 = const()[name = tensor("y_37_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd7_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd7_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3295424)))]; + tensor 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("y_37_cast_fp16")]; + tensor var_1558_axes_0 = const()[name = tensor("op_1558_axes_0"), val = tensor([-1])]; + tensor var_1558_keep_dims_0 = const()[name = tensor("op_1558_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1558_cast_fp16")]; + tensor var_1559 = const()[name = tensor("op_1559"), val = tensor([100])]; + tensor var_1560 = const()[name = tensor("op_1560"), val = tensor([100])]; + tensor seg_73_pad_type_0 = const()[name = tensor("seg_73_pad_type_0"), val = tensor("custom")]; + tensor seg_73_pad_0 = const()[name = tensor("seg_73_pad_0"), val = tensor([0, 0])]; + tensor seg_73_exclude_padding_from_average_0 = const()[name = tensor("seg_73_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_73_ceil_mode_0 = const()[name = tensor("seg_73_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_73_cast_fp16")]; + tensor var_1566_axes_0 = const()[name = tensor("op_1566_axes_0"), val = tensor([-1])]; + tensor var_1566_cast_fp16 = expand_dims(axes = var_1566_axes_0, x = seg_73_cast_fp16)[name = tensor("op_1566_cast_fp16")]; + tensor var_1568_reps_0 = const()[name = tensor("op_1568_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1568_cast_fp16 = tile(reps = var_1568_reps_0, x = var_1566_cast_fp16)[name = tensor("op_1568_cast_fp16")]; + tensor var_1569 = const()[name = tensor("op_1569"), val = tensor([1, 128, -1])]; + tensor seg_75_cast_fp16 = reshape(shape = var_1569, x = var_1568_cast_fp16)[name = tensor("seg_75_cast_fp16")]; + tensor input_449_cast_fp16 = add(x = var_1558_cast_fp16, y = seg_75_cast_fp16)[name = tensor("input_449_cast_fp16")]; + tensor input_451_pad_type_0 = const()[name = tensor("input_451_pad_type_0"), val = tensor("valid")]; + tensor input_451_strides_0 = const()[name = tensor("input_451_strides_0"), val = tensor([1])]; + tensor input_451_pad_0 = const()[name = tensor("input_451_pad_0"), val = tensor([0, 0])]; + tensor input_451_dilations_0 = const()[name = tensor("input_451_dilations_0"), val = tensor([1])]; + tensor input_451_groups_0 = const()[name = tensor("input_451_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd7_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd7_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3320064)))]; + tensor net_xvector_block2_tdnnd7_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd7_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3336512)))]; + tensor 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("input_451_cast_fp16")]; + tensor input_453_cast_fp16 = relu(x = input_451_cast_fp16)[name = tensor("input_453_cast_fp16")]; + tensor input_455_pad_type_0 = const()[name = tensor("input_455_pad_type_0"), val = tensor("valid")]; + tensor input_455_strides_0 = const()[name = tensor("input_455_strides_0"), val = tensor([1])]; + tensor input_455_pad_0 = const()[name = tensor("input_455_pad_0"), val = tensor([0, 0])]; + tensor input_455_dilations_0 = const()[name = tensor("input_455_dilations_0"), val = tensor([1])]; + tensor input_455_groups_0 = const()[name = tensor("input_455_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd7_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd7_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3336704)))]; + tensor net_xvector_block2_tdnnd7_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd7_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3340864)))]; + tensor 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("input_455_cast_fp16")]; + tensor m_37_cast_fp16 = sigmoid(x = input_455_cast_fp16)[name = tensor("m_37_cast_fp16")]; + tensor var_1590_cast_fp16 = mul(x = y_37_cast_fp16, y = m_37_cast_fp16)[name = tensor("op_1590_cast_fp16")]; + tensor input_457_interleave_0 = const()[name = tensor("input_457_interleave_0"), val = tensor(false)]; + tensor input_457_cast_fp16 = concat(axis = var_11, interleave = input_457_interleave_0, values = (input_437_cast_fp16, var_1590_cast_fp16))[name = tensor("input_457_cast_fp16")]; + tensor net_xvector_block2_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3340992)))]; + tensor net_xvector_block2_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3342016)))]; + tensor net_xvector_block2_tdnnd8_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd8_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3343040)))]; + tensor net_xvector_block2_tdnnd8_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd8_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3344064)))]; + tensor 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("input_459_cast_fp16")]; + tensor input_461_cast_fp16 = relu(x = input_459_cast_fp16)[name = tensor("input_461_cast_fp16")]; + tensor input_463_pad_type_0 = const()[name = tensor("input_463_pad_type_0"), val = tensor("valid")]; + tensor input_463_strides_0 = const()[name = tensor("input_463_strides_0"), val = tensor([1])]; + tensor input_463_pad_0 = const()[name = tensor("input_463_pad_0"), val = tensor([0, 0])]; + tensor input_463_dilations_0 = const()[name = tensor("input_463_dilations_0"), val = tensor([1])]; + tensor input_463_groups_0 = const()[name = tensor("input_463_groups_0"), val = tensor(1)]; + tensor const_276_to_fp16 = const()[name = tensor("const_276_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3345088)))]; + tensor const_277_to_fp16 = const()[name = tensor("const_277_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3468032)))]; + tensor input_465_cast_fp16 = conv(bias = const_277_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_276_to_fp16, x = input_461_cast_fp16)[name = tensor("input_465_cast_fp16")]; + tensor input_467_cast_fp16 = relu(x = input_465_cast_fp16)[name = tensor("input_467_cast_fp16")]; + tensor y_39_pad_type_0 = const()[name = tensor("y_39_pad_type_0"), val = tensor("custom")]; + tensor y_39_pad_0 = const()[name = tensor("y_39_pad_0"), val = tensor([2, 2])]; + tensor y_39_dilations_0 = const()[name = tensor("y_39_dilations_0"), val = tensor([2])]; + tensor y_39_strides_0 = const()[name = tensor("y_39_strides_0"), val = tensor([1])]; + tensor y_39_groups_0 = const()[name = tensor("y_39_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd8_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd8_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3468352)))]; + tensor 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("y_39_cast_fp16")]; + tensor var_1627_axes_0 = const()[name = tensor("op_1627_axes_0"), val = tensor([-1])]; + tensor var_1627_keep_dims_0 = const()[name = tensor("op_1627_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1627_cast_fp16")]; + tensor var_1628 = const()[name = tensor("op_1628"), val = tensor([100])]; + tensor var_1629 = const()[name = tensor("op_1629"), val = tensor([100])]; + tensor seg_77_pad_type_0 = const()[name = tensor("seg_77_pad_type_0"), val = tensor("custom")]; + tensor seg_77_pad_0 = const()[name = tensor("seg_77_pad_0"), val = tensor([0, 0])]; + tensor seg_77_exclude_padding_from_average_0 = const()[name = tensor("seg_77_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_77_ceil_mode_0 = const()[name = tensor("seg_77_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_77_cast_fp16")]; + tensor var_1635_axes_0 = const()[name = tensor("op_1635_axes_0"), val = tensor([-1])]; + tensor var_1635_cast_fp16 = expand_dims(axes = var_1635_axes_0, x = seg_77_cast_fp16)[name = tensor("op_1635_cast_fp16")]; + tensor var_1637_reps_0 = const()[name = tensor("op_1637_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1637_cast_fp16 = tile(reps = var_1637_reps_0, x = var_1635_cast_fp16)[name = tensor("op_1637_cast_fp16")]; + tensor var_1638 = const()[name = tensor("op_1638"), val = tensor([1, 128, -1])]; + tensor seg_79_cast_fp16 = reshape(shape = var_1638, x = var_1637_cast_fp16)[name = tensor("seg_79_cast_fp16")]; + tensor input_469_cast_fp16 = add(x = var_1627_cast_fp16, y = seg_79_cast_fp16)[name = tensor("input_469_cast_fp16")]; + tensor input_471_pad_type_0 = const()[name = tensor("input_471_pad_type_0"), val = tensor("valid")]; + tensor input_471_strides_0 = const()[name = tensor("input_471_strides_0"), val = tensor([1])]; + tensor input_471_pad_0 = const()[name = tensor("input_471_pad_0"), val = tensor([0, 0])]; + tensor input_471_dilations_0 = const()[name = tensor("input_471_dilations_0"), val = tensor([1])]; + tensor input_471_groups_0 = const()[name = tensor("input_471_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd8_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd8_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3492992)))]; + tensor net_xvector_block2_tdnnd8_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd8_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3509440)))]; + tensor 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("input_471_cast_fp16")]; + tensor input_473_cast_fp16 = relu(x = input_471_cast_fp16)[name = tensor("input_473_cast_fp16")]; + tensor input_475_pad_type_0 = const()[name = tensor("input_475_pad_type_0"), val = tensor("valid")]; + tensor input_475_strides_0 = const()[name = tensor("input_475_strides_0"), val = tensor([1])]; + tensor input_475_pad_0 = const()[name = tensor("input_475_pad_0"), val = tensor([0, 0])]; + tensor input_475_dilations_0 = const()[name = tensor("input_475_dilations_0"), val = tensor([1])]; + tensor input_475_groups_0 = const()[name = tensor("input_475_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd8_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd8_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3509632)))]; + tensor net_xvector_block2_tdnnd8_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd8_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3513792)))]; + tensor 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("input_475_cast_fp16")]; + tensor m_39_cast_fp16 = sigmoid(x = input_475_cast_fp16)[name = tensor("m_39_cast_fp16")]; + tensor var_1659_cast_fp16 = mul(x = y_39_cast_fp16, y = m_39_cast_fp16)[name = tensor("op_1659_cast_fp16")]; + tensor input_477_interleave_0 = const()[name = tensor("input_477_interleave_0"), val = tensor(false)]; + tensor input_477_cast_fp16 = concat(axis = var_11, interleave = input_477_interleave_0, values = (input_457_cast_fp16, var_1659_cast_fp16))[name = tensor("input_477_cast_fp16")]; + tensor net_xvector_block2_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3513920)))]; + tensor net_xvector_block2_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3515008)))]; + tensor net_xvector_block2_tdnnd9_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd9_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3516096)))]; + tensor net_xvector_block2_tdnnd9_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd9_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3517184)))]; + tensor 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("input_479_cast_fp16")]; + tensor input_481_cast_fp16 = relu(x = input_479_cast_fp16)[name = tensor("input_481_cast_fp16")]; + tensor input_483_pad_type_0 = const()[name = tensor("input_483_pad_type_0"), val = tensor("valid")]; + tensor input_483_strides_0 = const()[name = tensor("input_483_strides_0"), val = tensor([1])]; + tensor input_483_pad_0 = const()[name = tensor("input_483_pad_0"), val = tensor([0, 0])]; + tensor input_483_dilations_0 = const()[name = tensor("input_483_dilations_0"), val = tensor([1])]; + tensor input_483_groups_0 = const()[name = tensor("input_483_groups_0"), val = tensor(1)]; + tensor const_278_to_fp16 = const()[name = tensor("const_278_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3518272)))]; + tensor const_279_to_fp16 = const()[name = tensor("const_279_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3649408)))]; + tensor input_485_cast_fp16 = conv(bias = const_279_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_278_to_fp16, x = input_481_cast_fp16)[name = tensor("input_485_cast_fp16")]; + tensor input_487_cast_fp16 = relu(x = input_485_cast_fp16)[name = tensor("input_487_cast_fp16")]; + tensor y_41_pad_type_0 = const()[name = tensor("y_41_pad_type_0"), val = tensor("custom")]; + tensor y_41_pad_0 = const()[name = tensor("y_41_pad_0"), val = tensor([2, 2])]; + tensor y_41_dilations_0 = const()[name = tensor("y_41_dilations_0"), val = tensor([2])]; + tensor y_41_strides_0 = const()[name = tensor("y_41_strides_0"), val = tensor([1])]; + tensor y_41_groups_0 = const()[name = tensor("y_41_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd9_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd9_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3649728)))]; + tensor 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("y_41_cast_fp16")]; + tensor var_1696_axes_0 = const()[name = tensor("op_1696_axes_0"), val = tensor([-1])]; + tensor var_1696_keep_dims_0 = const()[name = tensor("op_1696_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1696_cast_fp16")]; + tensor var_1697 = const()[name = tensor("op_1697"), val = tensor([100])]; + tensor var_1698 = const()[name = tensor("op_1698"), val = tensor([100])]; + tensor seg_81_pad_type_0 = const()[name = tensor("seg_81_pad_type_0"), val = tensor("custom")]; + tensor seg_81_pad_0 = const()[name = tensor("seg_81_pad_0"), val = tensor([0, 0])]; + tensor seg_81_exclude_padding_from_average_0 = const()[name = tensor("seg_81_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_81_ceil_mode_0 = const()[name = tensor("seg_81_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_81_cast_fp16")]; + tensor var_1704_axes_0 = const()[name = tensor("op_1704_axes_0"), val = tensor([-1])]; + tensor var_1704_cast_fp16 = expand_dims(axes = var_1704_axes_0, x = seg_81_cast_fp16)[name = tensor("op_1704_cast_fp16")]; + tensor var_1706_reps_0 = const()[name = tensor("op_1706_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1706_cast_fp16 = tile(reps = var_1706_reps_0, x = var_1704_cast_fp16)[name = tensor("op_1706_cast_fp16")]; + tensor var_1707 = const()[name = tensor("op_1707"), val = tensor([1, 128, -1])]; + tensor seg_83_cast_fp16 = reshape(shape = var_1707, x = var_1706_cast_fp16)[name = tensor("seg_83_cast_fp16")]; + tensor input_489_cast_fp16 = add(x = var_1696_cast_fp16, y = seg_83_cast_fp16)[name = tensor("input_489_cast_fp16")]; + tensor input_491_pad_type_0 = const()[name = tensor("input_491_pad_type_0"), val = tensor("valid")]; + tensor input_491_strides_0 = const()[name = tensor("input_491_strides_0"), val = tensor([1])]; + tensor input_491_pad_0 = const()[name = tensor("input_491_pad_0"), val = tensor([0, 0])]; + tensor input_491_dilations_0 = const()[name = tensor("input_491_dilations_0"), val = tensor([1])]; + tensor input_491_groups_0 = const()[name = tensor("input_491_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd9_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd9_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3674368)))]; + tensor net_xvector_block2_tdnnd9_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd9_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3690816)))]; + tensor 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("input_491_cast_fp16")]; + tensor input_493_cast_fp16 = relu(x = input_491_cast_fp16)[name = tensor("input_493_cast_fp16")]; + tensor input_495_pad_type_0 = const()[name = tensor("input_495_pad_type_0"), val = tensor("valid")]; + tensor input_495_strides_0 = const()[name = tensor("input_495_strides_0"), val = tensor([1])]; + tensor input_495_pad_0 = const()[name = tensor("input_495_pad_0"), val = tensor([0, 0])]; + tensor input_495_dilations_0 = const()[name = tensor("input_495_dilations_0"), val = tensor([1])]; + tensor input_495_groups_0 = const()[name = tensor("input_495_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd9_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd9_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3691008)))]; + tensor net_xvector_block2_tdnnd9_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd9_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3695168)))]; + tensor 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("input_495_cast_fp16")]; + tensor m_41_cast_fp16 = sigmoid(x = input_495_cast_fp16)[name = tensor("m_41_cast_fp16")]; + tensor var_1728_cast_fp16 = mul(x = y_41_cast_fp16, y = m_41_cast_fp16)[name = tensor("op_1728_cast_fp16")]; + tensor input_497_interleave_0 = const()[name = tensor("input_497_interleave_0"), val = tensor(false)]; + tensor input_497_cast_fp16 = concat(axis = var_11, interleave = input_497_interleave_0, values = (input_477_cast_fp16, var_1728_cast_fp16))[name = tensor("input_497_cast_fp16")]; + tensor net_xvector_block2_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3695296)))]; + tensor net_xvector_block2_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3696448)))]; + tensor net_xvector_block2_tdnnd10_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd10_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3697600)))]; + tensor net_xvector_block2_tdnnd10_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd10_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3698752)))]; + tensor 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("input_499_cast_fp16")]; + tensor input_501_cast_fp16 = relu(x = input_499_cast_fp16)[name = tensor("input_501_cast_fp16")]; + tensor input_503_pad_type_0 = const()[name = tensor("input_503_pad_type_0"), val = tensor("valid")]; + tensor input_503_strides_0 = const()[name = tensor("input_503_strides_0"), val = tensor([1])]; + tensor input_503_pad_0 = const()[name = tensor("input_503_pad_0"), val = tensor([0, 0])]; + tensor input_503_dilations_0 = const()[name = tensor("input_503_dilations_0"), val = tensor([1])]; + tensor input_503_groups_0 = const()[name = tensor("input_503_groups_0"), val = tensor(1)]; + tensor const_280_to_fp16 = const()[name = tensor("const_280_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3699904)))]; + tensor const_281_to_fp16 = const()[name = tensor("const_281_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3839232)))]; + tensor input_505_cast_fp16 = conv(bias = const_281_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_280_to_fp16, x = input_501_cast_fp16)[name = tensor("input_505_cast_fp16")]; + tensor input_507_cast_fp16 = relu(x = input_505_cast_fp16)[name = tensor("input_507_cast_fp16")]; + tensor y_43_pad_type_0 = const()[name = tensor("y_43_pad_type_0"), val = tensor("custom")]; + tensor y_43_pad_0 = const()[name = tensor("y_43_pad_0"), val = tensor([2, 2])]; + tensor y_43_dilations_0 = const()[name = tensor("y_43_dilations_0"), val = tensor([2])]; + tensor y_43_strides_0 = const()[name = tensor("y_43_strides_0"), val = tensor([1])]; + tensor y_43_groups_0 = const()[name = tensor("y_43_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd10_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd10_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3839552)))]; + tensor 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("y_43_cast_fp16")]; + tensor var_1765_axes_0 = const()[name = tensor("op_1765_axes_0"), val = tensor([-1])]; + tensor var_1765_keep_dims_0 = const()[name = tensor("op_1765_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1765_cast_fp16")]; + tensor var_1766 = const()[name = tensor("op_1766"), val = tensor([100])]; + tensor var_1767 = const()[name = tensor("op_1767"), val = tensor([100])]; + tensor seg_85_pad_type_0 = const()[name = tensor("seg_85_pad_type_0"), val = tensor("custom")]; + tensor seg_85_pad_0 = const()[name = tensor("seg_85_pad_0"), val = tensor([0, 0])]; + tensor seg_85_exclude_padding_from_average_0 = const()[name = tensor("seg_85_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_85_ceil_mode_0 = const()[name = tensor("seg_85_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_85_cast_fp16")]; + tensor var_1773_axes_0 = const()[name = tensor("op_1773_axes_0"), val = tensor([-1])]; + tensor var_1773_cast_fp16 = expand_dims(axes = var_1773_axes_0, x = seg_85_cast_fp16)[name = tensor("op_1773_cast_fp16")]; + tensor var_1775_reps_0 = const()[name = tensor("op_1775_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1775_cast_fp16 = tile(reps = var_1775_reps_0, x = var_1773_cast_fp16)[name = tensor("op_1775_cast_fp16")]; + tensor var_1776 = const()[name = tensor("op_1776"), val = tensor([1, 128, -1])]; + tensor seg_87_cast_fp16 = reshape(shape = var_1776, x = var_1775_cast_fp16)[name = tensor("seg_87_cast_fp16")]; + tensor input_509_cast_fp16 = add(x = var_1765_cast_fp16, y = seg_87_cast_fp16)[name = tensor("input_509_cast_fp16")]; + tensor input_511_pad_type_0 = const()[name = tensor("input_511_pad_type_0"), val = tensor("valid")]; + tensor input_511_strides_0 = const()[name = tensor("input_511_strides_0"), val = tensor([1])]; + tensor input_511_pad_0 = const()[name = tensor("input_511_pad_0"), val = tensor([0, 0])]; + tensor input_511_dilations_0 = const()[name = tensor("input_511_dilations_0"), val = tensor([1])]; + tensor input_511_groups_0 = const()[name = tensor("input_511_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd10_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd10_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3864192)))]; + tensor net_xvector_block2_tdnnd10_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd10_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3880640)))]; + tensor 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("input_511_cast_fp16")]; + tensor input_513_cast_fp16 = relu(x = input_511_cast_fp16)[name = tensor("input_513_cast_fp16")]; + tensor input_515_pad_type_0 = const()[name = tensor("input_515_pad_type_0"), val = tensor("valid")]; + tensor input_515_strides_0 = const()[name = tensor("input_515_strides_0"), val = tensor([1])]; + tensor input_515_pad_0 = const()[name = tensor("input_515_pad_0"), val = tensor([0, 0])]; + tensor input_515_dilations_0 = const()[name = tensor("input_515_dilations_0"), val = tensor([1])]; + tensor input_515_groups_0 = const()[name = tensor("input_515_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd10_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd10_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3880832)))]; + tensor net_xvector_block2_tdnnd10_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd10_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3884992)))]; + tensor 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("input_515_cast_fp16")]; + tensor m_43_cast_fp16 = sigmoid(x = input_515_cast_fp16)[name = tensor("m_43_cast_fp16")]; + tensor var_1797_cast_fp16 = mul(x = y_43_cast_fp16, y = m_43_cast_fp16)[name = tensor("op_1797_cast_fp16")]; + tensor input_517_interleave_0 = const()[name = tensor("input_517_interleave_0"), val = tensor(false)]; + tensor input_517_cast_fp16 = concat(axis = var_11, interleave = input_517_interleave_0, values = (input_497_cast_fp16, var_1797_cast_fp16))[name = tensor("input_517_cast_fp16")]; + tensor net_xvector_block2_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3885120)))]; + tensor net_xvector_block2_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3886336)))]; + tensor net_xvector_block2_tdnnd11_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd11_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3887552)))]; + tensor net_xvector_block2_tdnnd11_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd11_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3888768)))]; + tensor 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("input_519_cast_fp16")]; + tensor input_521_cast_fp16 = relu(x = input_519_cast_fp16)[name = tensor("input_521_cast_fp16")]; + tensor input_523_pad_type_0 = const()[name = tensor("input_523_pad_type_0"), val = tensor("valid")]; + tensor input_523_strides_0 = const()[name = tensor("input_523_strides_0"), val = tensor([1])]; + tensor input_523_pad_0 = const()[name = tensor("input_523_pad_0"), val = tensor([0, 0])]; + tensor input_523_dilations_0 = const()[name = tensor("input_523_dilations_0"), val = tensor([1])]; + tensor input_523_groups_0 = const()[name = tensor("input_523_groups_0"), val = tensor(1)]; + tensor const_282_to_fp16 = const()[name = tensor("const_282_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3889984)))]; + tensor const_283_to_fp16 = const()[name = tensor("const_283_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4037504)))]; + tensor input_525_cast_fp16 = conv(bias = const_283_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_282_to_fp16, x = input_521_cast_fp16)[name = tensor("input_525_cast_fp16")]; + tensor input_527_cast_fp16 = relu(x = input_525_cast_fp16)[name = tensor("input_527_cast_fp16")]; + tensor y_45_pad_type_0 = const()[name = tensor("y_45_pad_type_0"), val = tensor("custom")]; + tensor y_45_pad_0 = const()[name = tensor("y_45_pad_0"), val = tensor([2, 2])]; + tensor y_45_dilations_0 = const()[name = tensor("y_45_dilations_0"), val = tensor([2])]; + tensor y_45_strides_0 = const()[name = tensor("y_45_strides_0"), val = tensor([1])]; + tensor y_45_groups_0 = const()[name = tensor("y_45_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd11_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd11_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4037824)))]; + tensor 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("y_45_cast_fp16")]; + tensor var_1834_axes_0 = const()[name = tensor("op_1834_axes_0"), val = tensor([-1])]; + tensor var_1834_keep_dims_0 = const()[name = tensor("op_1834_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1834_cast_fp16")]; + tensor var_1835 = const()[name = tensor("op_1835"), val = tensor([100])]; + tensor var_1836 = const()[name = tensor("op_1836"), val = tensor([100])]; + tensor seg_89_pad_type_0 = const()[name = tensor("seg_89_pad_type_0"), val = tensor("custom")]; + tensor seg_89_pad_0 = const()[name = tensor("seg_89_pad_0"), val = tensor([0, 0])]; + tensor seg_89_exclude_padding_from_average_0 = const()[name = tensor("seg_89_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_89_ceil_mode_0 = const()[name = tensor("seg_89_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_89_cast_fp16")]; + tensor var_1842_axes_0 = const()[name = tensor("op_1842_axes_0"), val = tensor([-1])]; + tensor var_1842_cast_fp16 = expand_dims(axes = var_1842_axes_0, x = seg_89_cast_fp16)[name = tensor("op_1842_cast_fp16")]; + tensor var_1844_reps_0 = const()[name = tensor("op_1844_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1844_cast_fp16 = tile(reps = var_1844_reps_0, x = var_1842_cast_fp16)[name = tensor("op_1844_cast_fp16")]; + tensor var_1845 = const()[name = tensor("op_1845"), val = tensor([1, 128, -1])]; + tensor seg_91_cast_fp16 = reshape(shape = var_1845, x = var_1844_cast_fp16)[name = tensor("seg_91_cast_fp16")]; + tensor input_529_cast_fp16 = add(x = var_1834_cast_fp16, y = seg_91_cast_fp16)[name = tensor("input_529_cast_fp16")]; + tensor input_531_pad_type_0 = const()[name = tensor("input_531_pad_type_0"), val = tensor("valid")]; + tensor input_531_strides_0 = const()[name = tensor("input_531_strides_0"), val = tensor([1])]; + tensor input_531_pad_0 = const()[name = tensor("input_531_pad_0"), val = tensor([0, 0])]; + tensor input_531_dilations_0 = const()[name = tensor("input_531_dilations_0"), val = tensor([1])]; + tensor input_531_groups_0 = const()[name = tensor("input_531_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd11_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd11_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4062464)))]; + tensor net_xvector_block2_tdnnd11_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd11_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4078912)))]; + tensor 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("input_531_cast_fp16")]; + tensor input_533_cast_fp16 = relu(x = input_531_cast_fp16)[name = tensor("input_533_cast_fp16")]; + tensor input_535_pad_type_0 = const()[name = tensor("input_535_pad_type_0"), val = tensor("valid")]; + tensor input_535_strides_0 = const()[name = tensor("input_535_strides_0"), val = tensor([1])]; + tensor input_535_pad_0 = const()[name = tensor("input_535_pad_0"), val = tensor([0, 0])]; + tensor input_535_dilations_0 = const()[name = tensor("input_535_dilations_0"), val = tensor([1])]; + tensor input_535_groups_0 = const()[name = tensor("input_535_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd11_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd11_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4079104)))]; + tensor net_xvector_block2_tdnnd11_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd11_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4083264)))]; + tensor 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("input_535_cast_fp16")]; + tensor m_45_cast_fp16 = sigmoid(x = input_535_cast_fp16)[name = tensor("m_45_cast_fp16")]; + tensor var_1866_cast_fp16 = mul(x = y_45_cast_fp16, y = m_45_cast_fp16)[name = tensor("op_1866_cast_fp16")]; + tensor input_537_interleave_0 = const()[name = tensor("input_537_interleave_0"), val = tensor(false)]; + tensor input_537_cast_fp16 = concat(axis = var_11, interleave = input_537_interleave_0, values = (input_517_cast_fp16, var_1866_cast_fp16))[name = tensor("input_537_cast_fp16")]; + tensor net_xvector_block2_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4083392)))]; + tensor net_xvector_block2_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4084672)))]; + tensor net_xvector_block2_tdnnd12_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd12_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4085952)))]; + tensor net_xvector_block2_tdnnd12_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd12_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4087232)))]; + tensor 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("input_539_cast_fp16")]; + tensor input_541_cast_fp16 = relu(x = input_539_cast_fp16)[name = tensor("input_541_cast_fp16")]; + tensor input_543_pad_type_0 = const()[name = tensor("input_543_pad_type_0"), val = tensor("valid")]; + tensor input_543_strides_0 = const()[name = tensor("input_543_strides_0"), val = tensor([1])]; + tensor input_543_pad_0 = const()[name = tensor("input_543_pad_0"), val = tensor([0, 0])]; + tensor input_543_dilations_0 = const()[name = tensor("input_543_dilations_0"), val = tensor([1])]; + tensor input_543_groups_0 = const()[name = tensor("input_543_groups_0"), val = tensor(1)]; + tensor const_284_to_fp16 = const()[name = tensor("const_284_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4088512)))]; + tensor const_285_to_fp16 = const()[name = tensor("const_285_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4244224)))]; + tensor input_545_cast_fp16 = conv(bias = const_285_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_284_to_fp16, x = input_541_cast_fp16)[name = tensor("input_545_cast_fp16")]; + tensor input_547_cast_fp16 = relu(x = input_545_cast_fp16)[name = tensor("input_547_cast_fp16")]; + tensor y_47_pad_type_0 = const()[name = tensor("y_47_pad_type_0"), val = tensor("custom")]; + tensor y_47_pad_0 = const()[name = tensor("y_47_pad_0"), val = tensor([2, 2])]; + tensor y_47_dilations_0 = const()[name = tensor("y_47_dilations_0"), val = tensor([2])]; + tensor y_47_strides_0 = const()[name = tensor("y_47_strides_0"), val = tensor([1])]; + tensor y_47_groups_0 = const()[name = tensor("y_47_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd12_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd12_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4244544)))]; + tensor 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("y_47_cast_fp16")]; + tensor var_1903_axes_0 = const()[name = tensor("op_1903_axes_0"), val = tensor([-1])]; + tensor var_1903_keep_dims_0 = const()[name = tensor("op_1903_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1903_cast_fp16")]; + tensor var_1904 = const()[name = tensor("op_1904"), val = tensor([100])]; + tensor var_1905 = const()[name = tensor("op_1905"), val = tensor([100])]; + tensor seg_93_pad_type_0 = const()[name = tensor("seg_93_pad_type_0"), val = tensor("custom")]; + tensor seg_93_pad_0 = const()[name = tensor("seg_93_pad_0"), val = tensor([0, 0])]; + tensor seg_93_exclude_padding_from_average_0 = const()[name = tensor("seg_93_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_93_ceil_mode_0 = const()[name = tensor("seg_93_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_93_cast_fp16")]; + tensor var_1911_axes_0 = const()[name = tensor("op_1911_axes_0"), val = tensor([-1])]; + tensor var_1911_cast_fp16 = expand_dims(axes = var_1911_axes_0, x = seg_93_cast_fp16)[name = tensor("op_1911_cast_fp16")]; + tensor var_1913_reps_0 = const()[name = tensor("op_1913_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1913_cast_fp16 = tile(reps = var_1913_reps_0, x = var_1911_cast_fp16)[name = tensor("op_1913_cast_fp16")]; + tensor var_1914 = const()[name = tensor("op_1914"), val = tensor([1, 128, -1])]; + tensor seg_95_cast_fp16 = reshape(shape = var_1914, x = var_1913_cast_fp16)[name = tensor("seg_95_cast_fp16")]; + tensor input_549_cast_fp16 = add(x = var_1903_cast_fp16, y = seg_95_cast_fp16)[name = tensor("input_549_cast_fp16")]; + tensor input_551_pad_type_0 = const()[name = tensor("input_551_pad_type_0"), val = tensor("valid")]; + tensor input_551_strides_0 = const()[name = tensor("input_551_strides_0"), val = tensor([1])]; + tensor input_551_pad_0 = const()[name = tensor("input_551_pad_0"), val = tensor([0, 0])]; + tensor input_551_dilations_0 = const()[name = tensor("input_551_dilations_0"), val = tensor([1])]; + tensor input_551_groups_0 = const()[name = tensor("input_551_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd12_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd12_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4269184)))]; + tensor net_xvector_block2_tdnnd12_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd12_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4285632)))]; + tensor 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("input_551_cast_fp16")]; + tensor input_553_cast_fp16 = relu(x = input_551_cast_fp16)[name = tensor("input_553_cast_fp16")]; + tensor input_555_pad_type_0 = const()[name = tensor("input_555_pad_type_0"), val = tensor("valid")]; + tensor input_555_strides_0 = const()[name = tensor("input_555_strides_0"), val = tensor([1])]; + tensor input_555_pad_0 = const()[name = tensor("input_555_pad_0"), val = tensor([0, 0])]; + tensor input_555_dilations_0 = const()[name = tensor("input_555_dilations_0"), val = tensor([1])]; + tensor input_555_groups_0 = const()[name = tensor("input_555_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd12_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd12_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4285824)))]; + tensor net_xvector_block2_tdnnd12_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd12_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4289984)))]; + tensor 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("input_555_cast_fp16")]; + tensor m_47_cast_fp16 = sigmoid(x = input_555_cast_fp16)[name = tensor("m_47_cast_fp16")]; + tensor var_1935_cast_fp16 = mul(x = y_47_cast_fp16, y = m_47_cast_fp16)[name = tensor("op_1935_cast_fp16")]; + tensor input_557_interleave_0 = const()[name = tensor("input_557_interleave_0"), val = tensor(false)]; + tensor input_557_cast_fp16 = concat(axis = var_11, interleave = input_557_interleave_0, values = (input_537_cast_fp16, var_1935_cast_fp16))[name = tensor("input_557_cast_fp16")]; + tensor net_xvector_block2_tdnnd13_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd13_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4290112)))]; + tensor net_xvector_block2_tdnnd13_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd13_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4291456)))]; + tensor net_xvector_block2_tdnnd13_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd13_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4292800)))]; + tensor net_xvector_block2_tdnnd13_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd13_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4294144)))]; + tensor 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("input_559_cast_fp16")]; + tensor input_561_cast_fp16 = relu(x = input_559_cast_fp16)[name = tensor("input_561_cast_fp16")]; + tensor input_563_pad_type_0 = const()[name = tensor("input_563_pad_type_0"), val = tensor("valid")]; + tensor input_563_strides_0 = const()[name = tensor("input_563_strides_0"), val = tensor([1])]; + tensor input_563_pad_0 = const()[name = tensor("input_563_pad_0"), val = tensor([0, 0])]; + tensor input_563_dilations_0 = const()[name = tensor("input_563_dilations_0"), val = tensor([1])]; + tensor input_563_groups_0 = const()[name = tensor("input_563_groups_0"), val = tensor(1)]; + tensor const_286_to_fp16 = const()[name = tensor("const_286_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4295488)))]; + tensor const_287_to_fp16 = const()[name = tensor("const_287_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4459392)))]; + tensor input_565_cast_fp16 = conv(bias = const_287_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_286_to_fp16, x = input_561_cast_fp16)[name = tensor("input_565_cast_fp16")]; + tensor input_567_cast_fp16 = relu(x = input_565_cast_fp16)[name = tensor("input_567_cast_fp16")]; + tensor y_49_pad_type_0 = const()[name = tensor("y_49_pad_type_0"), val = tensor("custom")]; + tensor y_49_pad_0 = const()[name = tensor("y_49_pad_0"), val = tensor([2, 2])]; + tensor y_49_dilations_0 = const()[name = tensor("y_49_dilations_0"), val = tensor([2])]; + tensor y_49_strides_0 = const()[name = tensor("y_49_strides_0"), val = tensor([1])]; + tensor y_49_groups_0 = const()[name = tensor("y_49_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd13_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd13_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4459712)))]; + tensor 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("y_49_cast_fp16")]; + tensor var_1972_axes_0 = const()[name = tensor("op_1972_axes_0"), val = tensor([-1])]; + tensor var_1972_keep_dims_0 = const()[name = tensor("op_1972_keep_dims_0"), val = tensor(true)]; + tensor 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("op_1972_cast_fp16")]; + tensor var_1973 = const()[name = tensor("op_1973"), val = tensor([100])]; + tensor var_1974 = const()[name = tensor("op_1974"), val = tensor([100])]; + tensor seg_97_pad_type_0 = const()[name = tensor("seg_97_pad_type_0"), val = tensor("custom")]; + tensor seg_97_pad_0 = const()[name = tensor("seg_97_pad_0"), val = tensor([0, 0])]; + tensor seg_97_exclude_padding_from_average_0 = const()[name = tensor("seg_97_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_97_ceil_mode_0 = const()[name = tensor("seg_97_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_97_cast_fp16")]; + tensor var_1980_axes_0 = const()[name = tensor("op_1980_axes_0"), val = tensor([-1])]; + tensor var_1980_cast_fp16 = expand_dims(axes = var_1980_axes_0, x = seg_97_cast_fp16)[name = tensor("op_1980_cast_fp16")]; + tensor var_1982_reps_0 = const()[name = tensor("op_1982_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_1982_cast_fp16 = tile(reps = var_1982_reps_0, x = var_1980_cast_fp16)[name = tensor("op_1982_cast_fp16")]; + tensor var_1983 = const()[name = tensor("op_1983"), val = tensor([1, 128, -1])]; + tensor seg_99_cast_fp16 = reshape(shape = var_1983, x = var_1982_cast_fp16)[name = tensor("seg_99_cast_fp16")]; + tensor input_569_cast_fp16 = add(x = var_1972_cast_fp16, y = seg_99_cast_fp16)[name = tensor("input_569_cast_fp16")]; + tensor input_571_pad_type_0 = const()[name = tensor("input_571_pad_type_0"), val = tensor("valid")]; + tensor input_571_strides_0 = const()[name = tensor("input_571_strides_0"), val = tensor([1])]; + tensor input_571_pad_0 = const()[name = tensor("input_571_pad_0"), val = tensor([0, 0])]; + tensor input_571_dilations_0 = const()[name = tensor("input_571_dilations_0"), val = tensor([1])]; + tensor input_571_groups_0 = const()[name = tensor("input_571_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd13_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd13_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4484352)))]; + tensor net_xvector_block2_tdnnd13_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd13_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4500800)))]; + tensor 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("input_571_cast_fp16")]; + tensor input_573_cast_fp16 = relu(x = input_571_cast_fp16)[name = tensor("input_573_cast_fp16")]; + tensor input_575_pad_type_0 = const()[name = tensor("input_575_pad_type_0"), val = tensor("valid")]; + tensor input_575_strides_0 = const()[name = tensor("input_575_strides_0"), val = tensor([1])]; + tensor input_575_pad_0 = const()[name = tensor("input_575_pad_0"), val = tensor([0, 0])]; + tensor input_575_dilations_0 = const()[name = tensor("input_575_dilations_0"), val = tensor([1])]; + tensor input_575_groups_0 = const()[name = tensor("input_575_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd13_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd13_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4500992)))]; + tensor net_xvector_block2_tdnnd13_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd13_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4505152)))]; + tensor 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("input_575_cast_fp16")]; + tensor m_49_cast_fp16 = sigmoid(x = input_575_cast_fp16)[name = tensor("m_49_cast_fp16")]; + tensor var_2004_cast_fp16 = mul(x = y_49_cast_fp16, y = m_49_cast_fp16)[name = tensor("op_2004_cast_fp16")]; + tensor input_577_interleave_0 = const()[name = tensor("input_577_interleave_0"), val = tensor(false)]; + tensor input_577_cast_fp16 = concat(axis = var_11, interleave = input_577_interleave_0, values = (input_557_cast_fp16, var_2004_cast_fp16))[name = tensor("input_577_cast_fp16")]; + tensor net_xvector_block2_tdnnd14_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd14_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4505280)))]; + tensor net_xvector_block2_tdnnd14_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd14_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4506688)))]; + tensor net_xvector_block2_tdnnd14_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd14_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4508096)))]; + tensor net_xvector_block2_tdnnd14_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd14_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4509504)))]; + tensor 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("input_579_cast_fp16")]; + tensor input_581_cast_fp16 = relu(x = input_579_cast_fp16)[name = tensor("input_581_cast_fp16")]; + tensor input_583_pad_type_0 = const()[name = tensor("input_583_pad_type_0"), val = tensor("valid")]; + tensor input_583_strides_0 = const()[name = tensor("input_583_strides_0"), val = tensor([1])]; + tensor input_583_pad_0 = const()[name = tensor("input_583_pad_0"), val = tensor([0, 0])]; + tensor input_583_dilations_0 = const()[name = tensor("input_583_dilations_0"), val = tensor([1])]; + tensor input_583_groups_0 = const()[name = tensor("input_583_groups_0"), val = tensor(1)]; + tensor const_288_to_fp16 = const()[name = tensor("const_288_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4510912)))]; + tensor const_289_to_fp16 = const()[name = tensor("const_289_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4683008)))]; + tensor input_585_cast_fp16 = conv(bias = const_289_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_288_to_fp16, x = input_581_cast_fp16)[name = tensor("input_585_cast_fp16")]; + tensor input_587_cast_fp16 = relu(x = input_585_cast_fp16)[name = tensor("input_587_cast_fp16")]; + tensor y_51_pad_type_0 = const()[name = tensor("y_51_pad_type_0"), val = tensor("custom")]; + tensor y_51_pad_0 = const()[name = tensor("y_51_pad_0"), val = tensor([2, 2])]; + tensor y_51_dilations_0 = const()[name = tensor("y_51_dilations_0"), val = tensor([2])]; + tensor y_51_strides_0 = const()[name = tensor("y_51_strides_0"), val = tensor([1])]; + tensor y_51_groups_0 = const()[name = tensor("y_51_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd14_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd14_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4683328)))]; + tensor 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("y_51_cast_fp16")]; + tensor var_2041_axes_0 = const()[name = tensor("op_2041_axes_0"), val = tensor([-1])]; + tensor var_2041_keep_dims_0 = const()[name = tensor("op_2041_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2041_cast_fp16")]; + tensor var_2042 = const()[name = tensor("op_2042"), val = tensor([100])]; + tensor var_2043 = const()[name = tensor("op_2043"), val = tensor([100])]; + tensor seg_101_pad_type_0 = const()[name = tensor("seg_101_pad_type_0"), val = tensor("custom")]; + tensor seg_101_pad_0 = const()[name = tensor("seg_101_pad_0"), val = tensor([0, 0])]; + tensor seg_101_exclude_padding_from_average_0 = const()[name = tensor("seg_101_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_101_ceil_mode_0 = const()[name = tensor("seg_101_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_101_cast_fp16")]; + tensor var_2049_axes_0 = const()[name = tensor("op_2049_axes_0"), val = tensor([-1])]; + tensor var_2049_cast_fp16 = expand_dims(axes = var_2049_axes_0, x = seg_101_cast_fp16)[name = tensor("op_2049_cast_fp16")]; + tensor var_2051_reps_0 = const()[name = tensor("op_2051_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2051_cast_fp16 = tile(reps = var_2051_reps_0, x = var_2049_cast_fp16)[name = tensor("op_2051_cast_fp16")]; + tensor var_2052 = const()[name = tensor("op_2052"), val = tensor([1, 128, -1])]; + tensor seg_103_cast_fp16 = reshape(shape = var_2052, x = var_2051_cast_fp16)[name = tensor("seg_103_cast_fp16")]; + tensor input_589_cast_fp16 = add(x = var_2041_cast_fp16, y = seg_103_cast_fp16)[name = tensor("input_589_cast_fp16")]; + tensor input_591_pad_type_0 = const()[name = tensor("input_591_pad_type_0"), val = tensor("valid")]; + tensor input_591_strides_0 = const()[name = tensor("input_591_strides_0"), val = tensor([1])]; + tensor input_591_pad_0 = const()[name = tensor("input_591_pad_0"), val = tensor([0, 0])]; + tensor input_591_dilations_0 = const()[name = tensor("input_591_dilations_0"), val = tensor([1])]; + tensor input_591_groups_0 = const()[name = tensor("input_591_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd14_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd14_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4707968)))]; + tensor net_xvector_block2_tdnnd14_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd14_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4724416)))]; + tensor 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("input_591_cast_fp16")]; + tensor input_593_cast_fp16 = relu(x = input_591_cast_fp16)[name = tensor("input_593_cast_fp16")]; + tensor input_595_pad_type_0 = const()[name = tensor("input_595_pad_type_0"), val = tensor("valid")]; + tensor input_595_strides_0 = const()[name = tensor("input_595_strides_0"), val = tensor([1])]; + tensor input_595_pad_0 = const()[name = tensor("input_595_pad_0"), val = tensor([0, 0])]; + tensor input_595_dilations_0 = const()[name = tensor("input_595_dilations_0"), val = tensor([1])]; + tensor input_595_groups_0 = const()[name = tensor("input_595_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd14_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd14_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4724608)))]; + tensor net_xvector_block2_tdnnd14_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd14_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4728768)))]; + tensor 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("input_595_cast_fp16")]; + tensor m_51_cast_fp16 = sigmoid(x = input_595_cast_fp16)[name = tensor("m_51_cast_fp16")]; + tensor var_2073_cast_fp16 = mul(x = y_51_cast_fp16, y = m_51_cast_fp16)[name = tensor("op_2073_cast_fp16")]; + tensor input_597_interleave_0 = const()[name = tensor("input_597_interleave_0"), val = tensor(false)]; + tensor input_597_cast_fp16 = concat(axis = var_11, interleave = input_597_interleave_0, values = (input_577_cast_fp16, var_2073_cast_fp16))[name = tensor("input_597_cast_fp16")]; + tensor net_xvector_block2_tdnnd15_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd15_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4728896)))]; + tensor net_xvector_block2_tdnnd15_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd15_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4730368)))]; + tensor net_xvector_block2_tdnnd15_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd15_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4731840)))]; + tensor net_xvector_block2_tdnnd15_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd15_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4733312)))]; + tensor 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("input_599_cast_fp16")]; + tensor input_601_cast_fp16 = relu(x = input_599_cast_fp16)[name = tensor("input_601_cast_fp16")]; + tensor input_603_pad_type_0 = const()[name = tensor("input_603_pad_type_0"), val = tensor("valid")]; + tensor input_603_strides_0 = const()[name = tensor("input_603_strides_0"), val = tensor([1])]; + tensor input_603_pad_0 = const()[name = tensor("input_603_pad_0"), val = tensor([0, 0])]; + tensor input_603_dilations_0 = const()[name = tensor("input_603_dilations_0"), val = tensor([1])]; + tensor input_603_groups_0 = const()[name = tensor("input_603_groups_0"), val = tensor(1)]; + tensor const_290_to_fp16 = const()[name = tensor("const_290_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4734784)))]; + tensor const_291_to_fp16 = const()[name = tensor("const_291_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4915072)))]; + tensor input_605_cast_fp16 = conv(bias = const_291_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_290_to_fp16, x = input_601_cast_fp16)[name = tensor("input_605_cast_fp16")]; + tensor input_607_cast_fp16 = relu(x = input_605_cast_fp16)[name = tensor("input_607_cast_fp16")]; + tensor y_53_pad_type_0 = const()[name = tensor("y_53_pad_type_0"), val = tensor("custom")]; + tensor y_53_pad_0 = const()[name = tensor("y_53_pad_0"), val = tensor([2, 2])]; + tensor y_53_dilations_0 = const()[name = tensor("y_53_dilations_0"), val = tensor([2])]; + tensor y_53_strides_0 = const()[name = tensor("y_53_strides_0"), val = tensor([1])]; + tensor y_53_groups_0 = const()[name = tensor("y_53_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd15_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd15_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4915392)))]; + tensor 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("y_53_cast_fp16")]; + tensor var_2110_axes_0 = const()[name = tensor("op_2110_axes_0"), val = tensor([-1])]; + tensor var_2110_keep_dims_0 = const()[name = tensor("op_2110_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2110_cast_fp16")]; + tensor var_2111 = const()[name = tensor("op_2111"), val = tensor([100])]; + tensor var_2112 = const()[name = tensor("op_2112"), val = tensor([100])]; + tensor seg_105_pad_type_0 = const()[name = tensor("seg_105_pad_type_0"), val = tensor("custom")]; + tensor seg_105_pad_0 = const()[name = tensor("seg_105_pad_0"), val = tensor([0, 0])]; + tensor seg_105_exclude_padding_from_average_0 = const()[name = tensor("seg_105_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_105_ceil_mode_0 = const()[name = tensor("seg_105_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_105_cast_fp16")]; + tensor var_2118_axes_0 = const()[name = tensor("op_2118_axes_0"), val = tensor([-1])]; + tensor var_2118_cast_fp16 = expand_dims(axes = var_2118_axes_0, x = seg_105_cast_fp16)[name = tensor("op_2118_cast_fp16")]; + tensor var_2120_reps_0 = const()[name = tensor("op_2120_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2120_cast_fp16 = tile(reps = var_2120_reps_0, x = var_2118_cast_fp16)[name = tensor("op_2120_cast_fp16")]; + tensor var_2121 = const()[name = tensor("op_2121"), val = tensor([1, 128, -1])]; + tensor seg_107_cast_fp16 = reshape(shape = var_2121, x = var_2120_cast_fp16)[name = tensor("seg_107_cast_fp16")]; + tensor input_609_cast_fp16 = add(x = var_2110_cast_fp16, y = seg_107_cast_fp16)[name = tensor("input_609_cast_fp16")]; + tensor input_611_pad_type_0 = const()[name = tensor("input_611_pad_type_0"), val = tensor("valid")]; + tensor input_611_strides_0 = const()[name = tensor("input_611_strides_0"), val = tensor([1])]; + tensor input_611_pad_0 = const()[name = tensor("input_611_pad_0"), val = tensor([0, 0])]; + tensor input_611_dilations_0 = const()[name = tensor("input_611_dilations_0"), val = tensor([1])]; + tensor input_611_groups_0 = const()[name = tensor("input_611_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd15_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd15_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4940032)))]; + tensor net_xvector_block2_tdnnd15_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd15_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4956480)))]; + tensor 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("input_611_cast_fp16")]; + tensor input_613_cast_fp16 = relu(x = input_611_cast_fp16)[name = tensor("input_613_cast_fp16")]; + tensor input_615_pad_type_0 = const()[name = tensor("input_615_pad_type_0"), val = tensor("valid")]; + tensor input_615_strides_0 = const()[name = tensor("input_615_strides_0"), val = tensor([1])]; + tensor input_615_pad_0 = const()[name = tensor("input_615_pad_0"), val = tensor([0, 0])]; + tensor input_615_dilations_0 = const()[name = tensor("input_615_dilations_0"), val = tensor([1])]; + tensor input_615_groups_0 = const()[name = tensor("input_615_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd15_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd15_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4956672)))]; + tensor net_xvector_block2_tdnnd15_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd15_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4960832)))]; + tensor 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("input_615_cast_fp16")]; + tensor m_53_cast_fp16 = sigmoid(x = input_615_cast_fp16)[name = tensor("m_53_cast_fp16")]; + tensor var_2142_cast_fp16 = mul(x = y_53_cast_fp16, y = m_53_cast_fp16)[name = tensor("op_2142_cast_fp16")]; + tensor input_617_interleave_0 = const()[name = tensor("input_617_interleave_0"), val = tensor(false)]; + tensor input_617_cast_fp16 = concat(axis = var_11, interleave = input_617_interleave_0, values = (input_597_cast_fp16, var_2142_cast_fp16))[name = tensor("input_617_cast_fp16")]; + tensor net_xvector_block2_tdnnd16_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd16_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4960960)))]; + tensor net_xvector_block2_tdnnd16_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd16_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4962496)))]; + tensor net_xvector_block2_tdnnd16_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd16_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4964032)))]; + tensor net_xvector_block2_tdnnd16_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd16_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4965568)))]; + tensor 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("input_619_cast_fp16")]; + tensor input_621_cast_fp16 = relu(x = input_619_cast_fp16)[name = tensor("input_621_cast_fp16")]; + tensor input_623_pad_type_0 = const()[name = tensor("input_623_pad_type_0"), val = tensor("valid")]; + tensor input_623_strides_0 = const()[name = tensor("input_623_strides_0"), val = tensor([1])]; + tensor input_623_pad_0 = const()[name = tensor("input_623_pad_0"), val = tensor([0, 0])]; + tensor input_623_dilations_0 = const()[name = tensor("input_623_dilations_0"), val = tensor([1])]; + tensor input_623_groups_0 = const()[name = tensor("input_623_groups_0"), val = tensor(1)]; + tensor const_292_to_fp16 = const()[name = tensor("const_292_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4967104)))]; + tensor const_293_to_fp16 = const()[name = tensor("const_293_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5155584)))]; + tensor input_625_cast_fp16 = conv(bias = const_293_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_292_to_fp16, x = input_621_cast_fp16)[name = tensor("input_625_cast_fp16")]; + tensor input_627_cast_fp16 = relu(x = input_625_cast_fp16)[name = tensor("input_627_cast_fp16")]; + tensor y_55_pad_type_0 = const()[name = tensor("y_55_pad_type_0"), val = tensor("custom")]; + tensor y_55_pad_0 = const()[name = tensor("y_55_pad_0"), val = tensor([2, 2])]; + tensor y_55_dilations_0 = const()[name = tensor("y_55_dilations_0"), val = tensor([2])]; + tensor y_55_strides_0 = const()[name = tensor("y_55_strides_0"), val = tensor([1])]; + tensor y_55_groups_0 = const()[name = tensor("y_55_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd16_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd16_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5155904)))]; + tensor 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("y_55_cast_fp16")]; + tensor var_2179_axes_0 = const()[name = tensor("op_2179_axes_0"), val = tensor([-1])]; + tensor var_2179_keep_dims_0 = const()[name = tensor("op_2179_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2179_cast_fp16")]; + tensor var_2180 = const()[name = tensor("op_2180"), val = tensor([100])]; + tensor var_2181 = const()[name = tensor("op_2181"), val = tensor([100])]; + tensor seg_109_pad_type_0 = const()[name = tensor("seg_109_pad_type_0"), val = tensor("custom")]; + tensor seg_109_pad_0 = const()[name = tensor("seg_109_pad_0"), val = tensor([0, 0])]; + tensor seg_109_exclude_padding_from_average_0 = const()[name = tensor("seg_109_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_109_ceil_mode_0 = const()[name = tensor("seg_109_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_109_cast_fp16")]; + tensor var_2187_axes_0 = const()[name = tensor("op_2187_axes_0"), val = tensor([-1])]; + tensor var_2187_cast_fp16 = expand_dims(axes = var_2187_axes_0, x = seg_109_cast_fp16)[name = tensor("op_2187_cast_fp16")]; + tensor var_2189_reps_0 = const()[name = tensor("op_2189_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2189_cast_fp16 = tile(reps = var_2189_reps_0, x = var_2187_cast_fp16)[name = tensor("op_2189_cast_fp16")]; + tensor var_2190 = const()[name = tensor("op_2190"), val = tensor([1, 128, -1])]; + tensor seg_111_cast_fp16 = reshape(shape = var_2190, x = var_2189_cast_fp16)[name = tensor("seg_111_cast_fp16")]; + tensor input_629_cast_fp16 = add(x = var_2179_cast_fp16, y = seg_111_cast_fp16)[name = tensor("input_629_cast_fp16")]; + tensor input_631_pad_type_0 = const()[name = tensor("input_631_pad_type_0"), val = tensor("valid")]; + tensor input_631_strides_0 = const()[name = tensor("input_631_strides_0"), val = tensor([1])]; + tensor input_631_pad_0 = const()[name = tensor("input_631_pad_0"), val = tensor([0, 0])]; + tensor input_631_dilations_0 = const()[name = tensor("input_631_dilations_0"), val = tensor([1])]; + tensor input_631_groups_0 = const()[name = tensor("input_631_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd16_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd16_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5180544)))]; + tensor net_xvector_block2_tdnnd16_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd16_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5196992)))]; + tensor 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("input_631_cast_fp16")]; + tensor input_633_cast_fp16 = relu(x = input_631_cast_fp16)[name = tensor("input_633_cast_fp16")]; + tensor input_635_pad_type_0 = const()[name = tensor("input_635_pad_type_0"), val = tensor("valid")]; + tensor input_635_strides_0 = const()[name = tensor("input_635_strides_0"), val = tensor([1])]; + tensor input_635_pad_0 = const()[name = tensor("input_635_pad_0"), val = tensor([0, 0])]; + tensor input_635_dilations_0 = const()[name = tensor("input_635_dilations_0"), val = tensor([1])]; + tensor input_635_groups_0 = const()[name = tensor("input_635_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd16_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd16_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5197184)))]; + tensor net_xvector_block2_tdnnd16_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd16_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5201344)))]; + tensor 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("input_635_cast_fp16")]; + tensor m_55_cast_fp16 = sigmoid(x = input_635_cast_fp16)[name = tensor("m_55_cast_fp16")]; + tensor var_2211_cast_fp16 = mul(x = y_55_cast_fp16, y = m_55_cast_fp16)[name = tensor("op_2211_cast_fp16")]; + tensor input_637_interleave_0 = const()[name = tensor("input_637_interleave_0"), val = tensor(false)]; + tensor input_637_cast_fp16 = concat(axis = var_11, interleave = input_637_interleave_0, values = (input_617_cast_fp16, var_2211_cast_fp16))[name = tensor("input_637_cast_fp16")]; + tensor net_xvector_block2_tdnnd17_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd17_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5201472)))]; + tensor net_xvector_block2_tdnnd17_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd17_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5203072)))]; + tensor net_xvector_block2_tdnnd17_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd17_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5204672)))]; + tensor net_xvector_block2_tdnnd17_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd17_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5206272)))]; + tensor 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("input_639_cast_fp16")]; + tensor input_641_cast_fp16 = relu(x = input_639_cast_fp16)[name = tensor("input_641_cast_fp16")]; + tensor input_643_pad_type_0 = const()[name = tensor("input_643_pad_type_0"), val = tensor("valid")]; + tensor input_643_strides_0 = const()[name = tensor("input_643_strides_0"), val = tensor([1])]; + tensor input_643_pad_0 = const()[name = tensor("input_643_pad_0"), val = tensor([0, 0])]; + tensor input_643_dilations_0 = const()[name = tensor("input_643_dilations_0"), val = tensor([1])]; + tensor input_643_groups_0 = const()[name = tensor("input_643_groups_0"), val = tensor(1)]; + tensor const_294_to_fp16 = const()[name = tensor("const_294_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5207872)))]; + tensor const_295_to_fp16 = const()[name = tensor("const_295_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5404544)))]; + tensor input_645_cast_fp16 = conv(bias = const_295_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_294_to_fp16, x = input_641_cast_fp16)[name = tensor("input_645_cast_fp16")]; + tensor input_647_cast_fp16 = relu(x = input_645_cast_fp16)[name = tensor("input_647_cast_fp16")]; + tensor y_57_pad_type_0 = const()[name = tensor("y_57_pad_type_0"), val = tensor("custom")]; + tensor y_57_pad_0 = const()[name = tensor("y_57_pad_0"), val = tensor([2, 2])]; + tensor y_57_dilations_0 = const()[name = tensor("y_57_dilations_0"), val = tensor([2])]; + tensor y_57_strides_0 = const()[name = tensor("y_57_strides_0"), val = tensor([1])]; + tensor y_57_groups_0 = const()[name = tensor("y_57_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd17_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd17_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5404864)))]; + tensor 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("y_57_cast_fp16")]; + tensor var_2248_axes_0 = const()[name = tensor("op_2248_axes_0"), val = tensor([-1])]; + tensor var_2248_keep_dims_0 = const()[name = tensor("op_2248_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2248_cast_fp16")]; + tensor var_2249 = const()[name = tensor("op_2249"), val = tensor([100])]; + tensor var_2250 = const()[name = tensor("op_2250"), val = tensor([100])]; + tensor seg_113_pad_type_0 = const()[name = tensor("seg_113_pad_type_0"), val = tensor("custom")]; + tensor seg_113_pad_0 = const()[name = tensor("seg_113_pad_0"), val = tensor([0, 0])]; + tensor seg_113_exclude_padding_from_average_0 = const()[name = tensor("seg_113_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_113_ceil_mode_0 = const()[name = tensor("seg_113_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_113_cast_fp16")]; + tensor var_2256_axes_0 = const()[name = tensor("op_2256_axes_0"), val = tensor([-1])]; + tensor var_2256_cast_fp16 = expand_dims(axes = var_2256_axes_0, x = seg_113_cast_fp16)[name = tensor("op_2256_cast_fp16")]; + tensor var_2258_reps_0 = const()[name = tensor("op_2258_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2258_cast_fp16 = tile(reps = var_2258_reps_0, x = var_2256_cast_fp16)[name = tensor("op_2258_cast_fp16")]; + tensor var_2259 = const()[name = tensor("op_2259"), val = tensor([1, 128, -1])]; + tensor seg_115_cast_fp16 = reshape(shape = var_2259, x = var_2258_cast_fp16)[name = tensor("seg_115_cast_fp16")]; + tensor input_649_cast_fp16 = add(x = var_2248_cast_fp16, y = seg_115_cast_fp16)[name = tensor("input_649_cast_fp16")]; + tensor input_651_pad_type_0 = const()[name = tensor("input_651_pad_type_0"), val = tensor("valid")]; + tensor input_651_strides_0 = const()[name = tensor("input_651_strides_0"), val = tensor([1])]; + tensor input_651_pad_0 = const()[name = tensor("input_651_pad_0"), val = tensor([0, 0])]; + tensor input_651_dilations_0 = const()[name = tensor("input_651_dilations_0"), val = tensor([1])]; + tensor input_651_groups_0 = const()[name = tensor("input_651_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd17_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd17_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5429504)))]; + tensor net_xvector_block2_tdnnd17_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd17_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5445952)))]; + tensor 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("input_651_cast_fp16")]; + tensor input_653_cast_fp16 = relu(x = input_651_cast_fp16)[name = tensor("input_653_cast_fp16")]; + tensor input_655_pad_type_0 = const()[name = tensor("input_655_pad_type_0"), val = tensor("valid")]; + tensor input_655_strides_0 = const()[name = tensor("input_655_strides_0"), val = tensor([1])]; + tensor input_655_pad_0 = const()[name = tensor("input_655_pad_0"), val = tensor([0, 0])]; + tensor input_655_dilations_0 = const()[name = tensor("input_655_dilations_0"), val = tensor([1])]; + tensor input_655_groups_0 = const()[name = tensor("input_655_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd17_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd17_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5446144)))]; + tensor net_xvector_block2_tdnnd17_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd17_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5450304)))]; + tensor 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("input_655_cast_fp16")]; + tensor m_57_cast_fp16 = sigmoid(x = input_655_cast_fp16)[name = tensor("m_57_cast_fp16")]; + tensor var_2280_cast_fp16 = mul(x = y_57_cast_fp16, y = m_57_cast_fp16)[name = tensor("op_2280_cast_fp16")]; + tensor input_657_interleave_0 = const()[name = tensor("input_657_interleave_0"), val = tensor(false)]; + tensor input_657_cast_fp16 = concat(axis = var_11, interleave = input_657_interleave_0, values = (input_637_cast_fp16, var_2280_cast_fp16))[name = tensor("input_657_cast_fp16")]; + tensor net_xvector_block2_tdnnd18_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd18_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5450432)))]; + tensor net_xvector_block2_tdnnd18_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd18_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5452096)))]; + tensor net_xvector_block2_tdnnd18_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd18_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5453760)))]; + tensor net_xvector_block2_tdnnd18_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd18_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5455424)))]; + tensor 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("input_659_cast_fp16")]; + tensor input_661_cast_fp16 = relu(x = input_659_cast_fp16)[name = tensor("input_661_cast_fp16")]; + tensor input_663_pad_type_0 = const()[name = tensor("input_663_pad_type_0"), val = tensor("valid")]; + tensor input_663_strides_0 = const()[name = tensor("input_663_strides_0"), val = tensor([1])]; + tensor input_663_pad_0 = const()[name = tensor("input_663_pad_0"), val = tensor([0, 0])]; + tensor input_663_dilations_0 = const()[name = tensor("input_663_dilations_0"), val = tensor([1])]; + tensor input_663_groups_0 = const()[name = tensor("input_663_groups_0"), val = tensor(1)]; + tensor const_296_to_fp16 = const()[name = tensor("const_296_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5457088)))]; + tensor const_297_to_fp16 = const()[name = tensor("const_297_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5661952)))]; + tensor input_665_cast_fp16 = conv(bias = const_297_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_296_to_fp16, x = input_661_cast_fp16)[name = tensor("input_665_cast_fp16")]; + tensor input_667_cast_fp16 = relu(x = input_665_cast_fp16)[name = tensor("input_667_cast_fp16")]; + tensor y_59_pad_type_0 = const()[name = tensor("y_59_pad_type_0"), val = tensor("custom")]; + tensor y_59_pad_0 = const()[name = tensor("y_59_pad_0"), val = tensor([2, 2])]; + tensor y_59_dilations_0 = const()[name = tensor("y_59_dilations_0"), val = tensor([2])]; + tensor y_59_strides_0 = const()[name = tensor("y_59_strides_0"), val = tensor([1])]; + tensor y_59_groups_0 = const()[name = tensor("y_59_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd18_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd18_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5662272)))]; + tensor 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("y_59_cast_fp16")]; + tensor var_2317_axes_0 = const()[name = tensor("op_2317_axes_0"), val = tensor([-1])]; + tensor var_2317_keep_dims_0 = const()[name = tensor("op_2317_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2317_cast_fp16")]; + tensor var_2318 = const()[name = tensor("op_2318"), val = tensor([100])]; + tensor var_2319 = const()[name = tensor("op_2319"), val = tensor([100])]; + tensor seg_117_pad_type_0 = const()[name = tensor("seg_117_pad_type_0"), val = tensor("custom")]; + tensor seg_117_pad_0 = const()[name = tensor("seg_117_pad_0"), val = tensor([0, 0])]; + tensor seg_117_exclude_padding_from_average_0 = const()[name = tensor("seg_117_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_117_ceil_mode_0 = const()[name = tensor("seg_117_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_117_cast_fp16")]; + tensor var_2325_axes_0 = const()[name = tensor("op_2325_axes_0"), val = tensor([-1])]; + tensor var_2325_cast_fp16 = expand_dims(axes = var_2325_axes_0, x = seg_117_cast_fp16)[name = tensor("op_2325_cast_fp16")]; + tensor var_2327_reps_0 = const()[name = tensor("op_2327_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2327_cast_fp16 = tile(reps = var_2327_reps_0, x = var_2325_cast_fp16)[name = tensor("op_2327_cast_fp16")]; + tensor var_2328 = const()[name = tensor("op_2328"), val = tensor([1, 128, -1])]; + tensor seg_119_cast_fp16 = reshape(shape = var_2328, x = var_2327_cast_fp16)[name = tensor("seg_119_cast_fp16")]; + tensor input_669_cast_fp16 = add(x = var_2317_cast_fp16, y = seg_119_cast_fp16)[name = tensor("input_669_cast_fp16")]; + tensor input_671_pad_type_0 = const()[name = tensor("input_671_pad_type_0"), val = tensor("valid")]; + tensor input_671_strides_0 = const()[name = tensor("input_671_strides_0"), val = tensor([1])]; + tensor input_671_pad_0 = const()[name = tensor("input_671_pad_0"), val = tensor([0, 0])]; + tensor input_671_dilations_0 = const()[name = tensor("input_671_dilations_0"), val = tensor([1])]; + tensor input_671_groups_0 = const()[name = tensor("input_671_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd18_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd18_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5686912)))]; + tensor net_xvector_block2_tdnnd18_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd18_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5703360)))]; + tensor 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("input_671_cast_fp16")]; + tensor input_673_cast_fp16 = relu(x = input_671_cast_fp16)[name = tensor("input_673_cast_fp16")]; + tensor input_675_pad_type_0 = const()[name = tensor("input_675_pad_type_0"), val = tensor("valid")]; + tensor input_675_strides_0 = const()[name = tensor("input_675_strides_0"), val = tensor([1])]; + tensor input_675_pad_0 = const()[name = tensor("input_675_pad_0"), val = tensor([0, 0])]; + tensor input_675_dilations_0 = const()[name = tensor("input_675_dilations_0"), val = tensor([1])]; + tensor input_675_groups_0 = const()[name = tensor("input_675_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd18_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd18_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5703552)))]; + tensor net_xvector_block2_tdnnd18_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd18_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5707712)))]; + tensor 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("input_675_cast_fp16")]; + tensor m_59_cast_fp16 = sigmoid(x = input_675_cast_fp16)[name = tensor("m_59_cast_fp16")]; + tensor var_2349_cast_fp16 = mul(x = y_59_cast_fp16, y = m_59_cast_fp16)[name = tensor("op_2349_cast_fp16")]; + tensor input_677_interleave_0 = const()[name = tensor("input_677_interleave_0"), val = tensor(false)]; + tensor input_677_cast_fp16 = concat(axis = var_11, interleave = input_677_interleave_0, values = (input_657_cast_fp16, var_2349_cast_fp16))[name = tensor("input_677_cast_fp16")]; + tensor net_xvector_block2_tdnnd19_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd19_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5707840)))]; + tensor net_xvector_block2_tdnnd19_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd19_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5709568)))]; + tensor net_xvector_block2_tdnnd19_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd19_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5711296)))]; + tensor net_xvector_block2_tdnnd19_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd19_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5713024)))]; + tensor 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("input_679_cast_fp16")]; + tensor input_681_cast_fp16 = relu(x = input_679_cast_fp16)[name = tensor("input_681_cast_fp16")]; + tensor input_683_pad_type_0 = const()[name = tensor("input_683_pad_type_0"), val = tensor("valid")]; + tensor input_683_strides_0 = const()[name = tensor("input_683_strides_0"), val = tensor([1])]; + tensor input_683_pad_0 = const()[name = tensor("input_683_pad_0"), val = tensor([0, 0])]; + tensor input_683_dilations_0 = const()[name = tensor("input_683_dilations_0"), val = tensor([1])]; + tensor input_683_groups_0 = const()[name = tensor("input_683_groups_0"), val = tensor(1)]; + tensor const_298_to_fp16 = const()[name = tensor("const_298_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5714752)))]; + tensor const_299_to_fp16 = const()[name = tensor("const_299_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5927808)))]; + tensor input_685_cast_fp16 = conv(bias = const_299_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_298_to_fp16, x = input_681_cast_fp16)[name = tensor("input_685_cast_fp16")]; + tensor input_687_cast_fp16 = relu(x = input_685_cast_fp16)[name = tensor("input_687_cast_fp16")]; + tensor y_61_pad_type_0 = const()[name = tensor("y_61_pad_type_0"), val = tensor("custom")]; + tensor y_61_pad_0 = const()[name = tensor("y_61_pad_0"), val = tensor([2, 2])]; + tensor y_61_dilations_0 = const()[name = tensor("y_61_dilations_0"), val = tensor([2])]; + tensor y_61_strides_0 = const()[name = tensor("y_61_strides_0"), val = tensor([1])]; + tensor y_61_groups_0 = const()[name = tensor("y_61_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd19_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd19_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5928128)))]; + tensor 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("y_61_cast_fp16")]; + tensor var_2386_axes_0 = const()[name = tensor("op_2386_axes_0"), val = tensor([-1])]; + tensor var_2386_keep_dims_0 = const()[name = tensor("op_2386_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2386_cast_fp16")]; + tensor var_2387 = const()[name = tensor("op_2387"), val = tensor([100])]; + tensor var_2388 = const()[name = tensor("op_2388"), val = tensor([100])]; + tensor seg_121_pad_type_0 = const()[name = tensor("seg_121_pad_type_0"), val = tensor("custom")]; + tensor seg_121_pad_0 = const()[name = tensor("seg_121_pad_0"), val = tensor([0, 0])]; + tensor seg_121_exclude_padding_from_average_0 = const()[name = tensor("seg_121_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_121_ceil_mode_0 = const()[name = tensor("seg_121_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_121_cast_fp16")]; + tensor var_2394_axes_0 = const()[name = tensor("op_2394_axes_0"), val = tensor([-1])]; + tensor var_2394_cast_fp16 = expand_dims(axes = var_2394_axes_0, x = seg_121_cast_fp16)[name = tensor("op_2394_cast_fp16")]; + tensor var_2396_reps_0 = const()[name = tensor("op_2396_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2396_cast_fp16 = tile(reps = var_2396_reps_0, x = var_2394_cast_fp16)[name = tensor("op_2396_cast_fp16")]; + tensor var_2397 = const()[name = tensor("op_2397"), val = tensor([1, 128, -1])]; + tensor seg_123_cast_fp16 = reshape(shape = var_2397, x = var_2396_cast_fp16)[name = tensor("seg_123_cast_fp16")]; + tensor input_689_cast_fp16 = add(x = var_2386_cast_fp16, y = seg_123_cast_fp16)[name = tensor("input_689_cast_fp16")]; + tensor input_691_pad_type_0 = const()[name = tensor("input_691_pad_type_0"), val = tensor("valid")]; + tensor input_691_strides_0 = const()[name = tensor("input_691_strides_0"), val = tensor([1])]; + tensor input_691_pad_0 = const()[name = tensor("input_691_pad_0"), val = tensor([0, 0])]; + tensor input_691_dilations_0 = const()[name = tensor("input_691_dilations_0"), val = tensor([1])]; + tensor input_691_groups_0 = const()[name = tensor("input_691_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd19_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd19_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5952768)))]; + tensor net_xvector_block2_tdnnd19_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd19_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5969216)))]; + tensor 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("input_691_cast_fp16")]; + tensor input_693_cast_fp16 = relu(x = input_691_cast_fp16)[name = tensor("input_693_cast_fp16")]; + tensor input_695_pad_type_0 = const()[name = tensor("input_695_pad_type_0"), val = tensor("valid")]; + tensor input_695_strides_0 = const()[name = tensor("input_695_strides_0"), val = tensor([1])]; + tensor input_695_pad_0 = const()[name = tensor("input_695_pad_0"), val = tensor([0, 0])]; + tensor input_695_dilations_0 = const()[name = tensor("input_695_dilations_0"), val = tensor([1])]; + tensor input_695_groups_0 = const()[name = tensor("input_695_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd19_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd19_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5969408)))]; + tensor net_xvector_block2_tdnnd19_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd19_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5973568)))]; + tensor 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("input_695_cast_fp16")]; + tensor m_61_cast_fp16 = sigmoid(x = input_695_cast_fp16)[name = tensor("m_61_cast_fp16")]; + tensor var_2418_cast_fp16 = mul(x = y_61_cast_fp16, y = m_61_cast_fp16)[name = tensor("op_2418_cast_fp16")]; + tensor input_697_interleave_0 = const()[name = tensor("input_697_interleave_0"), val = tensor(false)]; + tensor input_697_cast_fp16 = concat(axis = var_11, interleave = input_697_interleave_0, values = (input_677_cast_fp16, var_2418_cast_fp16))[name = tensor("input_697_cast_fp16")]; + tensor net_xvector_block2_tdnnd20_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd20_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5973696)))]; + tensor net_xvector_block2_tdnnd20_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd20_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5975488)))]; + tensor net_xvector_block2_tdnnd20_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd20_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5977280)))]; + tensor net_xvector_block2_tdnnd20_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd20_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5979072)))]; + tensor 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("input_699_cast_fp16")]; + tensor input_701_cast_fp16 = relu(x = input_699_cast_fp16)[name = tensor("input_701_cast_fp16")]; + tensor input_703_pad_type_0 = const()[name = tensor("input_703_pad_type_0"), val = tensor("valid")]; + tensor input_703_strides_0 = const()[name = tensor("input_703_strides_0"), val = tensor([1])]; + tensor input_703_pad_0 = const()[name = tensor("input_703_pad_0"), val = tensor([0, 0])]; + tensor input_703_dilations_0 = const()[name = tensor("input_703_dilations_0"), val = tensor([1])]; + tensor input_703_groups_0 = const()[name = tensor("input_703_groups_0"), val = tensor(1)]; + tensor const_300_to_fp16 = const()[name = tensor("const_300_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5980864)))]; + tensor const_301_to_fp16 = const()[name = tensor("const_301_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6202112)))]; + tensor input_705_cast_fp16 = conv(bias = const_301_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_300_to_fp16, x = input_701_cast_fp16)[name = tensor("input_705_cast_fp16")]; + tensor input_707_cast_fp16 = relu(x = input_705_cast_fp16)[name = tensor("input_707_cast_fp16")]; + tensor y_63_pad_type_0 = const()[name = tensor("y_63_pad_type_0"), val = tensor("custom")]; + tensor y_63_pad_0 = const()[name = tensor("y_63_pad_0"), val = tensor([2, 2])]; + tensor y_63_dilations_0 = const()[name = tensor("y_63_dilations_0"), val = tensor([2])]; + tensor y_63_strides_0 = const()[name = tensor("y_63_strides_0"), val = tensor([1])]; + tensor y_63_groups_0 = const()[name = tensor("y_63_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd20_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd20_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6202432)))]; + tensor 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("y_63_cast_fp16")]; + tensor var_2455_axes_0 = const()[name = tensor("op_2455_axes_0"), val = tensor([-1])]; + tensor var_2455_keep_dims_0 = const()[name = tensor("op_2455_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2455_cast_fp16")]; + tensor var_2456 = const()[name = tensor("op_2456"), val = tensor([100])]; + tensor var_2457 = const()[name = tensor("op_2457"), val = tensor([100])]; + tensor seg_125_pad_type_0 = const()[name = tensor("seg_125_pad_type_0"), val = tensor("custom")]; + tensor seg_125_pad_0 = const()[name = tensor("seg_125_pad_0"), val = tensor([0, 0])]; + tensor seg_125_exclude_padding_from_average_0 = const()[name = tensor("seg_125_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_125_ceil_mode_0 = const()[name = tensor("seg_125_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_125_cast_fp16")]; + tensor var_2463_axes_0 = const()[name = tensor("op_2463_axes_0"), val = tensor([-1])]; + tensor var_2463_cast_fp16 = expand_dims(axes = var_2463_axes_0, x = seg_125_cast_fp16)[name = tensor("op_2463_cast_fp16")]; + tensor var_2465_reps_0 = const()[name = tensor("op_2465_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2465_cast_fp16 = tile(reps = var_2465_reps_0, x = var_2463_cast_fp16)[name = tensor("op_2465_cast_fp16")]; + tensor var_2466 = const()[name = tensor("op_2466"), val = tensor([1, 128, -1])]; + tensor seg_127_cast_fp16 = reshape(shape = var_2466, x = var_2465_cast_fp16)[name = tensor("seg_127_cast_fp16")]; + tensor input_709_cast_fp16 = add(x = var_2455_cast_fp16, y = seg_127_cast_fp16)[name = tensor("input_709_cast_fp16")]; + tensor input_711_pad_type_0 = const()[name = tensor("input_711_pad_type_0"), val = tensor("valid")]; + tensor input_711_strides_0 = const()[name = tensor("input_711_strides_0"), val = tensor([1])]; + tensor input_711_pad_0 = const()[name = tensor("input_711_pad_0"), val = tensor([0, 0])]; + tensor input_711_dilations_0 = const()[name = tensor("input_711_dilations_0"), val = tensor([1])]; + tensor input_711_groups_0 = const()[name = tensor("input_711_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd20_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd20_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6227072)))]; + tensor net_xvector_block2_tdnnd20_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd20_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6243520)))]; + tensor 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("input_711_cast_fp16")]; + tensor input_713_cast_fp16 = relu(x = input_711_cast_fp16)[name = tensor("input_713_cast_fp16")]; + tensor input_715_pad_type_0 = const()[name = tensor("input_715_pad_type_0"), val = tensor("valid")]; + tensor input_715_strides_0 = const()[name = tensor("input_715_strides_0"), val = tensor([1])]; + tensor input_715_pad_0 = const()[name = tensor("input_715_pad_0"), val = tensor([0, 0])]; + tensor input_715_dilations_0 = const()[name = tensor("input_715_dilations_0"), val = tensor([1])]; + tensor input_715_groups_0 = const()[name = tensor("input_715_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd20_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd20_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6243712)))]; + tensor net_xvector_block2_tdnnd20_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd20_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6247872)))]; + tensor 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("input_715_cast_fp16")]; + tensor m_63_cast_fp16 = sigmoid(x = input_715_cast_fp16)[name = tensor("m_63_cast_fp16")]; + tensor var_2487_cast_fp16 = mul(x = y_63_cast_fp16, y = m_63_cast_fp16)[name = tensor("op_2487_cast_fp16")]; + tensor input_717_interleave_0 = const()[name = tensor("input_717_interleave_0"), val = tensor(false)]; + tensor input_717_cast_fp16 = concat(axis = var_11, interleave = input_717_interleave_0, values = (input_697_cast_fp16, var_2487_cast_fp16))[name = tensor("input_717_cast_fp16")]; + tensor net_xvector_block2_tdnnd21_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd21_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6248000)))]; + tensor net_xvector_block2_tdnnd21_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd21_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6249856)))]; + tensor net_xvector_block2_tdnnd21_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd21_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6251712)))]; + tensor net_xvector_block2_tdnnd21_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd21_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6253568)))]; + tensor 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("input_719_cast_fp16")]; + tensor input_721_cast_fp16 = relu(x = input_719_cast_fp16)[name = tensor("input_721_cast_fp16")]; + tensor input_723_pad_type_0 = const()[name = tensor("input_723_pad_type_0"), val = tensor("valid")]; + tensor input_723_strides_0 = const()[name = tensor("input_723_strides_0"), val = tensor([1])]; + tensor input_723_pad_0 = const()[name = tensor("input_723_pad_0"), val = tensor([0, 0])]; + tensor input_723_dilations_0 = const()[name = tensor("input_723_dilations_0"), val = tensor([1])]; + tensor input_723_groups_0 = const()[name = tensor("input_723_groups_0"), val = tensor(1)]; + tensor const_302_to_fp16 = const()[name = tensor("const_302_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6255424)))]; + tensor const_303_to_fp16 = const()[name = tensor("const_303_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6484864)))]; + tensor input_725_cast_fp16 = conv(bias = const_303_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_302_to_fp16, x = input_721_cast_fp16)[name = tensor("input_725_cast_fp16")]; + tensor input_727_cast_fp16 = relu(x = input_725_cast_fp16)[name = tensor("input_727_cast_fp16")]; + tensor y_65_pad_type_0 = const()[name = tensor("y_65_pad_type_0"), val = tensor("custom")]; + tensor y_65_pad_0 = const()[name = tensor("y_65_pad_0"), val = tensor([2, 2])]; + tensor y_65_dilations_0 = const()[name = tensor("y_65_dilations_0"), val = tensor([2])]; + tensor y_65_strides_0 = const()[name = tensor("y_65_strides_0"), val = tensor([1])]; + tensor y_65_groups_0 = const()[name = tensor("y_65_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd21_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd21_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6485184)))]; + tensor 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("y_65_cast_fp16")]; + tensor var_2524_axes_0 = const()[name = tensor("op_2524_axes_0"), val = tensor([-1])]; + tensor var_2524_keep_dims_0 = const()[name = tensor("op_2524_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2524_cast_fp16")]; + tensor var_2525 = const()[name = tensor("op_2525"), val = tensor([100])]; + tensor var_2526 = const()[name = tensor("op_2526"), val = tensor([100])]; + tensor seg_129_pad_type_0 = const()[name = tensor("seg_129_pad_type_0"), val = tensor("custom")]; + tensor seg_129_pad_0 = const()[name = tensor("seg_129_pad_0"), val = tensor([0, 0])]; + tensor seg_129_exclude_padding_from_average_0 = const()[name = tensor("seg_129_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_129_ceil_mode_0 = const()[name = tensor("seg_129_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_129_cast_fp16")]; + tensor var_2532_axes_0 = const()[name = tensor("op_2532_axes_0"), val = tensor([-1])]; + tensor var_2532_cast_fp16 = expand_dims(axes = var_2532_axes_0, x = seg_129_cast_fp16)[name = tensor("op_2532_cast_fp16")]; + tensor var_2534_reps_0 = const()[name = tensor("op_2534_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2534_cast_fp16 = tile(reps = var_2534_reps_0, x = var_2532_cast_fp16)[name = tensor("op_2534_cast_fp16")]; + tensor var_2535 = const()[name = tensor("op_2535"), val = tensor([1, 128, -1])]; + tensor seg_131_cast_fp16 = reshape(shape = var_2535, x = var_2534_cast_fp16)[name = tensor("seg_131_cast_fp16")]; + tensor input_729_cast_fp16 = add(x = var_2524_cast_fp16, y = seg_131_cast_fp16)[name = tensor("input_729_cast_fp16")]; + tensor input_731_pad_type_0 = const()[name = tensor("input_731_pad_type_0"), val = tensor("valid")]; + tensor input_731_strides_0 = const()[name = tensor("input_731_strides_0"), val = tensor([1])]; + tensor input_731_pad_0 = const()[name = tensor("input_731_pad_0"), val = tensor([0, 0])]; + tensor input_731_dilations_0 = const()[name = tensor("input_731_dilations_0"), val = tensor([1])]; + tensor input_731_groups_0 = const()[name = tensor("input_731_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd21_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd21_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6509824)))]; + tensor net_xvector_block2_tdnnd21_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd21_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6526272)))]; + tensor 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("input_731_cast_fp16")]; + tensor input_733_cast_fp16 = relu(x = input_731_cast_fp16)[name = tensor("input_733_cast_fp16")]; + tensor input_735_pad_type_0 = const()[name = tensor("input_735_pad_type_0"), val = tensor("valid")]; + tensor input_735_strides_0 = const()[name = tensor("input_735_strides_0"), val = tensor([1])]; + tensor input_735_pad_0 = const()[name = tensor("input_735_pad_0"), val = tensor([0, 0])]; + tensor input_735_dilations_0 = const()[name = tensor("input_735_dilations_0"), val = tensor([1])]; + tensor input_735_groups_0 = const()[name = tensor("input_735_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd21_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd21_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6526464)))]; + tensor net_xvector_block2_tdnnd21_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd21_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6530624)))]; + tensor 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("input_735_cast_fp16")]; + tensor m_65_cast_fp16 = sigmoid(x = input_735_cast_fp16)[name = tensor("m_65_cast_fp16")]; + tensor var_2556_cast_fp16 = mul(x = y_65_cast_fp16, y = m_65_cast_fp16)[name = tensor("op_2556_cast_fp16")]; + tensor input_737_interleave_0 = const()[name = tensor("input_737_interleave_0"), val = tensor(false)]; + tensor input_737_cast_fp16 = concat(axis = var_11, interleave = input_737_interleave_0, values = (input_717_cast_fp16, var_2556_cast_fp16))[name = tensor("input_737_cast_fp16")]; + tensor net_xvector_block2_tdnnd22_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd22_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6530752)))]; + tensor net_xvector_block2_tdnnd22_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd22_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6532672)))]; + tensor net_xvector_block2_tdnnd22_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd22_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6534592)))]; + tensor net_xvector_block2_tdnnd22_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd22_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6536512)))]; + tensor 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("input_739_cast_fp16")]; + tensor input_741_cast_fp16 = relu(x = input_739_cast_fp16)[name = tensor("input_741_cast_fp16")]; + tensor input_743_pad_type_0 = const()[name = tensor("input_743_pad_type_0"), val = tensor("valid")]; + tensor input_743_strides_0 = const()[name = tensor("input_743_strides_0"), val = tensor([1])]; + tensor input_743_pad_0 = const()[name = tensor("input_743_pad_0"), val = tensor([0, 0])]; + tensor input_743_dilations_0 = const()[name = tensor("input_743_dilations_0"), val = tensor([1])]; + tensor input_743_groups_0 = const()[name = tensor("input_743_groups_0"), val = tensor(1)]; + tensor const_304_to_fp16 = const()[name = tensor("const_304_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6538432)))]; + tensor const_305_to_fp16 = const()[name = tensor("const_305_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6776064)))]; + tensor input_745_cast_fp16 = conv(bias = const_305_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_304_to_fp16, x = input_741_cast_fp16)[name = tensor("input_745_cast_fp16")]; + tensor input_747_cast_fp16 = relu(x = input_745_cast_fp16)[name = tensor("input_747_cast_fp16")]; + tensor y_67_pad_type_0 = const()[name = tensor("y_67_pad_type_0"), val = tensor("custom")]; + tensor y_67_pad_0 = const()[name = tensor("y_67_pad_0"), val = tensor([2, 2])]; + tensor y_67_dilations_0 = const()[name = tensor("y_67_dilations_0"), val = tensor([2])]; + tensor y_67_strides_0 = const()[name = tensor("y_67_strides_0"), val = tensor([1])]; + tensor y_67_groups_0 = const()[name = tensor("y_67_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd22_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd22_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6776384)))]; + tensor 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("y_67_cast_fp16")]; + tensor var_2593_axes_0 = const()[name = tensor("op_2593_axes_0"), val = tensor([-1])]; + tensor var_2593_keep_dims_0 = const()[name = tensor("op_2593_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2593_cast_fp16")]; + tensor var_2594 = const()[name = tensor("op_2594"), val = tensor([100])]; + tensor var_2595 = const()[name = tensor("op_2595"), val = tensor([100])]; + tensor seg_133_pad_type_0 = const()[name = tensor("seg_133_pad_type_0"), val = tensor("custom")]; + tensor seg_133_pad_0 = const()[name = tensor("seg_133_pad_0"), val = tensor([0, 0])]; + tensor seg_133_exclude_padding_from_average_0 = const()[name = tensor("seg_133_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_133_ceil_mode_0 = const()[name = tensor("seg_133_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_133_cast_fp16")]; + tensor var_2601_axes_0 = const()[name = tensor("op_2601_axes_0"), val = tensor([-1])]; + tensor var_2601_cast_fp16 = expand_dims(axes = var_2601_axes_0, x = seg_133_cast_fp16)[name = tensor("op_2601_cast_fp16")]; + tensor var_2603_reps_0 = const()[name = tensor("op_2603_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2603_cast_fp16 = tile(reps = var_2603_reps_0, x = var_2601_cast_fp16)[name = tensor("op_2603_cast_fp16")]; + tensor var_2604 = const()[name = tensor("op_2604"), val = tensor([1, 128, -1])]; + tensor seg_135_cast_fp16 = reshape(shape = var_2604, x = var_2603_cast_fp16)[name = tensor("seg_135_cast_fp16")]; + tensor input_749_cast_fp16 = add(x = var_2593_cast_fp16, y = seg_135_cast_fp16)[name = tensor("input_749_cast_fp16")]; + tensor input_751_pad_type_0 = const()[name = tensor("input_751_pad_type_0"), val = tensor("valid")]; + tensor input_751_strides_0 = const()[name = tensor("input_751_strides_0"), val = tensor([1])]; + tensor input_751_pad_0 = const()[name = tensor("input_751_pad_0"), val = tensor([0, 0])]; + tensor input_751_dilations_0 = const()[name = tensor("input_751_dilations_0"), val = tensor([1])]; + tensor input_751_groups_0 = const()[name = tensor("input_751_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd22_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd22_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6801024)))]; + tensor net_xvector_block2_tdnnd22_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd22_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6817472)))]; + tensor 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("input_751_cast_fp16")]; + tensor input_753_cast_fp16 = relu(x = input_751_cast_fp16)[name = tensor("input_753_cast_fp16")]; + tensor input_755_pad_type_0 = const()[name = tensor("input_755_pad_type_0"), val = tensor("valid")]; + tensor input_755_strides_0 = const()[name = tensor("input_755_strides_0"), val = tensor([1])]; + tensor input_755_pad_0 = const()[name = tensor("input_755_pad_0"), val = tensor([0, 0])]; + tensor input_755_dilations_0 = const()[name = tensor("input_755_dilations_0"), val = tensor([1])]; + tensor input_755_groups_0 = const()[name = tensor("input_755_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd22_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd22_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6817664)))]; + tensor net_xvector_block2_tdnnd22_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd22_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6821824)))]; + tensor 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("input_755_cast_fp16")]; + tensor m_67_cast_fp16 = sigmoid(x = input_755_cast_fp16)[name = tensor("m_67_cast_fp16")]; + tensor var_2625_cast_fp16 = mul(x = y_67_cast_fp16, y = m_67_cast_fp16)[name = tensor("op_2625_cast_fp16")]; + tensor input_757_interleave_0 = const()[name = tensor("input_757_interleave_0"), val = tensor(false)]; + tensor input_757_cast_fp16 = concat(axis = var_11, interleave = input_757_interleave_0, values = (input_737_cast_fp16, var_2625_cast_fp16))[name = tensor("input_757_cast_fp16")]; + tensor net_xvector_block2_tdnnd23_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd23_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6821952)))]; + tensor net_xvector_block2_tdnnd23_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd23_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6823936)))]; + tensor net_xvector_block2_tdnnd23_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd23_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6825920)))]; + tensor net_xvector_block2_tdnnd23_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd23_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6827904)))]; + tensor 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("input_759_cast_fp16")]; + tensor input_761_cast_fp16 = relu(x = input_759_cast_fp16)[name = tensor("input_761_cast_fp16")]; + tensor input_763_pad_type_0 = const()[name = tensor("input_763_pad_type_0"), val = tensor("valid")]; + tensor input_763_strides_0 = const()[name = tensor("input_763_strides_0"), val = tensor([1])]; + tensor input_763_pad_0 = const()[name = tensor("input_763_pad_0"), val = tensor([0, 0])]; + tensor input_763_dilations_0 = const()[name = tensor("input_763_dilations_0"), val = tensor([1])]; + tensor input_763_groups_0 = const()[name = tensor("input_763_groups_0"), val = tensor(1)]; + tensor const_306_to_fp16 = const()[name = tensor("const_306_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6829888)))]; + tensor const_307_to_fp16 = const()[name = tensor("const_307_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7075712)))]; + tensor input_765_cast_fp16 = conv(bias = const_307_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_306_to_fp16, x = input_761_cast_fp16)[name = tensor("input_765_cast_fp16")]; + tensor input_767_cast_fp16 = relu(x = input_765_cast_fp16)[name = tensor("input_767_cast_fp16")]; + tensor y_69_pad_type_0 = const()[name = tensor("y_69_pad_type_0"), val = tensor("custom")]; + tensor y_69_pad_0 = const()[name = tensor("y_69_pad_0"), val = tensor([2, 2])]; + tensor y_69_dilations_0 = const()[name = tensor("y_69_dilations_0"), val = tensor([2])]; + tensor y_69_strides_0 = const()[name = tensor("y_69_strides_0"), val = tensor([1])]; + tensor y_69_groups_0 = const()[name = tensor("y_69_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd23_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd23_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7076032)))]; + tensor 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("y_69_cast_fp16")]; + tensor var_2662_axes_0 = const()[name = tensor("op_2662_axes_0"), val = tensor([-1])]; + tensor var_2662_keep_dims_0 = const()[name = tensor("op_2662_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2662_cast_fp16")]; + tensor var_2663 = const()[name = tensor("op_2663"), val = tensor([100])]; + tensor var_2664 = const()[name = tensor("op_2664"), val = tensor([100])]; + tensor seg_137_pad_type_0 = const()[name = tensor("seg_137_pad_type_0"), val = tensor("custom")]; + tensor seg_137_pad_0 = const()[name = tensor("seg_137_pad_0"), val = tensor([0, 0])]; + tensor seg_137_exclude_padding_from_average_0 = const()[name = tensor("seg_137_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_137_ceil_mode_0 = const()[name = tensor("seg_137_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_137_cast_fp16")]; + tensor var_2670_axes_0 = const()[name = tensor("op_2670_axes_0"), val = tensor([-1])]; + tensor var_2670_cast_fp16 = expand_dims(axes = var_2670_axes_0, x = seg_137_cast_fp16)[name = tensor("op_2670_cast_fp16")]; + tensor var_2672_reps_0 = const()[name = tensor("op_2672_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2672_cast_fp16 = tile(reps = var_2672_reps_0, x = var_2670_cast_fp16)[name = tensor("op_2672_cast_fp16")]; + tensor var_2673 = const()[name = tensor("op_2673"), val = tensor([1, 128, -1])]; + tensor seg_139_cast_fp16 = reshape(shape = var_2673, x = var_2672_cast_fp16)[name = tensor("seg_139_cast_fp16")]; + tensor input_769_cast_fp16 = add(x = var_2662_cast_fp16, y = seg_139_cast_fp16)[name = tensor("input_769_cast_fp16")]; + tensor input_771_pad_type_0 = const()[name = tensor("input_771_pad_type_0"), val = tensor("valid")]; + tensor input_771_strides_0 = const()[name = tensor("input_771_strides_0"), val = tensor([1])]; + tensor input_771_pad_0 = const()[name = tensor("input_771_pad_0"), val = tensor([0, 0])]; + tensor input_771_dilations_0 = const()[name = tensor("input_771_dilations_0"), val = tensor([1])]; + tensor input_771_groups_0 = const()[name = tensor("input_771_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd23_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd23_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7100672)))]; + tensor net_xvector_block2_tdnnd23_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd23_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7117120)))]; + tensor 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("input_771_cast_fp16")]; + tensor input_773_cast_fp16 = relu(x = input_771_cast_fp16)[name = tensor("input_773_cast_fp16")]; + tensor input_775_pad_type_0 = const()[name = tensor("input_775_pad_type_0"), val = tensor("valid")]; + tensor input_775_strides_0 = const()[name = tensor("input_775_strides_0"), val = tensor([1])]; + tensor input_775_pad_0 = const()[name = tensor("input_775_pad_0"), val = tensor([0, 0])]; + tensor input_775_dilations_0 = const()[name = tensor("input_775_dilations_0"), val = tensor([1])]; + tensor input_775_groups_0 = const()[name = tensor("input_775_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd23_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd23_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7117312)))]; + tensor net_xvector_block2_tdnnd23_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd23_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7121472)))]; + tensor 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("input_775_cast_fp16")]; + tensor m_69_cast_fp16 = sigmoid(x = input_775_cast_fp16)[name = tensor("m_69_cast_fp16")]; + tensor var_2694_cast_fp16 = mul(x = y_69_cast_fp16, y = m_69_cast_fp16)[name = tensor("op_2694_cast_fp16")]; + tensor input_777_interleave_0 = const()[name = tensor("input_777_interleave_0"), val = tensor(false)]; + tensor input_777_cast_fp16 = concat(axis = var_11, interleave = input_777_interleave_0, values = (input_757_cast_fp16, var_2694_cast_fp16))[name = tensor("input_777_cast_fp16")]; + tensor net_xvector_block2_tdnnd24_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd24_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7121600)))]; + tensor net_xvector_block2_tdnnd24_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd24_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7123648)))]; + tensor net_xvector_block2_tdnnd24_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd24_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7125696)))]; + tensor net_xvector_block2_tdnnd24_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd24_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7127744)))]; + tensor 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("input_779_cast_fp16")]; + tensor input_781_cast_fp16 = relu(x = input_779_cast_fp16)[name = tensor("input_781_cast_fp16")]; + tensor input_783_pad_type_0 = const()[name = tensor("input_783_pad_type_0"), val = tensor("valid")]; + tensor input_783_strides_0 = const()[name = tensor("input_783_strides_0"), val = tensor([1])]; + tensor input_783_pad_0 = const()[name = tensor("input_783_pad_0"), val = tensor([0, 0])]; + tensor input_783_dilations_0 = const()[name = tensor("input_783_dilations_0"), val = tensor([1])]; + tensor input_783_groups_0 = const()[name = tensor("input_783_groups_0"), val = tensor(1)]; + tensor const_308_to_fp16 = const()[name = tensor("const_308_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7129792)))]; + tensor const_309_to_fp16 = const()[name = tensor("const_309_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7383808)))]; + tensor input_785_cast_fp16 = conv(bias = const_309_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_308_to_fp16, x = input_781_cast_fp16)[name = tensor("input_785_cast_fp16")]; + tensor input_787_cast_fp16 = relu(x = input_785_cast_fp16)[name = tensor("input_787_cast_fp16")]; + tensor y_71_pad_type_0 = const()[name = tensor("y_71_pad_type_0"), val = tensor("custom")]; + tensor y_71_pad_0 = const()[name = tensor("y_71_pad_0"), val = tensor([2, 2])]; + tensor y_71_dilations_0 = const()[name = tensor("y_71_dilations_0"), val = tensor([2])]; + tensor y_71_strides_0 = const()[name = tensor("y_71_strides_0"), val = tensor([1])]; + tensor y_71_groups_0 = const()[name = tensor("y_71_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd24_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd24_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7384128)))]; + tensor 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("y_71_cast_fp16")]; + tensor var_2731_axes_0 = const()[name = tensor("op_2731_axes_0"), val = tensor([-1])]; + tensor var_2731_keep_dims_0 = const()[name = tensor("op_2731_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2731_cast_fp16")]; + tensor var_2732 = const()[name = tensor("op_2732"), val = tensor([100])]; + tensor var_2733 = const()[name = tensor("op_2733"), val = tensor([100])]; + tensor seg_141_pad_type_0 = const()[name = tensor("seg_141_pad_type_0"), val = tensor("custom")]; + tensor seg_141_pad_0 = const()[name = tensor("seg_141_pad_0"), val = tensor([0, 0])]; + tensor seg_141_exclude_padding_from_average_0 = const()[name = tensor("seg_141_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_141_ceil_mode_0 = const()[name = tensor("seg_141_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_141_cast_fp16")]; + tensor var_2739_axes_0 = const()[name = tensor("op_2739_axes_0"), val = tensor([-1])]; + tensor var_2739_cast_fp16 = expand_dims(axes = var_2739_axes_0, x = seg_141_cast_fp16)[name = tensor("op_2739_cast_fp16")]; + tensor var_2741_reps_0 = const()[name = tensor("op_2741_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2741_cast_fp16 = tile(reps = var_2741_reps_0, x = var_2739_cast_fp16)[name = tensor("op_2741_cast_fp16")]; + tensor var_2742 = const()[name = tensor("op_2742"), val = tensor([1, 128, -1])]; + tensor seg_143_cast_fp16 = reshape(shape = var_2742, x = var_2741_cast_fp16)[name = tensor("seg_143_cast_fp16")]; + tensor input_789_cast_fp16 = add(x = var_2731_cast_fp16, y = seg_143_cast_fp16)[name = tensor("input_789_cast_fp16")]; + tensor input_791_pad_type_0 = const()[name = tensor("input_791_pad_type_0"), val = tensor("valid")]; + tensor input_791_strides_0 = const()[name = tensor("input_791_strides_0"), val = tensor([1])]; + tensor input_791_pad_0 = const()[name = tensor("input_791_pad_0"), val = tensor([0, 0])]; + tensor input_791_dilations_0 = const()[name = tensor("input_791_dilations_0"), val = tensor([1])]; + tensor input_791_groups_0 = const()[name = tensor("input_791_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd24_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd24_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7408768)))]; + tensor net_xvector_block2_tdnnd24_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd24_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7425216)))]; + tensor 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("input_791_cast_fp16")]; + tensor input_793_cast_fp16 = relu(x = input_791_cast_fp16)[name = tensor("input_793_cast_fp16")]; + tensor input_795_pad_type_0 = const()[name = tensor("input_795_pad_type_0"), val = tensor("valid")]; + tensor input_795_strides_0 = const()[name = tensor("input_795_strides_0"), val = tensor([1])]; + tensor input_795_pad_0 = const()[name = tensor("input_795_pad_0"), val = tensor([0, 0])]; + tensor input_795_dilations_0 = const()[name = tensor("input_795_dilations_0"), val = tensor([1])]; + tensor input_795_groups_0 = const()[name = tensor("input_795_groups_0"), val = tensor(1)]; + tensor net_xvector_block2_tdnnd24_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd24_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7425408)))]; + tensor net_xvector_block2_tdnnd24_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block2_tdnnd24_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7429568)))]; + tensor 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("input_795_cast_fp16")]; + tensor m_71_cast_fp16 = sigmoid(x = input_795_cast_fp16)[name = tensor("m_71_cast_fp16")]; + tensor var_2763_cast_fp16 = mul(x = y_71_cast_fp16, y = m_71_cast_fp16)[name = tensor("op_2763_cast_fp16")]; + tensor input_797_interleave_0 = const()[name = tensor("input_797_interleave_0"), val = tensor(false)]; + tensor input_797_cast_fp16 = concat(axis = var_11, interleave = input_797_interleave_0, values = (input_777_cast_fp16, var_2763_cast_fp16))[name = tensor("input_797_cast_fp16")]; + tensor net_xvector_transit2_nonlinear_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_transit2_nonlinear_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7429696)))]; + tensor net_xvector_transit2_nonlinear_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_transit2_nonlinear_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7431808)))]; + tensor net_xvector_transit2_nonlinear_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_transit2_nonlinear_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7433920)))]; + tensor net_xvector_transit2_nonlinear_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_transit2_nonlinear_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7436032)))]; + tensor 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("input_799_cast_fp16")]; + tensor input_801_cast_fp16 = relu(x = input_799_cast_fp16)[name = tensor("input_801_cast_fp16")]; + tensor input_803_pad_type_0 = const()[name = tensor("input_803_pad_type_0"), val = tensor("valid")]; + tensor input_803_strides_0 = const()[name = tensor("input_803_strides_0"), val = tensor([1])]; + tensor input_803_pad_0 = const()[name = tensor("input_803_pad_0"), val = tensor([0, 0])]; + tensor input_803_dilations_0 = const()[name = tensor("input_803_dilations_0"), val = tensor([1])]; + tensor input_803_groups_0 = const()[name = tensor("input_803_groups_0"), val = tensor(1)]; + tensor net_xvector_transit2_linear_weight_to_fp16 = const()[name = tensor("net_xvector_transit2_linear_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7438144)))]; + tensor 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("input_803_cast_fp16")]; + tensor net_xvector_block3_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd1_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8486784)))]; + tensor net_xvector_block3_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd1_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8487872)))]; + tensor net_xvector_block3_tdnnd1_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd1_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8488960)))]; + tensor net_xvector_block3_tdnnd1_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd1_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8490048)))]; + tensor 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("input_805_cast_fp16")]; + tensor input_807_cast_fp16 = relu(x = input_805_cast_fp16)[name = tensor("input_807_cast_fp16")]; + tensor input_809_pad_type_0 = const()[name = tensor("input_809_pad_type_0"), val = tensor("valid")]; + tensor input_809_strides_0 = const()[name = tensor("input_809_strides_0"), val = tensor([1])]; + tensor input_809_pad_0 = const()[name = tensor("input_809_pad_0"), val = tensor([0, 0])]; + tensor input_809_dilations_0 = const()[name = tensor("input_809_dilations_0"), val = tensor([1])]; + tensor input_809_groups_0 = const()[name = tensor("input_809_groups_0"), val = tensor(1)]; + tensor const_310_to_fp16 = const()[name = tensor("const_310_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8491136)))]; + tensor const_311_to_fp16 = const()[name = tensor("const_311_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8622272)))]; + tensor input_811_cast_fp16 = conv(bias = const_311_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_310_to_fp16, x = input_807_cast_fp16)[name = tensor("input_811_cast_fp16")]; + tensor input_813_cast_fp16 = relu(x = input_811_cast_fp16)[name = tensor("input_813_cast_fp16")]; + tensor y_73_pad_type_0 = const()[name = tensor("y_73_pad_type_0"), val = tensor("custom")]; + tensor y_73_pad_0 = const()[name = tensor("y_73_pad_0"), val = tensor([2, 2])]; + tensor y_73_dilations_0 = const()[name = tensor("y_73_dilations_0"), val = tensor([2])]; + tensor y_73_strides_0 = const()[name = tensor("y_73_strides_0"), val = tensor([1])]; + tensor y_73_groups_0 = const()[name = tensor("y_73_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd1_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd1_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8622592)))]; + tensor 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("y_73_cast_fp16")]; + tensor var_2831_axes_0 = const()[name = tensor("op_2831_axes_0"), val = tensor([-1])]; + tensor var_2831_keep_dims_0 = const()[name = tensor("op_2831_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2831_cast_fp16")]; + tensor var_2832 = const()[name = tensor("op_2832"), val = tensor([100])]; + tensor var_2833 = const()[name = tensor("op_2833"), val = tensor([100])]; + tensor seg_145_pad_type_0 = const()[name = tensor("seg_145_pad_type_0"), val = tensor("custom")]; + tensor seg_145_pad_0 = const()[name = tensor("seg_145_pad_0"), val = tensor([0, 0])]; + tensor seg_145_exclude_padding_from_average_0 = const()[name = tensor("seg_145_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_145_ceil_mode_0 = const()[name = tensor("seg_145_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_145_cast_fp16")]; + tensor var_2839_axes_0 = const()[name = tensor("op_2839_axes_0"), val = tensor([-1])]; + tensor var_2839_cast_fp16 = expand_dims(axes = var_2839_axes_0, x = seg_145_cast_fp16)[name = tensor("op_2839_cast_fp16")]; + tensor var_2841_reps_0 = const()[name = tensor("op_2841_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2841_cast_fp16 = tile(reps = var_2841_reps_0, x = var_2839_cast_fp16)[name = tensor("op_2841_cast_fp16")]; + tensor var_2842 = const()[name = tensor("op_2842"), val = tensor([1, 128, -1])]; + tensor seg_147_cast_fp16 = reshape(shape = var_2842, x = var_2841_cast_fp16)[name = tensor("seg_147_cast_fp16")]; + tensor input_815_cast_fp16 = add(x = var_2831_cast_fp16, y = seg_147_cast_fp16)[name = tensor("input_815_cast_fp16")]; + tensor input_817_pad_type_0 = const()[name = tensor("input_817_pad_type_0"), val = tensor("valid")]; + tensor input_817_strides_0 = const()[name = tensor("input_817_strides_0"), val = tensor([1])]; + tensor input_817_pad_0 = const()[name = tensor("input_817_pad_0"), val = tensor([0, 0])]; + tensor input_817_dilations_0 = const()[name = tensor("input_817_dilations_0"), val = tensor([1])]; + tensor input_817_groups_0 = const()[name = tensor("input_817_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd1_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd1_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8647232)))]; + tensor net_xvector_block3_tdnnd1_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd1_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8663680)))]; + tensor 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("input_817_cast_fp16")]; + tensor input_819_cast_fp16 = relu(x = input_817_cast_fp16)[name = tensor("input_819_cast_fp16")]; + tensor input_821_pad_type_0 = const()[name = tensor("input_821_pad_type_0"), val = tensor("valid")]; + tensor input_821_strides_0 = const()[name = tensor("input_821_strides_0"), val = tensor([1])]; + tensor input_821_pad_0 = const()[name = tensor("input_821_pad_0"), val = tensor([0, 0])]; + tensor input_821_dilations_0 = const()[name = tensor("input_821_dilations_0"), val = tensor([1])]; + tensor input_821_groups_0 = const()[name = tensor("input_821_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd1_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd1_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8663872)))]; + tensor net_xvector_block3_tdnnd1_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd1_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8668032)))]; + tensor 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("input_821_cast_fp16")]; + tensor m_73_cast_fp16 = sigmoid(x = input_821_cast_fp16)[name = tensor("m_73_cast_fp16")]; + tensor var_2863_cast_fp16 = mul(x = y_73_cast_fp16, y = m_73_cast_fp16)[name = tensor("op_2863_cast_fp16")]; + tensor input_823_interleave_0 = const()[name = tensor("input_823_interleave_0"), val = tensor(false)]; + tensor input_823_cast_fp16 = concat(axis = var_11, interleave = input_823_interleave_0, values = (input_803_cast_fp16, var_2863_cast_fp16))[name = tensor("input_823_cast_fp16")]; + tensor net_xvector_block3_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd2_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8668160)))]; + tensor net_xvector_block3_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd2_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8669312)))]; + tensor net_xvector_block3_tdnnd2_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd2_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8670464)))]; + tensor net_xvector_block3_tdnnd2_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd2_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8671616)))]; + tensor 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("input_825_cast_fp16")]; + tensor input_827_cast_fp16 = relu(x = input_825_cast_fp16)[name = tensor("input_827_cast_fp16")]; + tensor input_829_pad_type_0 = const()[name = tensor("input_829_pad_type_0"), val = tensor("valid")]; + tensor input_829_strides_0 = const()[name = tensor("input_829_strides_0"), val = tensor([1])]; + tensor input_829_pad_0 = const()[name = tensor("input_829_pad_0"), val = tensor([0, 0])]; + tensor input_829_dilations_0 = const()[name = tensor("input_829_dilations_0"), val = tensor([1])]; + tensor input_829_groups_0 = const()[name = tensor("input_829_groups_0"), val = tensor(1)]; + tensor const_312_to_fp16 = const()[name = tensor("const_312_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8672768)))]; + tensor const_313_to_fp16 = const()[name = tensor("const_313_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8812096)))]; + tensor input_831_cast_fp16 = conv(bias = const_313_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_312_to_fp16, x = input_827_cast_fp16)[name = tensor("input_831_cast_fp16")]; + tensor input_833_cast_fp16 = relu(x = input_831_cast_fp16)[name = tensor("input_833_cast_fp16")]; + tensor y_75_pad_type_0 = const()[name = tensor("y_75_pad_type_0"), val = tensor("custom")]; + tensor y_75_pad_0 = const()[name = tensor("y_75_pad_0"), val = tensor([2, 2])]; + tensor y_75_dilations_0 = const()[name = tensor("y_75_dilations_0"), val = tensor([2])]; + tensor y_75_strides_0 = const()[name = tensor("y_75_strides_0"), val = tensor([1])]; + tensor y_75_groups_0 = const()[name = tensor("y_75_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd2_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd2_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8812416)))]; + tensor 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("y_75_cast_fp16")]; + tensor var_2900_axes_0 = const()[name = tensor("op_2900_axes_0"), val = tensor([-1])]; + tensor var_2900_keep_dims_0 = const()[name = tensor("op_2900_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2900_cast_fp16")]; + tensor var_2901 = const()[name = tensor("op_2901"), val = tensor([100])]; + tensor var_2902 = const()[name = tensor("op_2902"), val = tensor([100])]; + tensor seg_149_pad_type_0 = const()[name = tensor("seg_149_pad_type_0"), val = tensor("custom")]; + tensor seg_149_pad_0 = const()[name = tensor("seg_149_pad_0"), val = tensor([0, 0])]; + tensor seg_149_exclude_padding_from_average_0 = const()[name = tensor("seg_149_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_149_ceil_mode_0 = const()[name = tensor("seg_149_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_149_cast_fp16")]; + tensor var_2908_axes_0 = const()[name = tensor("op_2908_axes_0"), val = tensor([-1])]; + tensor var_2908_cast_fp16 = expand_dims(axes = var_2908_axes_0, x = seg_149_cast_fp16)[name = tensor("op_2908_cast_fp16")]; + tensor var_2910_reps_0 = const()[name = tensor("op_2910_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2910_cast_fp16 = tile(reps = var_2910_reps_0, x = var_2908_cast_fp16)[name = tensor("op_2910_cast_fp16")]; + tensor var_2911 = const()[name = tensor("op_2911"), val = tensor([1, 128, -1])]; + tensor seg_151_cast_fp16 = reshape(shape = var_2911, x = var_2910_cast_fp16)[name = tensor("seg_151_cast_fp16")]; + tensor input_835_cast_fp16 = add(x = var_2900_cast_fp16, y = seg_151_cast_fp16)[name = tensor("input_835_cast_fp16")]; + tensor input_837_pad_type_0 = const()[name = tensor("input_837_pad_type_0"), val = tensor("valid")]; + tensor input_837_strides_0 = const()[name = tensor("input_837_strides_0"), val = tensor([1])]; + tensor input_837_pad_0 = const()[name = tensor("input_837_pad_0"), val = tensor([0, 0])]; + tensor input_837_dilations_0 = const()[name = tensor("input_837_dilations_0"), val = tensor([1])]; + tensor input_837_groups_0 = const()[name = tensor("input_837_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd2_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd2_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8837056)))]; + tensor net_xvector_block3_tdnnd2_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd2_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8853504)))]; + tensor 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("input_837_cast_fp16")]; + tensor input_839_cast_fp16 = relu(x = input_837_cast_fp16)[name = tensor("input_839_cast_fp16")]; + tensor input_841_pad_type_0 = const()[name = tensor("input_841_pad_type_0"), val = tensor("valid")]; + tensor input_841_strides_0 = const()[name = tensor("input_841_strides_0"), val = tensor([1])]; + tensor input_841_pad_0 = const()[name = tensor("input_841_pad_0"), val = tensor([0, 0])]; + tensor input_841_dilations_0 = const()[name = tensor("input_841_dilations_0"), val = tensor([1])]; + tensor input_841_groups_0 = const()[name = tensor("input_841_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd2_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd2_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8853696)))]; + tensor net_xvector_block3_tdnnd2_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd2_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8857856)))]; + tensor 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("input_841_cast_fp16")]; + tensor m_75_cast_fp16 = sigmoid(x = input_841_cast_fp16)[name = tensor("m_75_cast_fp16")]; + tensor var_2932_cast_fp16 = mul(x = y_75_cast_fp16, y = m_75_cast_fp16)[name = tensor("op_2932_cast_fp16")]; + tensor input_843_interleave_0 = const()[name = tensor("input_843_interleave_0"), val = tensor(false)]; + tensor input_843_cast_fp16 = concat(axis = var_11, interleave = input_843_interleave_0, values = (input_823_cast_fp16, var_2932_cast_fp16))[name = tensor("input_843_cast_fp16")]; + tensor net_xvector_block3_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd3_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8857984)))]; + tensor net_xvector_block3_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd3_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8859200)))]; + tensor net_xvector_block3_tdnnd3_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd3_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8860416)))]; + tensor net_xvector_block3_tdnnd3_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd3_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8861632)))]; + tensor 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("input_845_cast_fp16")]; + tensor input_847_cast_fp16 = relu(x = input_845_cast_fp16)[name = tensor("input_847_cast_fp16")]; + tensor input_849_pad_type_0 = const()[name = tensor("input_849_pad_type_0"), val = tensor("valid")]; + tensor input_849_strides_0 = const()[name = tensor("input_849_strides_0"), val = tensor([1])]; + tensor input_849_pad_0 = const()[name = tensor("input_849_pad_0"), val = tensor([0, 0])]; + tensor input_849_dilations_0 = const()[name = tensor("input_849_dilations_0"), val = tensor([1])]; + tensor input_849_groups_0 = const()[name = tensor("input_849_groups_0"), val = tensor(1)]; + tensor const_314_to_fp16 = const()[name = tensor("const_314_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8862848)))]; + tensor const_315_to_fp16 = const()[name = tensor("const_315_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9010368)))]; + tensor input_851_cast_fp16 = conv(bias = const_315_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_314_to_fp16, x = input_847_cast_fp16)[name = tensor("input_851_cast_fp16")]; + tensor input_853_cast_fp16 = relu(x = input_851_cast_fp16)[name = tensor("input_853_cast_fp16")]; + tensor y_77_pad_type_0 = const()[name = tensor("y_77_pad_type_0"), val = tensor("custom")]; + tensor y_77_pad_0 = const()[name = tensor("y_77_pad_0"), val = tensor([2, 2])]; + tensor y_77_dilations_0 = const()[name = tensor("y_77_dilations_0"), val = tensor([2])]; + tensor y_77_strides_0 = const()[name = tensor("y_77_strides_0"), val = tensor([1])]; + tensor y_77_groups_0 = const()[name = tensor("y_77_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd3_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd3_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9010688)))]; + tensor 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("y_77_cast_fp16")]; + tensor var_2969_axes_0 = const()[name = tensor("op_2969_axes_0"), val = tensor([-1])]; + tensor var_2969_keep_dims_0 = const()[name = tensor("op_2969_keep_dims_0"), val = tensor(true)]; + tensor 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("op_2969_cast_fp16")]; + tensor var_2970 = const()[name = tensor("op_2970"), val = tensor([100])]; + tensor var_2971 = const()[name = tensor("op_2971"), val = tensor([100])]; + tensor seg_153_pad_type_0 = const()[name = tensor("seg_153_pad_type_0"), val = tensor("custom")]; + tensor seg_153_pad_0 = const()[name = tensor("seg_153_pad_0"), val = tensor([0, 0])]; + tensor seg_153_exclude_padding_from_average_0 = const()[name = tensor("seg_153_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_153_ceil_mode_0 = const()[name = tensor("seg_153_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_153_cast_fp16")]; + tensor var_2977_axes_0 = const()[name = tensor("op_2977_axes_0"), val = tensor([-1])]; + tensor var_2977_cast_fp16 = expand_dims(axes = var_2977_axes_0, x = seg_153_cast_fp16)[name = tensor("op_2977_cast_fp16")]; + tensor var_2979_reps_0 = const()[name = tensor("op_2979_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_2979_cast_fp16 = tile(reps = var_2979_reps_0, x = var_2977_cast_fp16)[name = tensor("op_2979_cast_fp16")]; + tensor var_2980 = const()[name = tensor("op_2980"), val = tensor([1, 128, -1])]; + tensor seg_155_cast_fp16 = reshape(shape = var_2980, x = var_2979_cast_fp16)[name = tensor("seg_155_cast_fp16")]; + tensor input_855_cast_fp16 = add(x = var_2969_cast_fp16, y = seg_155_cast_fp16)[name = tensor("input_855_cast_fp16")]; + tensor input_857_pad_type_0 = const()[name = tensor("input_857_pad_type_0"), val = tensor("valid")]; + tensor input_857_strides_0 = const()[name = tensor("input_857_strides_0"), val = tensor([1])]; + tensor input_857_pad_0 = const()[name = tensor("input_857_pad_0"), val = tensor([0, 0])]; + tensor input_857_dilations_0 = const()[name = tensor("input_857_dilations_0"), val = tensor([1])]; + tensor input_857_groups_0 = const()[name = tensor("input_857_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd3_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd3_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9035328)))]; + tensor net_xvector_block3_tdnnd3_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd3_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9051776)))]; + tensor 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("input_857_cast_fp16")]; + tensor input_859_cast_fp16 = relu(x = input_857_cast_fp16)[name = tensor("input_859_cast_fp16")]; + tensor input_861_pad_type_0 = const()[name = tensor("input_861_pad_type_0"), val = tensor("valid")]; + tensor input_861_strides_0 = const()[name = tensor("input_861_strides_0"), val = tensor([1])]; + tensor input_861_pad_0 = const()[name = tensor("input_861_pad_0"), val = tensor([0, 0])]; + tensor input_861_dilations_0 = const()[name = tensor("input_861_dilations_0"), val = tensor([1])]; + tensor input_861_groups_0 = const()[name = tensor("input_861_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd3_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd3_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9051968)))]; + tensor net_xvector_block3_tdnnd3_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd3_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9056128)))]; + tensor 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("input_861_cast_fp16")]; + tensor m_77_cast_fp16 = sigmoid(x = input_861_cast_fp16)[name = tensor("m_77_cast_fp16")]; + tensor var_3001_cast_fp16 = mul(x = y_77_cast_fp16, y = m_77_cast_fp16)[name = tensor("op_3001_cast_fp16")]; + tensor input_863_interleave_0 = const()[name = tensor("input_863_interleave_0"), val = tensor(false)]; + tensor input_863_cast_fp16 = concat(axis = var_11, interleave = input_863_interleave_0, values = (input_843_cast_fp16, var_3001_cast_fp16))[name = tensor("input_863_cast_fp16")]; + tensor net_xvector_block3_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd4_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9056256)))]; + tensor net_xvector_block3_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd4_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9057536)))]; + tensor net_xvector_block3_tdnnd4_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd4_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9058816)))]; + tensor net_xvector_block3_tdnnd4_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd4_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9060096)))]; + tensor 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("input_865_cast_fp16")]; + tensor input_867_cast_fp16 = relu(x = input_865_cast_fp16)[name = tensor("input_867_cast_fp16")]; + tensor input_869_pad_type_0 = const()[name = tensor("input_869_pad_type_0"), val = tensor("valid")]; + tensor input_869_strides_0 = const()[name = tensor("input_869_strides_0"), val = tensor([1])]; + tensor input_869_pad_0 = const()[name = tensor("input_869_pad_0"), val = tensor([0, 0])]; + tensor input_869_dilations_0 = const()[name = tensor("input_869_dilations_0"), val = tensor([1])]; + tensor input_869_groups_0 = const()[name = tensor("input_869_groups_0"), val = tensor(1)]; + tensor const_316_to_fp16 = const()[name = tensor("const_316_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9061376)))]; + tensor const_317_to_fp16 = const()[name = tensor("const_317_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9217088)))]; + tensor input_871_cast_fp16 = conv(bias = const_317_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_316_to_fp16, x = input_867_cast_fp16)[name = tensor("input_871_cast_fp16")]; + tensor input_873_cast_fp16 = relu(x = input_871_cast_fp16)[name = tensor("input_873_cast_fp16")]; + tensor y_79_pad_type_0 = const()[name = tensor("y_79_pad_type_0"), val = tensor("custom")]; + tensor y_79_pad_0 = const()[name = tensor("y_79_pad_0"), val = tensor([2, 2])]; + tensor y_79_dilations_0 = const()[name = tensor("y_79_dilations_0"), val = tensor([2])]; + tensor y_79_strides_0 = const()[name = tensor("y_79_strides_0"), val = tensor([1])]; + tensor y_79_groups_0 = const()[name = tensor("y_79_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd4_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd4_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9217408)))]; + tensor 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("y_79_cast_fp16")]; + tensor var_3038_axes_0 = const()[name = tensor("op_3038_axes_0"), val = tensor([-1])]; + tensor var_3038_keep_dims_0 = const()[name = tensor("op_3038_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3038_cast_fp16")]; + tensor var_3039 = const()[name = tensor("op_3039"), val = tensor([100])]; + tensor var_3040 = const()[name = tensor("op_3040"), val = tensor([100])]; + tensor seg_157_pad_type_0 = const()[name = tensor("seg_157_pad_type_0"), val = tensor("custom")]; + tensor seg_157_pad_0 = const()[name = tensor("seg_157_pad_0"), val = tensor([0, 0])]; + tensor seg_157_exclude_padding_from_average_0 = const()[name = tensor("seg_157_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_157_ceil_mode_0 = const()[name = tensor("seg_157_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_157_cast_fp16")]; + tensor var_3046_axes_0 = const()[name = tensor("op_3046_axes_0"), val = tensor([-1])]; + tensor var_3046_cast_fp16 = expand_dims(axes = var_3046_axes_0, x = seg_157_cast_fp16)[name = tensor("op_3046_cast_fp16")]; + tensor var_3048_reps_0 = const()[name = tensor("op_3048_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3048_cast_fp16 = tile(reps = var_3048_reps_0, x = var_3046_cast_fp16)[name = tensor("op_3048_cast_fp16")]; + tensor var_3049 = const()[name = tensor("op_3049"), val = tensor([1, 128, -1])]; + tensor seg_159_cast_fp16 = reshape(shape = var_3049, x = var_3048_cast_fp16)[name = tensor("seg_159_cast_fp16")]; + tensor input_875_cast_fp16 = add(x = var_3038_cast_fp16, y = seg_159_cast_fp16)[name = tensor("input_875_cast_fp16")]; + tensor input_877_pad_type_0 = const()[name = tensor("input_877_pad_type_0"), val = tensor("valid")]; + tensor input_877_strides_0 = const()[name = tensor("input_877_strides_0"), val = tensor([1])]; + tensor input_877_pad_0 = const()[name = tensor("input_877_pad_0"), val = tensor([0, 0])]; + tensor input_877_dilations_0 = const()[name = tensor("input_877_dilations_0"), val = tensor([1])]; + tensor input_877_groups_0 = const()[name = tensor("input_877_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd4_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd4_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9242048)))]; + tensor net_xvector_block3_tdnnd4_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd4_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9258496)))]; + tensor 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("input_877_cast_fp16")]; + tensor input_879_cast_fp16 = relu(x = input_877_cast_fp16)[name = tensor("input_879_cast_fp16")]; + tensor input_881_pad_type_0 = const()[name = tensor("input_881_pad_type_0"), val = tensor("valid")]; + tensor input_881_strides_0 = const()[name = tensor("input_881_strides_0"), val = tensor([1])]; + tensor input_881_pad_0 = const()[name = tensor("input_881_pad_0"), val = tensor([0, 0])]; + tensor input_881_dilations_0 = const()[name = tensor("input_881_dilations_0"), val = tensor([1])]; + tensor input_881_groups_0 = const()[name = tensor("input_881_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd4_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd4_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9258688)))]; + tensor net_xvector_block3_tdnnd4_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd4_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9262848)))]; + tensor 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("input_881_cast_fp16")]; + tensor m_79_cast_fp16 = sigmoid(x = input_881_cast_fp16)[name = tensor("m_79_cast_fp16")]; + tensor var_3070_cast_fp16 = mul(x = y_79_cast_fp16, y = m_79_cast_fp16)[name = tensor("op_3070_cast_fp16")]; + tensor input_883_interleave_0 = const()[name = tensor("input_883_interleave_0"), val = tensor(false)]; + tensor input_883_cast_fp16 = concat(axis = var_11, interleave = input_883_interleave_0, values = (input_863_cast_fp16, var_3070_cast_fp16))[name = tensor("input_883_cast_fp16")]; + tensor net_xvector_block3_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd5_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9262976)))]; + tensor net_xvector_block3_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd5_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9264320)))]; + tensor net_xvector_block3_tdnnd5_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd5_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9265664)))]; + tensor net_xvector_block3_tdnnd5_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd5_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9267008)))]; + tensor 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("input_885_cast_fp16")]; + tensor input_887_cast_fp16 = relu(x = input_885_cast_fp16)[name = tensor("input_887_cast_fp16")]; + tensor input_889_pad_type_0 = const()[name = tensor("input_889_pad_type_0"), val = tensor("valid")]; + tensor input_889_strides_0 = const()[name = tensor("input_889_strides_0"), val = tensor([1])]; + tensor input_889_pad_0 = const()[name = tensor("input_889_pad_0"), val = tensor([0, 0])]; + tensor input_889_dilations_0 = const()[name = tensor("input_889_dilations_0"), val = tensor([1])]; + tensor input_889_groups_0 = const()[name = tensor("input_889_groups_0"), val = tensor(1)]; + tensor const_318_to_fp16 = const()[name = tensor("const_318_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9268352)))]; + tensor const_319_to_fp16 = const()[name = tensor("const_319_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9432256)))]; + tensor input_891_cast_fp16 = conv(bias = const_319_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_318_to_fp16, x = input_887_cast_fp16)[name = tensor("input_891_cast_fp16")]; + tensor input_893_cast_fp16 = relu(x = input_891_cast_fp16)[name = tensor("input_893_cast_fp16")]; + tensor y_81_pad_type_0 = const()[name = tensor("y_81_pad_type_0"), val = tensor("custom")]; + tensor y_81_pad_0 = const()[name = tensor("y_81_pad_0"), val = tensor([2, 2])]; + tensor y_81_dilations_0 = const()[name = tensor("y_81_dilations_0"), val = tensor([2])]; + tensor y_81_strides_0 = const()[name = tensor("y_81_strides_0"), val = tensor([1])]; + tensor y_81_groups_0 = const()[name = tensor("y_81_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd5_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd5_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9432576)))]; + tensor 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("y_81_cast_fp16")]; + tensor var_3107_axes_0 = const()[name = tensor("op_3107_axes_0"), val = tensor([-1])]; + tensor var_3107_keep_dims_0 = const()[name = tensor("op_3107_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3107_cast_fp16")]; + tensor var_3108 = const()[name = tensor("op_3108"), val = tensor([100])]; + tensor var_3109 = const()[name = tensor("op_3109"), val = tensor([100])]; + tensor seg_161_pad_type_0 = const()[name = tensor("seg_161_pad_type_0"), val = tensor("custom")]; + tensor seg_161_pad_0 = const()[name = tensor("seg_161_pad_0"), val = tensor([0, 0])]; + tensor seg_161_exclude_padding_from_average_0 = const()[name = tensor("seg_161_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_161_ceil_mode_0 = const()[name = tensor("seg_161_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_161_cast_fp16")]; + tensor var_3115_axes_0 = const()[name = tensor("op_3115_axes_0"), val = tensor([-1])]; + tensor var_3115_cast_fp16 = expand_dims(axes = var_3115_axes_0, x = seg_161_cast_fp16)[name = tensor("op_3115_cast_fp16")]; + tensor var_3117_reps_0 = const()[name = tensor("op_3117_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3117_cast_fp16 = tile(reps = var_3117_reps_0, x = var_3115_cast_fp16)[name = tensor("op_3117_cast_fp16")]; + tensor var_3118 = const()[name = tensor("op_3118"), val = tensor([1, 128, -1])]; + tensor seg_163_cast_fp16 = reshape(shape = var_3118, x = var_3117_cast_fp16)[name = tensor("seg_163_cast_fp16")]; + tensor input_895_cast_fp16 = add(x = var_3107_cast_fp16, y = seg_163_cast_fp16)[name = tensor("input_895_cast_fp16")]; + tensor input_897_pad_type_0 = const()[name = tensor("input_897_pad_type_0"), val = tensor("valid")]; + tensor input_897_strides_0 = const()[name = tensor("input_897_strides_0"), val = tensor([1])]; + tensor input_897_pad_0 = const()[name = tensor("input_897_pad_0"), val = tensor([0, 0])]; + tensor input_897_dilations_0 = const()[name = tensor("input_897_dilations_0"), val = tensor([1])]; + tensor input_897_groups_0 = const()[name = tensor("input_897_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd5_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd5_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9457216)))]; + tensor net_xvector_block3_tdnnd5_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd5_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9473664)))]; + tensor 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("input_897_cast_fp16")]; + tensor input_899_cast_fp16 = relu(x = input_897_cast_fp16)[name = tensor("input_899_cast_fp16")]; + tensor input_901_pad_type_0 = const()[name = tensor("input_901_pad_type_0"), val = tensor("valid")]; + tensor input_901_strides_0 = const()[name = tensor("input_901_strides_0"), val = tensor([1])]; + tensor input_901_pad_0 = const()[name = tensor("input_901_pad_0"), val = tensor([0, 0])]; + tensor input_901_dilations_0 = const()[name = tensor("input_901_dilations_0"), val = tensor([1])]; + tensor input_901_groups_0 = const()[name = tensor("input_901_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd5_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd5_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9473856)))]; + tensor net_xvector_block3_tdnnd5_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd5_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9478016)))]; + tensor 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("input_901_cast_fp16")]; + tensor m_81_cast_fp16 = sigmoid(x = input_901_cast_fp16)[name = tensor("m_81_cast_fp16")]; + tensor var_3139_cast_fp16 = mul(x = y_81_cast_fp16, y = m_81_cast_fp16)[name = tensor("op_3139_cast_fp16")]; + tensor input_903_interleave_0 = const()[name = tensor("input_903_interleave_0"), val = tensor(false)]; + tensor input_903_cast_fp16 = concat(axis = var_11, interleave = input_903_interleave_0, values = (input_883_cast_fp16, var_3139_cast_fp16))[name = tensor("input_903_cast_fp16")]; + tensor net_xvector_block3_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd6_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9478144)))]; + tensor net_xvector_block3_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd6_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9479552)))]; + tensor net_xvector_block3_tdnnd6_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd6_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9480960)))]; + tensor net_xvector_block3_tdnnd6_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd6_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9482368)))]; + tensor 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("input_905_cast_fp16")]; + tensor input_907_cast_fp16 = relu(x = input_905_cast_fp16)[name = tensor("input_907_cast_fp16")]; + tensor input_909_pad_type_0 = const()[name = tensor("input_909_pad_type_0"), val = tensor("valid")]; + tensor input_909_strides_0 = const()[name = tensor("input_909_strides_0"), val = tensor([1])]; + tensor input_909_pad_0 = const()[name = tensor("input_909_pad_0"), val = tensor([0, 0])]; + tensor input_909_dilations_0 = const()[name = tensor("input_909_dilations_0"), val = tensor([1])]; + tensor input_909_groups_0 = const()[name = tensor("input_909_groups_0"), val = tensor(1)]; + tensor const_320_to_fp16 = const()[name = tensor("const_320_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9483776)))]; + tensor const_321_to_fp16 = const()[name = tensor("const_321_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9655872)))]; + tensor input_911_cast_fp16 = conv(bias = const_321_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_320_to_fp16, x = input_907_cast_fp16)[name = tensor("input_911_cast_fp16")]; + tensor input_913_cast_fp16 = relu(x = input_911_cast_fp16)[name = tensor("input_913_cast_fp16")]; + tensor y_83_pad_type_0 = const()[name = tensor("y_83_pad_type_0"), val = tensor("custom")]; + tensor y_83_pad_0 = const()[name = tensor("y_83_pad_0"), val = tensor([2, 2])]; + tensor y_83_dilations_0 = const()[name = tensor("y_83_dilations_0"), val = tensor([2])]; + tensor y_83_strides_0 = const()[name = tensor("y_83_strides_0"), val = tensor([1])]; + tensor y_83_groups_0 = const()[name = tensor("y_83_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd6_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd6_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9656192)))]; + tensor 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("y_83_cast_fp16")]; + tensor var_3176_axes_0 = const()[name = tensor("op_3176_axes_0"), val = tensor([-1])]; + tensor var_3176_keep_dims_0 = const()[name = tensor("op_3176_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3176_cast_fp16")]; + tensor var_3177 = const()[name = tensor("op_3177"), val = tensor([100])]; + tensor var_3178 = const()[name = tensor("op_3178"), val = tensor([100])]; + tensor seg_165_pad_type_0 = const()[name = tensor("seg_165_pad_type_0"), val = tensor("custom")]; + tensor seg_165_pad_0 = const()[name = tensor("seg_165_pad_0"), val = tensor([0, 0])]; + tensor seg_165_exclude_padding_from_average_0 = const()[name = tensor("seg_165_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_165_ceil_mode_0 = const()[name = tensor("seg_165_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_165_cast_fp16")]; + tensor var_3184_axes_0 = const()[name = tensor("op_3184_axes_0"), val = tensor([-1])]; + tensor var_3184_cast_fp16 = expand_dims(axes = var_3184_axes_0, x = seg_165_cast_fp16)[name = tensor("op_3184_cast_fp16")]; + tensor var_3186_reps_0 = const()[name = tensor("op_3186_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3186_cast_fp16 = tile(reps = var_3186_reps_0, x = var_3184_cast_fp16)[name = tensor("op_3186_cast_fp16")]; + tensor var_3187 = const()[name = tensor("op_3187"), val = tensor([1, 128, -1])]; + tensor seg_167_cast_fp16 = reshape(shape = var_3187, x = var_3186_cast_fp16)[name = tensor("seg_167_cast_fp16")]; + tensor input_915_cast_fp16 = add(x = var_3176_cast_fp16, y = seg_167_cast_fp16)[name = tensor("input_915_cast_fp16")]; + tensor input_917_pad_type_0 = const()[name = tensor("input_917_pad_type_0"), val = tensor("valid")]; + tensor input_917_strides_0 = const()[name = tensor("input_917_strides_0"), val = tensor([1])]; + tensor input_917_pad_0 = const()[name = tensor("input_917_pad_0"), val = tensor([0, 0])]; + tensor input_917_dilations_0 = const()[name = tensor("input_917_dilations_0"), val = tensor([1])]; + tensor input_917_groups_0 = const()[name = tensor("input_917_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd6_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd6_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9680832)))]; + tensor net_xvector_block3_tdnnd6_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd6_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9697280)))]; + tensor 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("input_917_cast_fp16")]; + tensor input_919_cast_fp16 = relu(x = input_917_cast_fp16)[name = tensor("input_919_cast_fp16")]; + tensor input_921_pad_type_0 = const()[name = tensor("input_921_pad_type_0"), val = tensor("valid")]; + tensor input_921_strides_0 = const()[name = tensor("input_921_strides_0"), val = tensor([1])]; + tensor input_921_pad_0 = const()[name = tensor("input_921_pad_0"), val = tensor([0, 0])]; + tensor input_921_dilations_0 = const()[name = tensor("input_921_dilations_0"), val = tensor([1])]; + tensor input_921_groups_0 = const()[name = tensor("input_921_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd6_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd6_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9697472)))]; + tensor net_xvector_block3_tdnnd6_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd6_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9701632)))]; + tensor 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("input_921_cast_fp16")]; + tensor m_83_cast_fp16 = sigmoid(x = input_921_cast_fp16)[name = tensor("m_83_cast_fp16")]; + tensor var_3208_cast_fp16 = mul(x = y_83_cast_fp16, y = m_83_cast_fp16)[name = tensor("op_3208_cast_fp16")]; + tensor input_923_interleave_0 = const()[name = tensor("input_923_interleave_0"), val = tensor(false)]; + tensor input_923_cast_fp16 = concat(axis = var_11, interleave = input_923_interleave_0, values = (input_903_cast_fp16, var_3208_cast_fp16))[name = tensor("input_923_cast_fp16")]; + tensor net_xvector_block3_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd7_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9701760)))]; + tensor net_xvector_block3_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd7_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9703232)))]; + tensor net_xvector_block3_tdnnd7_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd7_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9704704)))]; + tensor net_xvector_block3_tdnnd7_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd7_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9706176)))]; + tensor 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("input_925_cast_fp16")]; + tensor input_927_cast_fp16 = relu(x = input_925_cast_fp16)[name = tensor("input_927_cast_fp16")]; + tensor input_929_pad_type_0 = const()[name = tensor("input_929_pad_type_0"), val = tensor("valid")]; + tensor input_929_strides_0 = const()[name = tensor("input_929_strides_0"), val = tensor([1])]; + tensor input_929_pad_0 = const()[name = tensor("input_929_pad_0"), val = tensor([0, 0])]; + tensor input_929_dilations_0 = const()[name = tensor("input_929_dilations_0"), val = tensor([1])]; + tensor input_929_groups_0 = const()[name = tensor("input_929_groups_0"), val = tensor(1)]; + tensor const_322_to_fp16 = const()[name = tensor("const_322_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9707648)))]; + tensor const_323_to_fp16 = const()[name = tensor("const_323_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9887936)))]; + tensor input_931_cast_fp16 = conv(bias = const_323_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_322_to_fp16, x = input_927_cast_fp16)[name = tensor("input_931_cast_fp16")]; + tensor input_933_cast_fp16 = relu(x = input_931_cast_fp16)[name = tensor("input_933_cast_fp16")]; + tensor y_85_pad_type_0 = const()[name = tensor("y_85_pad_type_0"), val = tensor("custom")]; + tensor y_85_pad_0 = const()[name = tensor("y_85_pad_0"), val = tensor([2, 2])]; + tensor y_85_dilations_0 = const()[name = tensor("y_85_dilations_0"), val = tensor([2])]; + tensor y_85_strides_0 = const()[name = tensor("y_85_strides_0"), val = tensor([1])]; + tensor y_85_groups_0 = const()[name = tensor("y_85_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd7_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd7_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9888256)))]; + tensor 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("y_85_cast_fp16")]; + tensor var_3245_axes_0 = const()[name = tensor("op_3245_axes_0"), val = tensor([-1])]; + tensor var_3245_keep_dims_0 = const()[name = tensor("op_3245_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3245_cast_fp16")]; + tensor var_3246 = const()[name = tensor("op_3246"), val = tensor([100])]; + tensor var_3247 = const()[name = tensor("op_3247"), val = tensor([100])]; + tensor seg_169_pad_type_0 = const()[name = tensor("seg_169_pad_type_0"), val = tensor("custom")]; + tensor seg_169_pad_0 = const()[name = tensor("seg_169_pad_0"), val = tensor([0, 0])]; + tensor seg_169_exclude_padding_from_average_0 = const()[name = tensor("seg_169_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_169_ceil_mode_0 = const()[name = tensor("seg_169_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_169_cast_fp16")]; + tensor var_3253_axes_0 = const()[name = tensor("op_3253_axes_0"), val = tensor([-1])]; + tensor var_3253_cast_fp16 = expand_dims(axes = var_3253_axes_0, x = seg_169_cast_fp16)[name = tensor("op_3253_cast_fp16")]; + tensor var_3255_reps_0 = const()[name = tensor("op_3255_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3255_cast_fp16 = tile(reps = var_3255_reps_0, x = var_3253_cast_fp16)[name = tensor("op_3255_cast_fp16")]; + tensor var_3256 = const()[name = tensor("op_3256"), val = tensor([1, 128, -1])]; + tensor seg_171_cast_fp16 = reshape(shape = var_3256, x = var_3255_cast_fp16)[name = tensor("seg_171_cast_fp16")]; + tensor input_935_cast_fp16 = add(x = var_3245_cast_fp16, y = seg_171_cast_fp16)[name = tensor("input_935_cast_fp16")]; + tensor input_937_pad_type_0 = const()[name = tensor("input_937_pad_type_0"), val = tensor("valid")]; + tensor input_937_strides_0 = const()[name = tensor("input_937_strides_0"), val = tensor([1])]; + tensor input_937_pad_0 = const()[name = tensor("input_937_pad_0"), val = tensor([0, 0])]; + tensor input_937_dilations_0 = const()[name = tensor("input_937_dilations_0"), val = tensor([1])]; + tensor input_937_groups_0 = const()[name = tensor("input_937_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd7_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd7_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9912896)))]; + tensor net_xvector_block3_tdnnd7_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd7_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9929344)))]; + tensor 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("input_937_cast_fp16")]; + tensor input_939_cast_fp16 = relu(x = input_937_cast_fp16)[name = tensor("input_939_cast_fp16")]; + tensor input_941_pad_type_0 = const()[name = tensor("input_941_pad_type_0"), val = tensor("valid")]; + tensor input_941_strides_0 = const()[name = tensor("input_941_strides_0"), val = tensor([1])]; + tensor input_941_pad_0 = const()[name = tensor("input_941_pad_0"), val = tensor([0, 0])]; + tensor input_941_dilations_0 = const()[name = tensor("input_941_dilations_0"), val = tensor([1])]; + tensor input_941_groups_0 = const()[name = tensor("input_941_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd7_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd7_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9929536)))]; + tensor net_xvector_block3_tdnnd7_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd7_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9933696)))]; + tensor 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("input_941_cast_fp16")]; + tensor m_85_cast_fp16 = sigmoid(x = input_941_cast_fp16)[name = tensor("m_85_cast_fp16")]; + tensor var_3277_cast_fp16 = mul(x = y_85_cast_fp16, y = m_85_cast_fp16)[name = tensor("op_3277_cast_fp16")]; + tensor input_943_interleave_0 = const()[name = tensor("input_943_interleave_0"), val = tensor(false)]; + tensor input_943_cast_fp16 = concat(axis = var_11, interleave = input_943_interleave_0, values = (input_923_cast_fp16, var_3277_cast_fp16))[name = tensor("input_943_cast_fp16")]; + tensor net_xvector_block3_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd8_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9933824)))]; + tensor net_xvector_block3_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd8_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9935360)))]; + tensor net_xvector_block3_tdnnd8_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd8_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9936896)))]; + tensor net_xvector_block3_tdnnd8_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd8_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9938432)))]; + tensor 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("input_945_cast_fp16")]; + tensor input_947_cast_fp16 = relu(x = input_945_cast_fp16)[name = tensor("input_947_cast_fp16")]; + tensor input_949_pad_type_0 = const()[name = tensor("input_949_pad_type_0"), val = tensor("valid")]; + tensor input_949_strides_0 = const()[name = tensor("input_949_strides_0"), val = tensor([1])]; + tensor input_949_pad_0 = const()[name = tensor("input_949_pad_0"), val = tensor([0, 0])]; + tensor input_949_dilations_0 = const()[name = tensor("input_949_dilations_0"), val = tensor([1])]; + tensor input_949_groups_0 = const()[name = tensor("input_949_groups_0"), val = tensor(1)]; + tensor const_324_to_fp16 = const()[name = tensor("const_324_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9939968)))]; + tensor const_325_to_fp16 = const()[name = tensor("const_325_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10128448)))]; + tensor input_951_cast_fp16 = conv(bias = const_325_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_324_to_fp16, x = input_947_cast_fp16)[name = tensor("input_951_cast_fp16")]; + tensor input_953_cast_fp16 = relu(x = input_951_cast_fp16)[name = tensor("input_953_cast_fp16")]; + tensor y_87_pad_type_0 = const()[name = tensor("y_87_pad_type_0"), val = tensor("custom")]; + tensor y_87_pad_0 = const()[name = tensor("y_87_pad_0"), val = tensor([2, 2])]; + tensor y_87_dilations_0 = const()[name = tensor("y_87_dilations_0"), val = tensor([2])]; + tensor y_87_strides_0 = const()[name = tensor("y_87_strides_0"), val = tensor([1])]; + tensor y_87_groups_0 = const()[name = tensor("y_87_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd8_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd8_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10128768)))]; + tensor 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("y_87_cast_fp16")]; + tensor var_3314_axes_0 = const()[name = tensor("op_3314_axes_0"), val = tensor([-1])]; + tensor var_3314_keep_dims_0 = const()[name = tensor("op_3314_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3314_cast_fp16")]; + tensor var_3315 = const()[name = tensor("op_3315"), val = tensor([100])]; + tensor var_3316 = const()[name = tensor("op_3316"), val = tensor([100])]; + tensor seg_173_pad_type_0 = const()[name = tensor("seg_173_pad_type_0"), val = tensor("custom")]; + tensor seg_173_pad_0 = const()[name = tensor("seg_173_pad_0"), val = tensor([0, 0])]; + tensor seg_173_exclude_padding_from_average_0 = const()[name = tensor("seg_173_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_173_ceil_mode_0 = const()[name = tensor("seg_173_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_173_cast_fp16")]; + tensor var_3322_axes_0 = const()[name = tensor("op_3322_axes_0"), val = tensor([-1])]; + tensor var_3322_cast_fp16 = expand_dims(axes = var_3322_axes_0, x = seg_173_cast_fp16)[name = tensor("op_3322_cast_fp16")]; + tensor var_3324_reps_0 = const()[name = tensor("op_3324_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3324_cast_fp16 = tile(reps = var_3324_reps_0, x = var_3322_cast_fp16)[name = tensor("op_3324_cast_fp16")]; + tensor var_3325 = const()[name = tensor("op_3325"), val = tensor([1, 128, -1])]; + tensor seg_175_cast_fp16 = reshape(shape = var_3325, x = var_3324_cast_fp16)[name = tensor("seg_175_cast_fp16")]; + tensor input_955_cast_fp16 = add(x = var_3314_cast_fp16, y = seg_175_cast_fp16)[name = tensor("input_955_cast_fp16")]; + tensor input_957_pad_type_0 = const()[name = tensor("input_957_pad_type_0"), val = tensor("valid")]; + tensor input_957_strides_0 = const()[name = tensor("input_957_strides_0"), val = tensor([1])]; + tensor input_957_pad_0 = const()[name = tensor("input_957_pad_0"), val = tensor([0, 0])]; + tensor input_957_dilations_0 = const()[name = tensor("input_957_dilations_0"), val = tensor([1])]; + tensor input_957_groups_0 = const()[name = tensor("input_957_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd8_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd8_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10153408)))]; + tensor net_xvector_block3_tdnnd8_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd8_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10169856)))]; + tensor 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("input_957_cast_fp16")]; + tensor input_959_cast_fp16 = relu(x = input_957_cast_fp16)[name = tensor("input_959_cast_fp16")]; + tensor input_961_pad_type_0 = const()[name = tensor("input_961_pad_type_0"), val = tensor("valid")]; + tensor input_961_strides_0 = const()[name = tensor("input_961_strides_0"), val = tensor([1])]; + tensor input_961_pad_0 = const()[name = tensor("input_961_pad_0"), val = tensor([0, 0])]; + tensor input_961_dilations_0 = const()[name = tensor("input_961_dilations_0"), val = tensor([1])]; + tensor input_961_groups_0 = const()[name = tensor("input_961_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd8_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd8_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10170048)))]; + tensor net_xvector_block3_tdnnd8_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd8_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10174208)))]; + tensor 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("input_961_cast_fp16")]; + tensor m_87_cast_fp16 = sigmoid(x = input_961_cast_fp16)[name = tensor("m_87_cast_fp16")]; + tensor var_3346_cast_fp16 = mul(x = y_87_cast_fp16, y = m_87_cast_fp16)[name = tensor("op_3346_cast_fp16")]; + tensor input_963_interleave_0 = const()[name = tensor("input_963_interleave_0"), val = tensor(false)]; + tensor input_963_cast_fp16 = concat(axis = var_11, interleave = input_963_interleave_0, values = (input_943_cast_fp16, var_3346_cast_fp16))[name = tensor("input_963_cast_fp16")]; + tensor net_xvector_block3_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd9_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10174336)))]; + tensor net_xvector_block3_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd9_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10175936)))]; + tensor net_xvector_block3_tdnnd9_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd9_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10177536)))]; + tensor net_xvector_block3_tdnnd9_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd9_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10179136)))]; + tensor 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("input_965_cast_fp16")]; + tensor input_967_cast_fp16 = relu(x = input_965_cast_fp16)[name = tensor("input_967_cast_fp16")]; + tensor input_969_pad_type_0 = const()[name = tensor("input_969_pad_type_0"), val = tensor("valid")]; + tensor input_969_strides_0 = const()[name = tensor("input_969_strides_0"), val = tensor([1])]; + tensor input_969_pad_0 = const()[name = tensor("input_969_pad_0"), val = tensor([0, 0])]; + tensor input_969_dilations_0 = const()[name = tensor("input_969_dilations_0"), val = tensor([1])]; + tensor input_969_groups_0 = const()[name = tensor("input_969_groups_0"), val = tensor(1)]; + tensor const_326_to_fp16 = const()[name = tensor("const_326_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10180736)))]; + tensor const_327_to_fp16 = const()[name = tensor("const_327_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10377408)))]; + tensor input_971_cast_fp16 = conv(bias = const_327_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_326_to_fp16, x = input_967_cast_fp16)[name = tensor("input_971_cast_fp16")]; + tensor input_973_cast_fp16 = relu(x = input_971_cast_fp16)[name = tensor("input_973_cast_fp16")]; + tensor y_89_pad_type_0 = const()[name = tensor("y_89_pad_type_0"), val = tensor("custom")]; + tensor y_89_pad_0 = const()[name = tensor("y_89_pad_0"), val = tensor([2, 2])]; + tensor y_89_dilations_0 = const()[name = tensor("y_89_dilations_0"), val = tensor([2])]; + tensor y_89_strides_0 = const()[name = tensor("y_89_strides_0"), val = tensor([1])]; + tensor y_89_groups_0 = const()[name = tensor("y_89_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd9_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd9_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10377728)))]; + tensor 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("y_89_cast_fp16")]; + tensor var_3383_axes_0 = const()[name = tensor("op_3383_axes_0"), val = tensor([-1])]; + tensor var_3383_keep_dims_0 = const()[name = tensor("op_3383_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3383_cast_fp16")]; + tensor var_3384 = const()[name = tensor("op_3384"), val = tensor([100])]; + tensor var_3385 = const()[name = tensor("op_3385"), val = tensor([100])]; + tensor seg_177_pad_type_0 = const()[name = tensor("seg_177_pad_type_0"), val = tensor("custom")]; + tensor seg_177_pad_0 = const()[name = tensor("seg_177_pad_0"), val = tensor([0, 0])]; + tensor seg_177_exclude_padding_from_average_0 = const()[name = tensor("seg_177_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_177_ceil_mode_0 = const()[name = tensor("seg_177_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_177_cast_fp16")]; + tensor var_3391_axes_0 = const()[name = tensor("op_3391_axes_0"), val = tensor([-1])]; + tensor var_3391_cast_fp16 = expand_dims(axes = var_3391_axes_0, x = seg_177_cast_fp16)[name = tensor("op_3391_cast_fp16")]; + tensor var_3393_reps_0 = const()[name = tensor("op_3393_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3393_cast_fp16 = tile(reps = var_3393_reps_0, x = var_3391_cast_fp16)[name = tensor("op_3393_cast_fp16")]; + tensor var_3394 = const()[name = tensor("op_3394"), val = tensor([1, 128, -1])]; + tensor seg_179_cast_fp16 = reshape(shape = var_3394, x = var_3393_cast_fp16)[name = tensor("seg_179_cast_fp16")]; + tensor input_975_cast_fp16 = add(x = var_3383_cast_fp16, y = seg_179_cast_fp16)[name = tensor("input_975_cast_fp16")]; + tensor input_977_pad_type_0 = const()[name = tensor("input_977_pad_type_0"), val = tensor("valid")]; + tensor input_977_strides_0 = const()[name = tensor("input_977_strides_0"), val = tensor([1])]; + tensor input_977_pad_0 = const()[name = tensor("input_977_pad_0"), val = tensor([0, 0])]; + tensor input_977_dilations_0 = const()[name = tensor("input_977_dilations_0"), val = tensor([1])]; + tensor input_977_groups_0 = const()[name = tensor("input_977_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd9_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd9_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10402368)))]; + tensor net_xvector_block3_tdnnd9_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd9_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10418816)))]; + tensor 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("input_977_cast_fp16")]; + tensor input_979_cast_fp16 = relu(x = input_977_cast_fp16)[name = tensor("input_979_cast_fp16")]; + tensor input_981_pad_type_0 = const()[name = tensor("input_981_pad_type_0"), val = tensor("valid")]; + tensor input_981_strides_0 = const()[name = tensor("input_981_strides_0"), val = tensor([1])]; + tensor input_981_pad_0 = const()[name = tensor("input_981_pad_0"), val = tensor([0, 0])]; + tensor input_981_dilations_0 = const()[name = tensor("input_981_dilations_0"), val = tensor([1])]; + tensor input_981_groups_0 = const()[name = tensor("input_981_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd9_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd9_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10419008)))]; + tensor net_xvector_block3_tdnnd9_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd9_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10423168)))]; + tensor 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("input_981_cast_fp16")]; + tensor m_89_cast_fp16 = sigmoid(x = input_981_cast_fp16)[name = tensor("m_89_cast_fp16")]; + tensor var_3415_cast_fp16 = mul(x = y_89_cast_fp16, y = m_89_cast_fp16)[name = tensor("op_3415_cast_fp16")]; + tensor input_983_interleave_0 = const()[name = tensor("input_983_interleave_0"), val = tensor(false)]; + tensor input_983_cast_fp16 = concat(axis = var_11, interleave = input_983_interleave_0, values = (input_963_cast_fp16, var_3415_cast_fp16))[name = tensor("input_983_cast_fp16")]; + tensor net_xvector_block3_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd10_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10423296)))]; + tensor net_xvector_block3_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd10_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10424960)))]; + tensor net_xvector_block3_tdnnd10_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd10_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10426624)))]; + tensor net_xvector_block3_tdnnd10_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd10_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10428288)))]; + tensor 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("input_985_cast_fp16")]; + tensor input_987_cast_fp16 = relu(x = input_985_cast_fp16)[name = tensor("input_987_cast_fp16")]; + tensor input_989_pad_type_0 = const()[name = tensor("input_989_pad_type_0"), val = tensor("valid")]; + tensor input_989_strides_0 = const()[name = tensor("input_989_strides_0"), val = tensor([1])]; + tensor input_989_pad_0 = const()[name = tensor("input_989_pad_0"), val = tensor([0, 0])]; + tensor input_989_dilations_0 = const()[name = tensor("input_989_dilations_0"), val = tensor([1])]; + tensor input_989_groups_0 = const()[name = tensor("input_989_groups_0"), val = tensor(1)]; + tensor const_328_to_fp16 = const()[name = tensor("const_328_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10429952)))]; + tensor const_329_to_fp16 = const()[name = tensor("const_329_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10634816)))]; + tensor input_991_cast_fp16 = conv(bias = const_329_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_328_to_fp16, x = input_987_cast_fp16)[name = tensor("input_991_cast_fp16")]; + tensor input_993_cast_fp16 = relu(x = input_991_cast_fp16)[name = tensor("input_993_cast_fp16")]; + tensor y_91_pad_type_0 = const()[name = tensor("y_91_pad_type_0"), val = tensor("custom")]; + tensor y_91_pad_0 = const()[name = tensor("y_91_pad_0"), val = tensor([2, 2])]; + tensor y_91_dilations_0 = const()[name = tensor("y_91_dilations_0"), val = tensor([2])]; + tensor y_91_strides_0 = const()[name = tensor("y_91_strides_0"), val = tensor([1])]; + tensor y_91_groups_0 = const()[name = tensor("y_91_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd10_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd10_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10635136)))]; + tensor 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("y_91_cast_fp16")]; + tensor var_3452_axes_0 = const()[name = tensor("op_3452_axes_0"), val = tensor([-1])]; + tensor var_3452_keep_dims_0 = const()[name = tensor("op_3452_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3452_cast_fp16")]; + tensor var_3453 = const()[name = tensor("op_3453"), val = tensor([100])]; + tensor var_3454 = const()[name = tensor("op_3454"), val = tensor([100])]; + tensor seg_181_pad_type_0 = const()[name = tensor("seg_181_pad_type_0"), val = tensor("custom")]; + tensor seg_181_pad_0 = const()[name = tensor("seg_181_pad_0"), val = tensor([0, 0])]; + tensor seg_181_exclude_padding_from_average_0 = const()[name = tensor("seg_181_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_181_ceil_mode_0 = const()[name = tensor("seg_181_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_181_cast_fp16")]; + tensor var_3460_axes_0 = const()[name = tensor("op_3460_axes_0"), val = tensor([-1])]; + tensor var_3460_cast_fp16 = expand_dims(axes = var_3460_axes_0, x = seg_181_cast_fp16)[name = tensor("op_3460_cast_fp16")]; + tensor var_3462_reps_0 = const()[name = tensor("op_3462_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3462_cast_fp16 = tile(reps = var_3462_reps_0, x = var_3460_cast_fp16)[name = tensor("op_3462_cast_fp16")]; + tensor var_3463 = const()[name = tensor("op_3463"), val = tensor([1, 128, -1])]; + tensor seg_183_cast_fp16 = reshape(shape = var_3463, x = var_3462_cast_fp16)[name = tensor("seg_183_cast_fp16")]; + tensor input_995_cast_fp16 = add(x = var_3452_cast_fp16, y = seg_183_cast_fp16)[name = tensor("input_995_cast_fp16")]; + tensor input_997_pad_type_0 = const()[name = tensor("input_997_pad_type_0"), val = tensor("valid")]; + tensor input_997_strides_0 = const()[name = tensor("input_997_strides_0"), val = tensor([1])]; + tensor input_997_pad_0 = const()[name = tensor("input_997_pad_0"), val = tensor([0, 0])]; + tensor input_997_dilations_0 = const()[name = tensor("input_997_dilations_0"), val = tensor([1])]; + tensor input_997_groups_0 = const()[name = tensor("input_997_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd10_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd10_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10659776)))]; + tensor net_xvector_block3_tdnnd10_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd10_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10676224)))]; + tensor 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("input_997_cast_fp16")]; + tensor input_999_cast_fp16 = relu(x = input_997_cast_fp16)[name = tensor("input_999_cast_fp16")]; + tensor input_1001_pad_type_0 = const()[name = tensor("input_1001_pad_type_0"), val = tensor("valid")]; + tensor input_1001_strides_0 = const()[name = tensor("input_1001_strides_0"), val = tensor([1])]; + tensor input_1001_pad_0 = const()[name = tensor("input_1001_pad_0"), val = tensor([0, 0])]; + tensor input_1001_dilations_0 = const()[name = tensor("input_1001_dilations_0"), val = tensor([1])]; + tensor input_1001_groups_0 = const()[name = tensor("input_1001_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd10_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd10_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10676416)))]; + tensor net_xvector_block3_tdnnd10_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd10_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10680576)))]; + tensor 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("input_1001_cast_fp16")]; + tensor m_91_cast_fp16 = sigmoid(x = input_1001_cast_fp16)[name = tensor("m_91_cast_fp16")]; + tensor var_3484_cast_fp16 = mul(x = y_91_cast_fp16, y = m_91_cast_fp16)[name = tensor("op_3484_cast_fp16")]; + tensor input_1003_interleave_0 = const()[name = tensor("input_1003_interleave_0"), val = tensor(false)]; + tensor input_1003_cast_fp16 = concat(axis = var_11, interleave = input_1003_interleave_0, values = (input_983_cast_fp16, var_3484_cast_fp16))[name = tensor("input_1003_cast_fp16")]; + tensor net_xvector_block3_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd11_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10680704)))]; + tensor net_xvector_block3_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd11_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10682432)))]; + tensor net_xvector_block3_tdnnd11_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd11_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10684160)))]; + tensor net_xvector_block3_tdnnd11_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd11_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10685888)))]; + tensor 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("input_1005_cast_fp16")]; + tensor input_1007_cast_fp16 = relu(x = input_1005_cast_fp16)[name = tensor("input_1007_cast_fp16")]; + tensor input_1009_pad_type_0 = const()[name = tensor("input_1009_pad_type_0"), val = tensor("valid")]; + tensor input_1009_strides_0 = const()[name = tensor("input_1009_strides_0"), val = tensor([1])]; + tensor input_1009_pad_0 = const()[name = tensor("input_1009_pad_0"), val = tensor([0, 0])]; + tensor input_1009_dilations_0 = const()[name = tensor("input_1009_dilations_0"), val = tensor([1])]; + tensor input_1009_groups_0 = const()[name = tensor("input_1009_groups_0"), val = tensor(1)]; + tensor const_330_to_fp16 = const()[name = tensor("const_330_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10687616)))]; + tensor const_331_to_fp16 = const()[name = tensor("const_331_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10900672)))]; + tensor input_1011_cast_fp16 = conv(bias = const_331_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_330_to_fp16, x = input_1007_cast_fp16)[name = tensor("input_1011_cast_fp16")]; + tensor input_1013_cast_fp16 = relu(x = input_1011_cast_fp16)[name = tensor("input_1013_cast_fp16")]; + tensor y_93_pad_type_0 = const()[name = tensor("y_93_pad_type_0"), val = tensor("custom")]; + tensor y_93_pad_0 = const()[name = tensor("y_93_pad_0"), val = tensor([2, 2])]; + tensor y_93_dilations_0 = const()[name = tensor("y_93_dilations_0"), val = tensor([2])]; + tensor y_93_strides_0 = const()[name = tensor("y_93_strides_0"), val = tensor([1])]; + tensor y_93_groups_0 = const()[name = tensor("y_93_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd11_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd11_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10900992)))]; + tensor 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("y_93_cast_fp16")]; + tensor var_3521_axes_0 = const()[name = tensor("op_3521_axes_0"), val = tensor([-1])]; + tensor var_3521_keep_dims_0 = const()[name = tensor("op_3521_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3521_cast_fp16")]; + tensor var_3522 = const()[name = tensor("op_3522"), val = tensor([100])]; + tensor var_3523 = const()[name = tensor("op_3523"), val = tensor([100])]; + tensor seg_185_pad_type_0 = const()[name = tensor("seg_185_pad_type_0"), val = tensor("custom")]; + tensor seg_185_pad_0 = const()[name = tensor("seg_185_pad_0"), val = tensor([0, 0])]; + tensor seg_185_exclude_padding_from_average_0 = const()[name = tensor("seg_185_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_185_ceil_mode_0 = const()[name = tensor("seg_185_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_185_cast_fp16")]; + tensor var_3529_axes_0 = const()[name = tensor("op_3529_axes_0"), val = tensor([-1])]; + tensor var_3529_cast_fp16 = expand_dims(axes = var_3529_axes_0, x = seg_185_cast_fp16)[name = tensor("op_3529_cast_fp16")]; + tensor var_3531_reps_0 = const()[name = tensor("op_3531_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3531_cast_fp16 = tile(reps = var_3531_reps_0, x = var_3529_cast_fp16)[name = tensor("op_3531_cast_fp16")]; + tensor var_3532 = const()[name = tensor("op_3532"), val = tensor([1, 128, -1])]; + tensor seg_187_cast_fp16 = reshape(shape = var_3532, x = var_3531_cast_fp16)[name = tensor("seg_187_cast_fp16")]; + tensor input_1015_cast_fp16 = add(x = var_3521_cast_fp16, y = seg_187_cast_fp16)[name = tensor("input_1015_cast_fp16")]; + tensor input_1017_pad_type_0 = const()[name = tensor("input_1017_pad_type_0"), val = tensor("valid")]; + tensor input_1017_strides_0 = const()[name = tensor("input_1017_strides_0"), val = tensor([1])]; + tensor input_1017_pad_0 = const()[name = tensor("input_1017_pad_0"), val = tensor([0, 0])]; + tensor input_1017_dilations_0 = const()[name = tensor("input_1017_dilations_0"), val = tensor([1])]; + tensor input_1017_groups_0 = const()[name = tensor("input_1017_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd11_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd11_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10925632)))]; + tensor net_xvector_block3_tdnnd11_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd11_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10942080)))]; + tensor 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("input_1017_cast_fp16")]; + tensor input_1019_cast_fp16 = relu(x = input_1017_cast_fp16)[name = tensor("input_1019_cast_fp16")]; + tensor input_1021_pad_type_0 = const()[name = tensor("input_1021_pad_type_0"), val = tensor("valid")]; + tensor input_1021_strides_0 = const()[name = tensor("input_1021_strides_0"), val = tensor([1])]; + tensor input_1021_pad_0 = const()[name = tensor("input_1021_pad_0"), val = tensor([0, 0])]; + tensor input_1021_dilations_0 = const()[name = tensor("input_1021_dilations_0"), val = tensor([1])]; + tensor input_1021_groups_0 = const()[name = tensor("input_1021_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd11_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd11_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10942272)))]; + tensor net_xvector_block3_tdnnd11_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd11_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10946432)))]; + tensor 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("input_1021_cast_fp16")]; + tensor m_93_cast_fp16 = sigmoid(x = input_1021_cast_fp16)[name = tensor("m_93_cast_fp16")]; + tensor var_3553_cast_fp16 = mul(x = y_93_cast_fp16, y = m_93_cast_fp16)[name = tensor("op_3553_cast_fp16")]; + tensor input_1023_interleave_0 = const()[name = tensor("input_1023_interleave_0"), val = tensor(false)]; + tensor input_1023_cast_fp16 = concat(axis = var_11, interleave = input_1023_interleave_0, values = (input_1003_cast_fp16, var_3553_cast_fp16))[name = tensor("input_1023_cast_fp16")]; + tensor net_xvector_block3_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd12_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10946560)))]; + tensor net_xvector_block3_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd12_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10948352)))]; + tensor net_xvector_block3_tdnnd12_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd12_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10950144)))]; + tensor net_xvector_block3_tdnnd12_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd12_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10951936)))]; + tensor 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("input_1025_cast_fp16")]; + tensor input_1027_cast_fp16 = relu(x = input_1025_cast_fp16)[name = tensor("input_1027_cast_fp16")]; + tensor input_1029_pad_type_0 = const()[name = tensor("input_1029_pad_type_0"), val = tensor("valid")]; + tensor input_1029_strides_0 = const()[name = tensor("input_1029_strides_0"), val = tensor([1])]; + tensor input_1029_pad_0 = const()[name = tensor("input_1029_pad_0"), val = tensor([0, 0])]; + tensor input_1029_dilations_0 = const()[name = tensor("input_1029_dilations_0"), val = tensor([1])]; + tensor input_1029_groups_0 = const()[name = tensor("input_1029_groups_0"), val = tensor(1)]; + tensor const_332_to_fp16 = const()[name = tensor("const_332_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10953728)))]; + tensor const_333_to_fp16 = const()[name = tensor("const_333_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11174976)))]; + tensor input_1031_cast_fp16 = conv(bias = const_333_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_332_to_fp16, x = input_1027_cast_fp16)[name = tensor("input_1031_cast_fp16")]; + tensor input_1033_cast_fp16 = relu(x = input_1031_cast_fp16)[name = tensor("input_1033_cast_fp16")]; + tensor y_95_pad_type_0 = const()[name = tensor("y_95_pad_type_0"), val = tensor("custom")]; + tensor y_95_pad_0 = const()[name = tensor("y_95_pad_0"), val = tensor([2, 2])]; + tensor y_95_dilations_0 = const()[name = tensor("y_95_dilations_0"), val = tensor([2])]; + tensor y_95_strides_0 = const()[name = tensor("y_95_strides_0"), val = tensor([1])]; + tensor y_95_groups_0 = const()[name = tensor("y_95_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd12_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd12_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11175296)))]; + tensor 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("y_95_cast_fp16")]; + tensor var_3590_axes_0 = const()[name = tensor("op_3590_axes_0"), val = tensor([-1])]; + tensor var_3590_keep_dims_0 = const()[name = tensor("op_3590_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3590_cast_fp16")]; + tensor var_3591 = const()[name = tensor("op_3591"), val = tensor([100])]; + tensor var_3592 = const()[name = tensor("op_3592"), val = tensor([100])]; + tensor seg_189_pad_type_0 = const()[name = tensor("seg_189_pad_type_0"), val = tensor("custom")]; + tensor seg_189_pad_0 = const()[name = tensor("seg_189_pad_0"), val = tensor([0, 0])]; + tensor seg_189_exclude_padding_from_average_0 = const()[name = tensor("seg_189_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_189_ceil_mode_0 = const()[name = tensor("seg_189_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_189_cast_fp16")]; + tensor var_3598_axes_0 = const()[name = tensor("op_3598_axes_0"), val = tensor([-1])]; + tensor var_3598_cast_fp16 = expand_dims(axes = var_3598_axes_0, x = seg_189_cast_fp16)[name = tensor("op_3598_cast_fp16")]; + tensor var_3600_reps_0 = const()[name = tensor("op_3600_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3600_cast_fp16 = tile(reps = var_3600_reps_0, x = var_3598_cast_fp16)[name = tensor("op_3600_cast_fp16")]; + tensor var_3601 = const()[name = tensor("op_3601"), val = tensor([1, 128, -1])]; + tensor seg_191_cast_fp16 = reshape(shape = var_3601, x = var_3600_cast_fp16)[name = tensor("seg_191_cast_fp16")]; + tensor input_1035_cast_fp16 = add(x = var_3590_cast_fp16, y = seg_191_cast_fp16)[name = tensor("input_1035_cast_fp16")]; + tensor input_1037_pad_type_0 = const()[name = tensor("input_1037_pad_type_0"), val = tensor("valid")]; + tensor input_1037_strides_0 = const()[name = tensor("input_1037_strides_0"), val = tensor([1])]; + tensor input_1037_pad_0 = const()[name = tensor("input_1037_pad_0"), val = tensor([0, 0])]; + tensor input_1037_dilations_0 = const()[name = tensor("input_1037_dilations_0"), val = tensor([1])]; + tensor input_1037_groups_0 = const()[name = tensor("input_1037_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd12_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd12_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11199936)))]; + tensor net_xvector_block3_tdnnd12_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd12_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11216384)))]; + tensor 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("input_1037_cast_fp16")]; + tensor input_1039_cast_fp16 = relu(x = input_1037_cast_fp16)[name = tensor("input_1039_cast_fp16")]; + tensor input_1041_pad_type_0 = const()[name = tensor("input_1041_pad_type_0"), val = tensor("valid")]; + tensor input_1041_strides_0 = const()[name = tensor("input_1041_strides_0"), val = tensor([1])]; + tensor input_1041_pad_0 = const()[name = tensor("input_1041_pad_0"), val = tensor([0, 0])]; + tensor input_1041_dilations_0 = const()[name = tensor("input_1041_dilations_0"), val = tensor([1])]; + tensor input_1041_groups_0 = const()[name = tensor("input_1041_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd12_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd12_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11216576)))]; + tensor net_xvector_block3_tdnnd12_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd12_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11220736)))]; + tensor 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("input_1041_cast_fp16")]; + tensor m_95_cast_fp16 = sigmoid(x = input_1041_cast_fp16)[name = tensor("m_95_cast_fp16")]; + tensor var_3622_cast_fp16 = mul(x = y_95_cast_fp16, y = m_95_cast_fp16)[name = tensor("op_3622_cast_fp16")]; + tensor input_1043_interleave_0 = const()[name = tensor("input_1043_interleave_0"), val = tensor(false)]; + tensor input_1043_cast_fp16 = concat(axis = var_11, interleave = input_1043_interleave_0, values = (input_1023_cast_fp16, var_3622_cast_fp16))[name = tensor("input_1043_cast_fp16")]; + tensor net_xvector_block3_tdnnd13_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd13_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11220864)))]; + tensor net_xvector_block3_tdnnd13_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd13_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11222720)))]; + tensor net_xvector_block3_tdnnd13_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd13_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11224576)))]; + tensor net_xvector_block3_tdnnd13_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd13_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11226432)))]; + tensor 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("input_1045_cast_fp16")]; + tensor input_1047_cast_fp16 = relu(x = input_1045_cast_fp16)[name = tensor("input_1047_cast_fp16")]; + tensor input_1049_pad_type_0 = const()[name = tensor("input_1049_pad_type_0"), val = tensor("valid")]; + tensor input_1049_strides_0 = const()[name = tensor("input_1049_strides_0"), val = tensor([1])]; + tensor input_1049_pad_0 = const()[name = tensor("input_1049_pad_0"), val = tensor([0, 0])]; + tensor input_1049_dilations_0 = const()[name = tensor("input_1049_dilations_0"), val = tensor([1])]; + tensor input_1049_groups_0 = const()[name = tensor("input_1049_groups_0"), val = tensor(1)]; + tensor const_334_to_fp16 = const()[name = tensor("const_334_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11228288)))]; + tensor const_335_to_fp16 = const()[name = tensor("const_335_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11457728)))]; + tensor input_1051_cast_fp16 = conv(bias = const_335_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_334_to_fp16, x = input_1047_cast_fp16)[name = tensor("input_1051_cast_fp16")]; + tensor input_1053_cast_fp16 = relu(x = input_1051_cast_fp16)[name = tensor("input_1053_cast_fp16")]; + tensor y_97_pad_type_0 = const()[name = tensor("y_97_pad_type_0"), val = tensor("custom")]; + tensor y_97_pad_0 = const()[name = tensor("y_97_pad_0"), val = tensor([2, 2])]; + tensor y_97_dilations_0 = const()[name = tensor("y_97_dilations_0"), val = tensor([2])]; + tensor y_97_strides_0 = const()[name = tensor("y_97_strides_0"), val = tensor([1])]; + tensor y_97_groups_0 = const()[name = tensor("y_97_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd13_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd13_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11458048)))]; + tensor 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("y_97_cast_fp16")]; + tensor var_3659_axes_0 = const()[name = tensor("op_3659_axes_0"), val = tensor([-1])]; + tensor var_3659_keep_dims_0 = const()[name = tensor("op_3659_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3659_cast_fp16")]; + tensor var_3660 = const()[name = tensor("op_3660"), val = tensor([100])]; + tensor var_3661 = const()[name = tensor("op_3661"), val = tensor([100])]; + tensor seg_193_pad_type_0 = const()[name = tensor("seg_193_pad_type_0"), val = tensor("custom")]; + tensor seg_193_pad_0 = const()[name = tensor("seg_193_pad_0"), val = tensor([0, 0])]; + tensor seg_193_exclude_padding_from_average_0 = const()[name = tensor("seg_193_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_193_ceil_mode_0 = const()[name = tensor("seg_193_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_193_cast_fp16")]; + tensor var_3667_axes_0 = const()[name = tensor("op_3667_axes_0"), val = tensor([-1])]; + tensor var_3667_cast_fp16 = expand_dims(axes = var_3667_axes_0, x = seg_193_cast_fp16)[name = tensor("op_3667_cast_fp16")]; + tensor var_3669_reps_0 = const()[name = tensor("op_3669_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3669_cast_fp16 = tile(reps = var_3669_reps_0, x = var_3667_cast_fp16)[name = tensor("op_3669_cast_fp16")]; + tensor var_3670 = const()[name = tensor("op_3670"), val = tensor([1, 128, -1])]; + tensor seg_195_cast_fp16 = reshape(shape = var_3670, x = var_3669_cast_fp16)[name = tensor("seg_195_cast_fp16")]; + tensor input_1055_cast_fp16 = add(x = var_3659_cast_fp16, y = seg_195_cast_fp16)[name = tensor("input_1055_cast_fp16")]; + tensor input_1057_pad_type_0 = const()[name = tensor("input_1057_pad_type_0"), val = tensor("valid")]; + tensor input_1057_strides_0 = const()[name = tensor("input_1057_strides_0"), val = tensor([1])]; + tensor input_1057_pad_0 = const()[name = tensor("input_1057_pad_0"), val = tensor([0, 0])]; + tensor input_1057_dilations_0 = const()[name = tensor("input_1057_dilations_0"), val = tensor([1])]; + tensor input_1057_groups_0 = const()[name = tensor("input_1057_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd13_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd13_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11482688)))]; + tensor net_xvector_block3_tdnnd13_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd13_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11499136)))]; + tensor 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("input_1057_cast_fp16")]; + tensor input_1059_cast_fp16 = relu(x = input_1057_cast_fp16)[name = tensor("input_1059_cast_fp16")]; + tensor input_1061_pad_type_0 = const()[name = tensor("input_1061_pad_type_0"), val = tensor("valid")]; + tensor input_1061_strides_0 = const()[name = tensor("input_1061_strides_0"), val = tensor([1])]; + tensor input_1061_pad_0 = const()[name = tensor("input_1061_pad_0"), val = tensor([0, 0])]; + tensor input_1061_dilations_0 = const()[name = tensor("input_1061_dilations_0"), val = tensor([1])]; + tensor input_1061_groups_0 = const()[name = tensor("input_1061_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd13_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd13_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11499328)))]; + tensor net_xvector_block3_tdnnd13_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd13_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11503488)))]; + tensor 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("input_1061_cast_fp16")]; + tensor m_97_cast_fp16 = sigmoid(x = input_1061_cast_fp16)[name = tensor("m_97_cast_fp16")]; + tensor var_3691_cast_fp16 = mul(x = y_97_cast_fp16, y = m_97_cast_fp16)[name = tensor("op_3691_cast_fp16")]; + tensor input_1063_interleave_0 = const()[name = tensor("input_1063_interleave_0"), val = tensor(false)]; + tensor input_1063_cast_fp16 = concat(axis = var_11, interleave = input_1063_interleave_0, values = (input_1043_cast_fp16, var_3691_cast_fp16))[name = tensor("input_1063_cast_fp16")]; + tensor net_xvector_block3_tdnnd14_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd14_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11503616)))]; + tensor net_xvector_block3_tdnnd14_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd14_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11505536)))]; + tensor net_xvector_block3_tdnnd14_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd14_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11507456)))]; + tensor net_xvector_block3_tdnnd14_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd14_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11509376)))]; + tensor 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("input_1065_cast_fp16")]; + tensor input_1067_cast_fp16 = relu(x = input_1065_cast_fp16)[name = tensor("input_1067_cast_fp16")]; + tensor input_1069_pad_type_0 = const()[name = tensor("input_1069_pad_type_0"), val = tensor("valid")]; + tensor input_1069_strides_0 = const()[name = tensor("input_1069_strides_0"), val = tensor([1])]; + tensor input_1069_pad_0 = const()[name = tensor("input_1069_pad_0"), val = tensor([0, 0])]; + tensor input_1069_dilations_0 = const()[name = tensor("input_1069_dilations_0"), val = tensor([1])]; + tensor input_1069_groups_0 = const()[name = tensor("input_1069_groups_0"), val = tensor(1)]; + tensor const_336_to_fp16 = const()[name = tensor("const_336_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11511296)))]; + tensor const_337_to_fp16 = const()[name = tensor("const_337_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11748928)))]; + tensor input_1071_cast_fp16 = conv(bias = const_337_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_336_to_fp16, x = input_1067_cast_fp16)[name = tensor("input_1071_cast_fp16")]; + tensor input_1073_cast_fp16 = relu(x = input_1071_cast_fp16)[name = tensor("input_1073_cast_fp16")]; + tensor y_99_pad_type_0 = const()[name = tensor("y_99_pad_type_0"), val = tensor("custom")]; + tensor y_99_pad_0 = const()[name = tensor("y_99_pad_0"), val = tensor([2, 2])]; + tensor y_99_dilations_0 = const()[name = tensor("y_99_dilations_0"), val = tensor([2])]; + tensor y_99_strides_0 = const()[name = tensor("y_99_strides_0"), val = tensor([1])]; + tensor y_99_groups_0 = const()[name = tensor("y_99_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd14_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd14_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11749248)))]; + tensor 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("y_99_cast_fp16")]; + tensor var_3728_axes_0 = const()[name = tensor("op_3728_axes_0"), val = tensor([-1])]; + tensor var_3728_keep_dims_0 = const()[name = tensor("op_3728_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3728_cast_fp16")]; + tensor var_3729 = const()[name = tensor("op_3729"), val = tensor([100])]; + tensor var_3730 = const()[name = tensor("op_3730"), val = tensor([100])]; + tensor seg_197_pad_type_0 = const()[name = tensor("seg_197_pad_type_0"), val = tensor("custom")]; + tensor seg_197_pad_0 = const()[name = tensor("seg_197_pad_0"), val = tensor([0, 0])]; + tensor seg_197_exclude_padding_from_average_0 = const()[name = tensor("seg_197_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_197_ceil_mode_0 = const()[name = tensor("seg_197_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_197_cast_fp16")]; + tensor var_3736_axes_0 = const()[name = tensor("op_3736_axes_0"), val = tensor([-1])]; + tensor var_3736_cast_fp16 = expand_dims(axes = var_3736_axes_0, x = seg_197_cast_fp16)[name = tensor("op_3736_cast_fp16")]; + tensor var_3738_reps_0 = const()[name = tensor("op_3738_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3738_cast_fp16 = tile(reps = var_3738_reps_0, x = var_3736_cast_fp16)[name = tensor("op_3738_cast_fp16")]; + tensor var_3739 = const()[name = tensor("op_3739"), val = tensor([1, 128, -1])]; + tensor seg_199_cast_fp16 = reshape(shape = var_3739, x = var_3738_cast_fp16)[name = tensor("seg_199_cast_fp16")]; + tensor input_1075_cast_fp16 = add(x = var_3728_cast_fp16, y = seg_199_cast_fp16)[name = tensor("input_1075_cast_fp16")]; + tensor input_1077_pad_type_0 = const()[name = tensor("input_1077_pad_type_0"), val = tensor("valid")]; + tensor input_1077_strides_0 = const()[name = tensor("input_1077_strides_0"), val = tensor([1])]; + tensor input_1077_pad_0 = const()[name = tensor("input_1077_pad_0"), val = tensor([0, 0])]; + tensor input_1077_dilations_0 = const()[name = tensor("input_1077_dilations_0"), val = tensor([1])]; + tensor input_1077_groups_0 = const()[name = tensor("input_1077_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd14_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd14_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11773888)))]; + tensor net_xvector_block3_tdnnd14_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd14_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11790336)))]; + tensor 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("input_1077_cast_fp16")]; + tensor input_1079_cast_fp16 = relu(x = input_1077_cast_fp16)[name = tensor("input_1079_cast_fp16")]; + tensor input_1081_pad_type_0 = const()[name = tensor("input_1081_pad_type_0"), val = tensor("valid")]; + tensor input_1081_strides_0 = const()[name = tensor("input_1081_strides_0"), val = tensor([1])]; + tensor input_1081_pad_0 = const()[name = tensor("input_1081_pad_0"), val = tensor([0, 0])]; + tensor input_1081_dilations_0 = const()[name = tensor("input_1081_dilations_0"), val = tensor([1])]; + tensor input_1081_groups_0 = const()[name = tensor("input_1081_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd14_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd14_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11790528)))]; + tensor net_xvector_block3_tdnnd14_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd14_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11794688)))]; + tensor 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("input_1081_cast_fp16")]; + tensor m_99_cast_fp16 = sigmoid(x = input_1081_cast_fp16)[name = tensor("m_99_cast_fp16")]; + tensor var_3760_cast_fp16 = mul(x = y_99_cast_fp16, y = m_99_cast_fp16)[name = tensor("op_3760_cast_fp16")]; + tensor input_1083_interleave_0 = const()[name = tensor("input_1083_interleave_0"), val = tensor(false)]; + tensor input_1083_cast_fp16 = concat(axis = var_11, interleave = input_1083_interleave_0, values = (input_1063_cast_fp16, var_3760_cast_fp16))[name = tensor("input_1083_cast_fp16")]; + tensor net_xvector_block3_tdnnd15_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd15_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11794816)))]; + tensor net_xvector_block3_tdnnd15_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd15_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11796800)))]; + tensor net_xvector_block3_tdnnd15_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd15_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11798784)))]; + tensor net_xvector_block3_tdnnd15_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd15_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11800768)))]; + tensor 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("input_1085_cast_fp16")]; + tensor input_1087_cast_fp16 = relu(x = input_1085_cast_fp16)[name = tensor("input_1087_cast_fp16")]; + tensor input_1089_pad_type_0 = const()[name = tensor("input_1089_pad_type_0"), val = tensor("valid")]; + tensor input_1089_strides_0 = const()[name = tensor("input_1089_strides_0"), val = tensor([1])]; + tensor input_1089_pad_0 = const()[name = tensor("input_1089_pad_0"), val = tensor([0, 0])]; + tensor input_1089_dilations_0 = const()[name = tensor("input_1089_dilations_0"), val = tensor([1])]; + tensor input_1089_groups_0 = const()[name = tensor("input_1089_groups_0"), val = tensor(1)]; + tensor const_338_to_fp16 = const()[name = tensor("const_338_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11802752)))]; + tensor const_339_to_fp16 = const()[name = tensor("const_339_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12048576)))]; + tensor input_1091_cast_fp16 = conv(bias = const_339_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_338_to_fp16, x = input_1087_cast_fp16)[name = tensor("input_1091_cast_fp16")]; + tensor input_1093_cast_fp16 = relu(x = input_1091_cast_fp16)[name = tensor("input_1093_cast_fp16")]; + tensor y_101_pad_type_0 = const()[name = tensor("y_101_pad_type_0"), val = tensor("custom")]; + tensor y_101_pad_0 = const()[name = tensor("y_101_pad_0"), val = tensor([2, 2])]; + tensor y_101_dilations_0 = const()[name = tensor("y_101_dilations_0"), val = tensor([2])]; + tensor y_101_strides_0 = const()[name = tensor("y_101_strides_0"), val = tensor([1])]; + tensor y_101_groups_0 = const()[name = tensor("y_101_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd15_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd15_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12048896)))]; + tensor 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("y_101_cast_fp16")]; + tensor var_3797_axes_0 = const()[name = tensor("op_3797_axes_0"), val = tensor([-1])]; + tensor var_3797_keep_dims_0 = const()[name = tensor("op_3797_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3797_cast_fp16")]; + tensor var_3798 = const()[name = tensor("op_3798"), val = tensor([100])]; + tensor var_3799 = const()[name = tensor("op_3799"), val = tensor([100])]; + tensor seg_201_pad_type_0 = const()[name = tensor("seg_201_pad_type_0"), val = tensor("custom")]; + tensor seg_201_pad_0 = const()[name = tensor("seg_201_pad_0"), val = tensor([0, 0])]; + tensor seg_201_exclude_padding_from_average_0 = const()[name = tensor("seg_201_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_201_ceil_mode_0 = const()[name = tensor("seg_201_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_201_cast_fp16")]; + tensor var_3805_axes_0 = const()[name = tensor("op_3805_axes_0"), val = tensor([-1])]; + tensor var_3805_cast_fp16 = expand_dims(axes = var_3805_axes_0, x = seg_201_cast_fp16)[name = tensor("op_3805_cast_fp16")]; + tensor var_3807_reps_0 = const()[name = tensor("op_3807_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3807_cast_fp16 = tile(reps = var_3807_reps_0, x = var_3805_cast_fp16)[name = tensor("op_3807_cast_fp16")]; + tensor var_3808 = const()[name = tensor("op_3808"), val = tensor([1, 128, -1])]; + tensor seg_203_cast_fp16 = reshape(shape = var_3808, x = var_3807_cast_fp16)[name = tensor("seg_203_cast_fp16")]; + tensor input_1095_cast_fp16 = add(x = var_3797_cast_fp16, y = seg_203_cast_fp16)[name = tensor("input_1095_cast_fp16")]; + tensor input_1097_pad_type_0 = const()[name = tensor("input_1097_pad_type_0"), val = tensor("valid")]; + tensor input_1097_strides_0 = const()[name = tensor("input_1097_strides_0"), val = tensor([1])]; + tensor input_1097_pad_0 = const()[name = tensor("input_1097_pad_0"), val = tensor([0, 0])]; + tensor input_1097_dilations_0 = const()[name = tensor("input_1097_dilations_0"), val = tensor([1])]; + tensor input_1097_groups_0 = const()[name = tensor("input_1097_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd15_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd15_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12073536)))]; + tensor net_xvector_block3_tdnnd15_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd15_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12089984)))]; + tensor 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("input_1097_cast_fp16")]; + tensor input_1099_cast_fp16 = relu(x = input_1097_cast_fp16)[name = tensor("input_1099_cast_fp16")]; + tensor input_1101_pad_type_0 = const()[name = tensor("input_1101_pad_type_0"), val = tensor("valid")]; + tensor input_1101_strides_0 = const()[name = tensor("input_1101_strides_0"), val = tensor([1])]; + tensor input_1101_pad_0 = const()[name = tensor("input_1101_pad_0"), val = tensor([0, 0])]; + tensor input_1101_dilations_0 = const()[name = tensor("input_1101_dilations_0"), val = tensor([1])]; + tensor input_1101_groups_0 = const()[name = tensor("input_1101_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd15_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd15_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12090176)))]; + tensor net_xvector_block3_tdnnd15_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd15_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12094336)))]; + tensor 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("input_1101_cast_fp16")]; + tensor m_101_cast_fp16 = sigmoid(x = input_1101_cast_fp16)[name = tensor("m_101_cast_fp16")]; + tensor var_3829_cast_fp16 = mul(x = y_101_cast_fp16, y = m_101_cast_fp16)[name = tensor("op_3829_cast_fp16")]; + tensor input_1103_interleave_0 = const()[name = tensor("input_1103_interleave_0"), val = tensor(false)]; + tensor input_1103_cast_fp16 = concat(axis = var_11, interleave = input_1103_interleave_0, values = (input_1083_cast_fp16, var_3829_cast_fp16))[name = tensor("input_1103_cast_fp16")]; + tensor net_xvector_block3_tdnnd16_nonlinear1_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd16_nonlinear1_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12094464)))]; + tensor net_xvector_block3_tdnnd16_nonlinear1_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd16_nonlinear1_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12096512)))]; + tensor net_xvector_block3_tdnnd16_nonlinear1_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd16_nonlinear1_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12098560)))]; + tensor net_xvector_block3_tdnnd16_nonlinear1_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd16_nonlinear1_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12100608)))]; + tensor 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("input_1105_cast_fp16")]; + tensor input_1107_cast_fp16 = relu(x = input_1105_cast_fp16)[name = tensor("input_1107_cast_fp16")]; + tensor input_1109_pad_type_0 = const()[name = tensor("input_1109_pad_type_0"), val = tensor("valid")]; + tensor input_1109_strides_0 = const()[name = tensor("input_1109_strides_0"), val = tensor([1])]; + tensor input_1109_pad_0 = const()[name = tensor("input_1109_pad_0"), val = tensor([0, 0])]; + tensor input_1109_dilations_0 = const()[name = tensor("input_1109_dilations_0"), val = tensor([1])]; + tensor input_1109_groups_0 = const()[name = tensor("input_1109_groups_0"), val = tensor(1)]; + tensor const_340_to_fp16 = const()[name = tensor("const_340_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12102656)))]; + tensor const_341_to_fp16 = const()[name = tensor("const_341_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12356672)))]; + tensor input_1111_cast_fp16 = conv(bias = const_341_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_340_to_fp16, x = input_1107_cast_fp16)[name = tensor("input_1111_cast_fp16")]; + tensor input_1113_cast_fp16 = relu(x = input_1111_cast_fp16)[name = tensor("input_1113_cast_fp16")]; + tensor y_pad_type_0 = const()[name = tensor("y_pad_type_0"), val = tensor("custom")]; + tensor y_pad_0 = const()[name = tensor("y_pad_0"), val = tensor([2, 2])]; + tensor y_dilations_0 = const()[name = tensor("y_dilations_0"), val = tensor([2])]; + tensor y_strides_0 = const()[name = tensor("y_strides_0"), val = tensor([1])]; + tensor y_groups_0 = const()[name = tensor("y_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd16_cam_layer_linear_local_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd16_cam_layer_linear_local_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12356992)))]; + tensor 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("y_cast_fp16")]; + tensor var_3866_axes_0 = const()[name = tensor("op_3866_axes_0"), val = tensor([-1])]; + tensor var_3866_keep_dims_0 = const()[name = tensor("op_3866_keep_dims_0"), val = tensor(true)]; + tensor 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("op_3866_cast_fp16")]; + tensor var_3867 = const()[name = tensor("op_3867"), val = tensor([100])]; + tensor var_3868 = const()[name = tensor("op_3868"), val = tensor([100])]; + tensor seg_205_pad_type_0 = const()[name = tensor("seg_205_pad_type_0"), val = tensor("custom")]; + tensor seg_205_pad_0 = const()[name = tensor("seg_205_pad_0"), val = tensor([0, 0])]; + tensor seg_205_exclude_padding_from_average_0 = const()[name = tensor("seg_205_exclude_padding_from_average_0"), val = tensor(false)]; + tensor seg_205_ceil_mode_0 = const()[name = tensor("seg_205_ceil_mode_0"), val = tensor(true)]; + tensor 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("seg_205_cast_fp16")]; + tensor var_3874_axes_0 = const()[name = tensor("op_3874_axes_0"), val = tensor([-1])]; + tensor var_3874_cast_fp16 = expand_dims(axes = var_3874_axes_0, x = seg_205_cast_fp16)[name = tensor("op_3874_cast_fp16")]; + tensor var_3876_reps_0 = const()[name = tensor("op_3876_reps_0"), val = tensor([1, 1, 1, 100])]; + tensor var_3876_cast_fp16 = tile(reps = var_3876_reps_0, x = var_3874_cast_fp16)[name = tensor("op_3876_cast_fp16")]; + tensor var_3877 = const()[name = tensor("op_3877"), val = tensor([1, 128, -1])]; + tensor seg_cast_fp16 = reshape(shape = var_3877, x = var_3876_cast_fp16)[name = tensor("seg_cast_fp16")]; + tensor input_1115_cast_fp16 = add(x = var_3866_cast_fp16, y = seg_cast_fp16)[name = tensor("input_1115_cast_fp16")]; + tensor input_1117_pad_type_0 = const()[name = tensor("input_1117_pad_type_0"), val = tensor("valid")]; + tensor input_1117_strides_0 = const()[name = tensor("input_1117_strides_0"), val = tensor([1])]; + tensor input_1117_pad_0 = const()[name = tensor("input_1117_pad_0"), val = tensor([0, 0])]; + tensor input_1117_dilations_0 = const()[name = tensor("input_1117_dilations_0"), val = tensor([1])]; + tensor input_1117_groups_0 = const()[name = tensor("input_1117_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd16_cam_layer_linear1_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd16_cam_layer_linear1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12381632)))]; + tensor net_xvector_block3_tdnnd16_cam_layer_linear1_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd16_cam_layer_linear1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12398080)))]; + tensor 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("input_1117_cast_fp16")]; + tensor input_1119_cast_fp16 = relu(x = input_1117_cast_fp16)[name = tensor("input_1119_cast_fp16")]; + tensor input_1121_pad_type_0 = const()[name = tensor("input_1121_pad_type_0"), val = tensor("valid")]; + tensor input_1121_strides_0 = const()[name = tensor("input_1121_strides_0"), val = tensor([1])]; + tensor input_1121_pad_0 = const()[name = tensor("input_1121_pad_0"), val = tensor([0, 0])]; + tensor input_1121_dilations_0 = const()[name = tensor("input_1121_dilations_0"), val = tensor([1])]; + tensor input_1121_groups_0 = const()[name = tensor("input_1121_groups_0"), val = tensor(1)]; + tensor net_xvector_block3_tdnnd16_cam_layer_linear2_weight_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd16_cam_layer_linear2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12398272)))]; + tensor net_xvector_block3_tdnnd16_cam_layer_linear2_bias_to_fp16 = const()[name = tensor("net_xvector_block3_tdnnd16_cam_layer_linear2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12402432)))]; + tensor 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("input_1121_cast_fp16")]; + tensor m_cast_fp16 = sigmoid(x = input_1121_cast_fp16)[name = tensor("m_cast_fp16")]; + tensor var_3898_cast_fp16 = mul(x = y_cast_fp16, y = m_cast_fp16)[name = tensor("op_3898_cast_fp16")]; + tensor input_1123_interleave_0 = const()[name = tensor("input_1123_interleave_0"), val = tensor(false)]; + tensor input_1123_cast_fp16 = concat(axis = var_11, interleave = input_1123_interleave_0, values = (input_1103_cast_fp16, var_3898_cast_fp16))[name = tensor("input_1123_cast_fp16")]; + tensor net_xvector_transit3_nonlinear_batchnorm_running_mean_to_fp16 = const()[name = tensor("net_xvector_transit3_nonlinear_batchnorm_running_mean_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12402560)))]; + tensor net_xvector_transit3_nonlinear_batchnorm_running_var_to_fp16 = const()[name = tensor("net_xvector_transit3_nonlinear_batchnorm_running_var_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12404672)))]; + tensor net_xvector_transit3_nonlinear_batchnorm_weight_to_fp16 = const()[name = tensor("net_xvector_transit3_nonlinear_batchnorm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12406784)))]; + tensor net_xvector_transit3_nonlinear_batchnorm_bias_to_fp16 = const()[name = tensor("net_xvector_transit3_nonlinear_batchnorm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12408896)))]; + tensor 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("input_1125_cast_fp16")]; + tensor input_1127_cast_fp16 = relu(x = input_1125_cast_fp16)[name = tensor("input_1127_cast_fp16")]; + tensor input_1129_pad_type_0 = const()[name = tensor("input_1129_pad_type_0"), val = tensor("valid")]; + tensor input_1129_strides_0 = const()[name = tensor("input_1129_strides_0"), val = tensor([1])]; + tensor input_1129_pad_0 = const()[name = tensor("input_1129_pad_0"), val = tensor([0, 0])]; + tensor input_1129_dilations_0 = const()[name = tensor("input_1129_dilations_0"), val = tensor([1])]; + tensor input_1129_groups_0 = const()[name = tensor("input_1129_groups_0"), val = tensor(1)]; + tensor const_342_to_fp16 = const()[name = tensor("const_342_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12411008)))]; + tensor const_343_to_fp16 = const()[name = tensor("const_343_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13459648)))]; + tensor input_1131_cast_fp16 = conv(bias = const_343_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_342_to_fp16, x = input_1127_cast_fp16)[name = tensor("input_1131_cast_fp16")]; + tensor x_3_cast_fp16 = relu(x = input_1131_cast_fp16)[name = tensor("x_3_cast_fp16")]; + tensor mean_axes_0 = const()[name = tensor("mean_axes_0"), val = tensor([-1])]; + tensor mean_keep_dims_0 = const()[name = tensor("mean_keep_dims_0"), val = tensor(false)]; + tensor mean_cast_fp16 = reduce_mean(axes = mean_axes_0, keep_dims = mean_keep_dims_0, x = x_3_cast_fp16)[name = tensor("mean_cast_fp16")]; + tensor reduce_mean_0_axes_0 = const()[name = tensor("reduce_mean_0_axes_0"), val = tensor([-1])]; + tensor reduce_mean_0_keep_dims_0 = const()[name = tensor("reduce_mean_0_keep_dims_0"), val = tensor(true)]; + tensor 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("reduce_mean_0_cast_fp16")]; + tensor sub_0_cast_fp16 = sub(x = x_3_cast_fp16, y = reduce_mean_0_cast_fp16)[name = tensor("sub_0_cast_fp16")]; + tensor square_0_cast_fp16 = square(x = sub_0_cast_fp16)[name = tensor("square_0_cast_fp16")]; + tensor reduce_mean_1_axes_0 = const()[name = tensor("reduce_mean_1_axes_0"), val = tensor([-1])]; + tensor reduce_mean_1_keep_dims_0 = const()[name = tensor("reduce_mean_1_keep_dims_0"), val = tensor(false)]; + tensor 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("reduce_mean_1_cast_fp16")]; + tensor real_div_0_to_fp16 = const()[name = tensor("real_div_0_to_fp16"), val = tensor(0x1.008p+0)]; + tensor mul_0_cast_fp16 = mul(x = reduce_mean_1_cast_fp16, y = real_div_0_to_fp16)[name = tensor("mul_0_cast_fp16")]; + tensor sqrt_0_cast_fp16 = sqrt(x = mul_0_cast_fp16)[name = tensor("sqrt_0_cast_fp16")]; + tensor x_interleave_0 = const()[name = tensor("x_interleave_0"), val = tensor(false)]; + tensor x_cast_fp16 = concat(axis = var_4, interleave = x_interleave_0, values = (mean_cast_fp16, sqrt_0_cast_fp16))[name = tensor("x_cast_fp16")]; + tensor input_1133_axes_0 = const()[name = tensor("input_1133_axes_0"), val = tensor([-1])]; + tensor input_1133_cast_fp16 = expand_dims(axes = input_1133_axes_0, x = x_cast_fp16)[name = tensor("input_1133_cast_fp16")]; + tensor var_3937_pad_type_0 = const()[name = tensor("op_3937_pad_type_0"), val = tensor("valid")]; + tensor var_3937_strides_0 = const()[name = tensor("op_3937_strides_0"), val = tensor([1])]; + tensor var_3937_pad_0 = const()[name = tensor("op_3937_pad_0"), val = tensor([0, 0])]; + tensor var_3937_dilations_0 = const()[name = tensor("op_3937_dilations_0"), val = tensor([1])]; + tensor var_3937_groups_0 = const()[name = tensor("op_3937_groups_0"), val = tensor(1)]; + tensor net_xvector_dense_linear_weight_to_fp16 = const()[name = tensor("net_xvector_dense_linear_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13460736)))]; + tensor 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("op_3937_cast_fp16")]; + tensor input_axes_0 = const()[name = tensor("input_axes_0"), val = tensor([-1])]; + tensor input_cast_fp16 = squeeze(axes = input_axes_0, x = var_3937_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor reshape_0_to_fp16 = const()[name = tensor("reshape_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13854016)))]; + tensor sub_2_cast_fp16 = sub(x = input_cast_fp16, y = reshape_0_to_fp16)[name = tensor("sub_2_cast_fp16")]; + tensor _inversed_3942_y_0_to_fp16 = const()[name = tensor("_inversed_3942_y_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13854464)))]; + tensor embedding = mul(x = sub_2_cast_fp16, y = _inversed_3942_y_0_to_fp16)[name = tensor("_inversed_3942_cast_fp16")]; + } -> (embedding); +} \ No newline at end of file