when (filePropertyType) {
                    OutputFilePropertyType.DIRECTORY -> dir(pack(propertyValue))
                    OutputFilePropertyType.DIRECTORIES -> dirs(pack(propertyValue))
                    OutputFilePropertyType.FILE -> file(pack(propertyValue))
                    OutputFilePropertyType.FILES -> files(pack(propertyValue))
                }
            }.run {
                withPropertyName(propertyName)

  // Import input_model to a MLIR module
  flatbuffers::FlatBufferBuilder input_builder;
  flatbuffers::Offset<tflite::Model> input_model_location =
      tflite::Model::Pack(input_builder, &input_model);
  tflite::FinishModelBuffer(input_builder, input_model_location);

  std::string serialized_model(
      reinterpret_cast<const char*>(input_builder.GetBufferPointer()),

        "//tensorflow/lite/tools/optimize:testdata/mixed16x8.bin",
        "//tensorflow/lite/tools/optimize:testdata/multi_input_add_reshape.bin",
        "//tensorflow/lite/tools/optimize:testdata/pack.bin",
        "//tensorflow/lite/tools/optimize:testdata/single_avg_pool_min_minus_5_max_plus_5.bin",
        "//tensorflow/lite/tools/optimize:testdata/single_conv_no_bias.bin",

  %2 = "tfl.add"(%arg0, %arg3) {fused_activation_function = "RELU6", per_device_costs = {CPU = 5.0 : f32, GPU = 1.0 : f32}, tac.device = "GPU"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
  %3 = "tfl.pack"(%1, %2) {axis = 0 : i32, per_device_costs = {CPU = 2.0 : f32, GPU = -1.0 : f32}, values_count = 2 : i32, tac.device = "CPU"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<2x1xf32>
  func.return %3 : tensor<2x1xf32>
})";

  // CHECK: "tfl.pack"(%arg0, %arg1) <{axis = 0 : i32, values_count = 2 : i32}>
  %0 = "tfl.pack"(%arg0, %arg1) {axis = 0 : i32, values_count = 2 : i32} : (tensor<2x!quant.uniform<i8:f32, 0.1>>, tensor<2x!quant.uniform<i8:f32, 0.1>>) -> tensor<2x2x!quant.uniform<i8:f32, 0.1>>
  func.return %0 : tensor<2x2x!quant.uniform<i8:f32, 0.1>>
}

// -----

  // Import input_model to a MLIR module
  flatbuffers::FlatBufferBuilder input_builder;
  flatbuffers::Offset<tflite::Model> input_model_location = tflite::Model::Pack(
      input_builder, CreateMutableModelFromFile(input_model).get());
  tflite::FinishModelBuffer(input_builder, input_model_location);

  std::string serialized_model(

	github.com/peterbourgon/diskv v2.0.1+incompatible // indirect
	github.com/pkg/errors v0.9.1 // indirect
	github.com/planetscale/vtprotobuf v0.6.1-0.20240319094008-0393e58bdf10 // indirect
	github.com/quic-go/qpack v0.4.0 // indirect
	github.com/rivo/uniseg v0.4.6 // indirect
	github.com/rogpeppe/go-internal v1.12.0 // indirect
	github.com/russross/blackfriday/v2 v2.1.0 // indirect
	github.com/sagikazarmark/locafero v0.4.0 // indirect

    auto result_ty = tensorflow::GetTypeFromTFTensorShape(
        result_shape, list_element_ty.getElementType());

    // If the list is empty, directly create the final result instead of
    // creating the tf.Pack op. tf.Pack op requires at least one operand.
    if (tensors.empty()) {
      tensorflow::Tensor tensor(list->element_dtype,
                                tensorflow::TensorShape(result_shape));

  // CHECK:  return
}

func.func @pack2Tensors(%arg0: tensor<2xi32>, %arg1: tensor<2xi32>) -> tensor<2x2xi32> {
  %0 = "tf.Pack"(%arg0, %arg1) : (tensor<2xi32>, tensor<2xi32>) -> tensor<2x2xi32>
  func.return %0 : tensor<2x2xi32>

// CHECK-LABEL: pack2Tensors
// CHECK: "tfl.pack"(%arg0, %arg1) <{axis = 0 : i32, values_count = 2 : i32}> : (tensor<2xi32>, tensor<2xi32>) -> tensor<2x2xi32>
}

	}

	// Pack into archive in objdir directory.
	// If the Go compiler wrote an archive, we only need to add the
	// object files for non-Go sources to the archive.
	// If the Go compiler wrote an archive and the package is entirely
	// Go sources, there is no pack to execute at all.
	if len(objects) > 0 {
		if err := BuildToolchain.pack(b, a, objpkg, objects); err != nil {
			return err
		}