for (auto input_type : func_type.getInputs()) {
    tensorflow::TensorShape tensor_shape;
    xla::Shape xla_shape = xla::TypeToShape(input_type);
    TF_RETURN_IF_ERROR(tensorflow::TensorShape::BuildTensorShape(
        xla_shape.dimensions(), &tensor_shape));
    arg_shapes.emplace_back(tensor_shape);

    DataType dtype;
    TF_RETURN_IF_ERROR(ConvertToDataType(input_type, &dtype));

    Tensor* cpu_tensor, StatusCallback done) {
  DataType dtype = EncodePrimitiveTypeAsDataType(shape_.element_type()).value();
  TensorShape tensor_shape;
  Status status = XLAShapeToTensorShape(shape_, &tensor_shape);
  if (!status.ok()) {
    done(status);
    return;
  }

  *cpu_tensor = Tensor(dtype, tensor_shape);

  status = stream_->Memcpy(cpu_tensor->data(), device_memory_base_,
                           device_memory_base_.size());

#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_UTILS_CONVERT_TYPE_H_

#include "mlir/IR/Builders.h"  // from @llvm-project
#include "mlir/IR/Types.h"  // from @llvm-project
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/framework/types.pb.h"

namespace tensorflow {

using tsl::StatusOr;

// Converts the TensorFlow DataType 'dtype' into an MLIR (scalar) type.

==============================================================================*/

#include "tensorflow/cc/experimental/libtf/impl/tensor_spec.h"

#include "absl/hash/hash_testing.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/test.h"

namespace tf {
namespace libtf {
namespace impl {

TEST(TensorSpecTest, TestSupportsAbslHash) {

#include "tensorflow/cc/experimental/libtf/impl/scalars.h"
#include "tensorflow/cc/experimental/libtf/impl/string.h"
#include "tensorflow/cc/experimental/libtf/impl/tensor_spec.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/test.h"

namespace tf {
namespace libtf {
namespace impl {

TEST(OStreamTest, TestInt64) {
  Int64 x(42);

#include "tensorflow/c/eager/immediate_execution_operation.h"
#include "tensorflow/c/eager/immediate_execution_tensor_handle.h"
#include "tensorflow/core/framework/resource_handle.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/gtl/inlined_vector.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
#include "tensorflow/core/platform/errors.h"

#include "mlir/IR/BuiltinTypes.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"

namespace mlir {
namespace TFL {

bool IsQuantized(const tflite::TensorT& tensor);

absl::StatusOr<mlir::quant::QuantizedType> GetQuantizedType(
    const tflite::TensorT& tensor, mlir::Builder builder,

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_attributes.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/protobuf/struct.pb.h"

namespace tensorflow {

using tsl::StatusOr;

// Converts an TensorFlow tensor proto into an MLIR elements attribute.

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_attributes.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/mangling_util.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/platform/status.h"
#include "tsl/platform/statusor.h"

namespace mlir {
namespace TFL {

absl::StatusOr<TypedAttr> CreateTypedAttr(ShapedType shaped_type, int value) {

#include "tensorflow/compiler/mlir/tensorflow/translate/tf_mlir_translate.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/convert_type.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/status.h"
#include "tsl/platform/errors.h"
#include "tfrt/bef_converter/mlir_to_bef.h"  // from @tf_runtime

namespace tensorflow {