metagraph_def.ParseFromArray(metagraph->data, metagraph->length);
  TF_DeleteBuffer(metagraph);

  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  CSession csession(session);

  // Retrieve the regression signature from meta graph def.
  const auto signature_def_map = metagraph_def.signature_def();
  const auto signature_def = signature_def_map.at("regress_x_to_y");

#include "tensorflow/compiler/mlir/tensorflow/translate/tf_mlir_translate.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/core/protobuf/saver.pb.h"
#include "tsl/platform/errors.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {
namespace quantization {
namespace {

#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/op_def.pb.h"
#include "tensorflow/core/framework/op_def_builder.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/core/public/session.h"
#include "tensorflow/lite/c/c_api_types.h"
#include "tensorflow/lite/experimental/remat/metadata_util.h"
#include "tensorflow/lite/python/metrics/converter_error_data.pb.h"

  TFE_DeleteContext(ctx);
}

// This tests running the "serving_default" SignatureDefFunction from the
// VarsAndArithmeticObjectGraph savedmodel. Here's what the signature_defs
// protobuf in the metagraph looks like:
// signature_def: {
//   key  : "serving_default"
//   value: {
//     inputs: {
//       key  : "a"
//       value: {
//         name : "serving_default_a:0"
//         dtype: DT_FLOAT

saved_model_schema_version: 1
meta_graphs {
  meta_info_def {
    stripped_op_list {
      op {
        name: "Const"
        output_arg {
          name: "output"
          type_attr: "dtype"
        }
        attr {
          name: "value"
          type: "tensor"
        }
        attr {
          name: "dtype"
          type: "type"
        }
      }
      op {
        name: "Identity"
        input_arg {

  def _run_model_in_sess(self, model_dir, tags, signature_key, sample_inputs):
    with tensorflow.compat.v1.Session(graph=tensorflow.Graph()) as sess:
      meta_graph = saved_model_loader.load(sess, tags, export_dir=model_dir)
      signature_def = meta_graph.signature_def[signature_key]

      # DumpTensorOp only works in graph mode.
      # Execute the model using session to run DumpTensorOp.
      output_tensor_names = [

#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/platform/protobuf.h"
#include "tensorflow/core/platform/threadpool.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/core/protobuf/saved_object_graph.pb.h"
#include "tensorflow/core/protobuf/saver.pb.h"
#include "tensorflow/core/protobuf/struct.pb.h"

    *   TFRecordWriter now raises an error if .write() fails.
    *   TPU: More helpful error messages in TPUClusterResolvers.
    *   The legacy_init_op argument to SavedModelBuilder methods for adding
        MetaGraphs has been deprecated. Please use the equivalent main_op
        argument instead. As part of this, we now explicitly check for a single
        main_op or legacy_init_op at the time of SavedModel building, whereas