using tensorflow::PartialTensorShape;
using tensorflow::RunMetadata;
using tensorflow::RunOptions;
using tensorflow::Session;
using tensorflow::Status;
using tensorflow::string;
using tensorflow::Tensor;
using tensorflow::TensorId;
using tensorflow::TensorShapeProto;
using tensorflow::VersionDef;
using tensorflow::errors::FailedPrecondition;
using tensorflow::errors::InvalidArgument;
using tensorflow::errors::OutOfRange;

  // Rename local device
  // This server def has the task index set to 0.
  string serialized = server_def.SerializeAsString();
  TFE_ContextSetServerDef(ctx, 0, serialized.data(), serialized.size(), status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  const string dev1_name =
      absl::StrCat("/job:", first_name, "/replica:0/task:0/device:CPU:0");

// =============================================================================

using tensorflow::AbstractContext;
using tensorflow::AbstractTensorHandle;
using tensorflow::dyn_cast;
using tensorflow::ImmediateExecutionContext;
using tensorflow::ImmediateExecutionTensorHandle;
using tensorflow::string;
using tensorflow::unwrap;
using tensorflow::wrap;
using tensorflow::strings::StrCat;

#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace parallel_device {

using ::testing::ElementsAre;
using ::testing::HasSubstr;

TEST(PARALLEL_DEVICE_LIB, TestOpWithError) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);

#include "tensorflow/core/protobuf/config.pb.h"
#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

namespace {

using ::tensorflow::string;

void TestRemoteExecute(bool async) {
  tensorflow::ServerDef server_def = GetServerDef(2);

  // This server def has the task index set to 0.
  string serialized = server_def.SerializeAsString();

  server_def.set_task_index(1);

                     TF_Status* status) {
  using tensorflow::NodeDef;
  using tensorflow::OpRegistrationData;
  using tensorflow::Tensor;
  using tensorflow::shape_inference::DimensionHandle;
  using tensorflow::shape_inference::InferenceContext;
  using tensorflow::shape_inference::ShapeAndType;
  using tensorflow::shape_inference::ShapeHandle;

  const int num_inputs = input_shapes->num_items;

#include <dirent.h>
#include <errno.h>
#include <fcntl.h>
#include <limits.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <sys/mman.h>
#include <sys/stat.h>
#include <unistd.h>

#include "tensorflow/c/experimental/filesystem/filesystem_interface.h"

  if (ret) ret = attr_value->ParseFromArray(buffer->data, buffer->length);
  TF_DeleteBuffer(buffer);
  return ret;
}

std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def) {
  std::vector<std::pair<string, string>> grads;
  for (const tensorflow::GradientDef& grad : graph_def.library().gradient()) {
    grads.emplace_back(grad.function_name(), grad.gradient_func());
  }

namespace tensorflow {

std::string ImmediateExecutionTensorHandle::DebugString() const {
  PartialTensorShape shape;
  std::string shape_string;
  if (Shape(&shape).ok()) {
    shape_string = shape.DebugString();
  } else {
    shape_string = "<error computing shape>";
  }
  std::string value_string;
  if (!SummarizeValue(value_string).ok()) {
    value_string = "<error computing value>";
  }

  TF_SetStatus(status, TF_OK, "");
  const std::unordered_set<std::string>& nodes =
      reinterpret_cast<const tensorflow::grappler::GrapplerItem*>(item)
          ->NodesToPreserve();
  *num_values = nodes.size();
  *storage_size = 0;
  for (const std::string& str : nodes) {
    *storage_size += str.size();
  }
}