std::unique_ptr<tensorflow::GrpcServer> worker_server1;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(
                  server_def, tensorflow::Env::Default(), &worker_server1)
                  .ok());
  ASSERT_TRUE(worker_server1->Start().ok());

  server_def.set_task_index(2);
  std::unique_ptr<tensorflow::GrpcServer> worker_server2;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(

  auto allocator = std::make_unique<AsyncValueAllocator>();
  tensorflow::Tensor tensor(allocator.get(), DT_FLOAT, {1});
  TF_ASSERT_OK_AND_ASSIGN(
      auto pjrt_client,
      xla::GetTfrtCpuClient(/*asynchronous=*/true, /*cpu_device_count=*/1));
  std::vector<int32_t> data(1, 0);
  xla::Shape shape = xla::ShapeUtil::MakeShape(xla::S32, {1});
  TF_ASSERT_OK_AND_ASSIGN(
      auto buffer,
      pjrt_client->BufferFromHostBuffer(

                       /*executing_eagerly*/ ::testing::Values(true, false)));
#else
INSTANTIATE_TEST_SUITE_P(
    UnifiedCAPI, CppGradients,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),
                       /*executing_eagerly*/ ::testing::Values(true, false)));
#endif
}  // namespace
}  // namespace internal

  tensorflow::FunctionDef fdef;
  status->status = tensorflow::GraphToFunctionDef(
      fn_body->graph, fn_name, append_hash_to_fn_name != 0,
      /*set_stateful_from_nodes=*/true,
      /*copy_placeholder_attrs_from_nodes=*/true, body_nodes, input_tensors,
      output_tensors, output_names_vec, control_output_nodes,
      control_output_names_vec, description, &fdef);
  if (TF_GetCode(status) != TF_OK) {
    return nullptr;

        //
        // TODO(allenl): We should have an async API that works with the
        // parallel device.
        device_(device),
        executor_(
            TFE_NewExecutor(is_async, /*enable_streaming_enqueue=*/true,
                            /*in_flight_nodes_limit=*/in_flight_nodes_limit)),
        op_(nullptr),
        thread_(tensorflow::Env::Default()->StartThread(
            tensorflow::ThreadOptions(), "parallel_device_execute",

  value_str.copy(static_cast<char*>(data), value_str.length(), 0);
  result->data = data;
  result->length = value_str.length();
  result->data_deallocator = [](void* data, size_t length) { free(data); };
  return result;
}

TF_Buffer* TF_CoordinationServiceGetKeyValue(const char* key, int64_t key_size,
                                             TF_CoordinationServiceAgent* agent,

      [gcs_file](const std::string& dir, GcsFileStat* stat, TF_Status* status) {
        auto children =
            GetChildrenBounded(gcs_file, dir, 1, true, true, status);
        if (TF_GetCode(status) != TF_OK) return;
        if (!children.empty()) {
          stat->base = {0, 0, true};
          return TF_SetStatus(status, TF_OK, "");
        } else {
          return TF_SetStatus(status, TF_INVALID_ARGUMENT, "Not a directory!");

    TF_SetStatus(status, TF_INVALID_ARGUMENT,
                 "op_to_reset should not be nullptr");
  }
}

void TFE_ContextEnableGraphCollection(TFE_Context* ctx) {
  tensorflow::unwrap(ctx)->SetShouldStoreGraphs(true);
}

void TFE_ContextDisableGraphCollection(TFE_Context* ctx) {
  tensorflow::unwrap(ctx)->SetShouldStoreGraphs(false);
}

uint64_t TFE_GetContextId(TFE_Context* ctx) {
  tensorflow::EagerContext* context =

  EXPECT_EQ(op_def.input_arg_size(), 0);
  EXPECT_EQ(op_def.output_arg_size(), 1);
  EXPECT_TRUE(op_def.is_stateful());

  TF_DeleteBuffer(buffer);
}

void AssertEqual(TF_Function* f1, TF_Function* f2) {
  string s1, s2;
  tensorflow::FunctionDef fdef1, fdef2;
  ASSERT_TRUE(GetFunctionDef(f1, &fdef1));
  ASSERT_TRUE(GetFunctionDef(f2, &fdef2));
  SerializeToStringDeterministic(fdef1, &s1);

                                /*transpose_a = */ true,
                                /*transpose_b = */ true, name_grad_A.c_str()));

      TF_RETURN_IF_ERROR(MatMul(ctx, upstream_grad, A.get(), &matmul_B_output,
                                /*transpose_a = */ true,
                                /*transpose_b = */ true, name_grad_B.c_str()));
    }

    // Gradient for A