// TF_FunctionImportFunctionDef) to the context, allowing it to be executed with
// TFE_Execute by creating an op with the same name as the function.
TF_CAPI_EXPORT extern void TFE_ContextAddFunction(TFE_Context* ctx,
                                                  TF_Function* function,
                                                  TF_Status* status);

  TFE_ContextOptions* opts = TFE_NewContextOptions();
  TFE_Context* ctx = TFE_NewContext(opts, status);
  ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
  TFE_DeleteContextOptions(opts);
  TFE_ContextAddFunction(ctx, fn, status);
  ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
  TF_DeleteFunction(fn);

  for (bool async : {false, true, false}) {

          /* opts */ nullptr, /* description */ "", /* status */ status),
      TF_DeleteFunction);
  if (TF_GetCode(status) != TF_OK) return;
  TFE_ContextAddFunction(context, function.get(), status);
}

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

    return;
  }

  AnnotateEagerRuntimeConstructionContext(function_def);
  status->status = tensorflow::unwrap(ctx)->AddFunctionDef(function_def);
}

void TFE_ContextAddFunction(TFE_Context* ctx, TF_Function* function,
                            TF_Status* status) {
  auto fdef_or = function->record->mutable_fdef();
  if (!fdef_or.ok()) {
    status->status = fdef_or.status();