ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

  // Register and run a function which returns the sum of 3 variables.
  const string function_def = AddVariablesFunction();
  TFE_ContextAddFunctionDef(ctx, function_def.data(), function_def.size(),
                            status);
  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

  TFE_Op* func = TFE_NewOp(ctx, "AddVariablesFunction", status);

  }

  TFE_Op* matmul = nullptr;
  if (func) {
    const string matmul_device = remote_func_outputs ? task2_name : "";
    string function_def = MatMulFunction(matmul_device);
    TFE_ContextAddFunctionDef(ctx, function_def.data(), function_def.size(),
                              status);
    CHECK_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

    matmul = TFE_NewOp(ctx, "MatMulFunction", status);

  EXPECT_EQ(TF_UNAVAILABLE, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteOp(comm_op);

  const string& fdef1 = FunctionWithErrorOp("TestNonCommUnavailable");
  TFE_ContextAddFunctionDef(ctx, fdef1.data(), fdef1.size(), status);
  TFE_Op* fn1 = TFE_NewOp(ctx, "FunctionWithTestNonCommUnavailable", status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

// Add a function (serialized FunctionDef protocol buffer) to ctx so
// that it can be invoked using TFE_Execute.
TF_CAPI_EXPORT extern void TFE_ContextAddFunctionDef(
    TFE_Context* ctx, const char* serialized_function_def, size_t size,
    TF_Status* status);

// Adds a function (created from TF_GraphToFunction or

          unwrapped_ctx, tensorflow::unwrap(h), device_name, &status->status);

  if (status->status.ok()) {
    return tensorflow::wrap(result);
  }
  return nullptr;
}

void TFE_ContextAddFunctionDef(TFE_Context* ctx,
                               const char* serialized_function_def, size_t size,
                               TF_Status* status) {
  tensorflow::FunctionDef function_def;