auto y = Elu(scope_, x);
  Tensor x_init_value = test::AsTensor<float>(
      {-0.9f, -0.7f, -0.5f, -0.3f, -0.1f, 0.1f, 0.3f, 0.5f, 0.7f, 0.9f},
      {5, 2});
  RunTest(x, x_init_value, y, shape);
}

TEST_F(NNGradTest, SeluGrad) {
  TensorShape shape({5, 2});
  auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(shape));
  auto y = Selu(scope_, x);
  Tensor x_init_value = test::AsTensor<float>(

    EXPECT_LT(max_error, 1e-3);
  }

  void RunTest(const Output& x, const Tensor& x_init_value, const Output& y,
               const TensorShape& y_shape) {
    TF_ASSERT_OK(scope_.status());
    float max_error;
    TF_ASSERT_OK((ComputeGradientError<float, float, float>(
        scope_, x, x_init_value, y, y_shape, &max_error)));
    EXPECT_LT(max_error, 1e-3);
  }

  Scope scope_;
};

Status ComputeGradientError(const Scope& scope, const Output& x,
                            const Tensor& x_init_value, const Output& y,
                            const TensorShape& y_shape, JAC_T* max_error) {
  // Initialize 'x_data' from 'x_init_value'.
  std::vector<Tensor> x_datas(1, Tensor(x_init_value));
  // Compute gradient error.
  return ComputeGradientErrorInternal<X_T, Y_T, JAC_T>(