// Store current value of 'x' at 'r'.
        X_T v = x_data_flat(r);
        // Evaluate at positive delta.
        x_data_flat(r) = v + x_delta;
        std::vector<Tensor> y_pos;
        TF_RETURN_IF_ERROR(EvaluateGraph(&session, xs, ys, x_datas, &y_pos));
        // Evaluate at negative delta.
        x_data_flat(r) = v - x_delta;
        std::vector<Tensor> y_neg;

    TensorShape shape({2, 3, 2});
    auto x = Placeholder(scope_, x_type, Placeholder::Shape(shape));
    Tensor x_data(x_type, shape);
    auto x_data_flat = x_data.flat<X_T>();
    for (int i = 0; i < x_data_flat.size(); ++i) {
      x_data_flat(i) = x_fn(i);
    }

    Output y;
    switch (op_type) {
      using namespace ops;  // NOLINT(build/namespaces)
      case ABS:
        y = Abs(scope_, x);

  template <typename T>
  Tensor MakeData(const TensorShape& data_shape) {
    DataType data_type = DataTypeToEnum<T>::v();
    Tensor data(data_type, data_shape);
    auto data_flat = data.flat<T>();
    for (int i = 0; i < data_flat.size(); ++i) {
      data_flat(i) = T(i);
    }
    return data;
  }

  template <typename T>
  void MakeOp(const OpType op_type, const Tensor& x_data, const Input& y_shape,