internal::MaxPoolGrad::DataFormat(data_format));
  grad_outputs->push_back(dx);
  return scope.status();
}
REGISTER_GRADIENT_OP("MaxPool", MaxPoolGradHelper);

Status MaxPoolGradV2Helper(const Scope& scope, const Operation& op,
                           const std::vector<Output>& grad_inputs,
                           std::vector<Output>* grad_outputs) {
  string data_format;
  string padding;

  Tensor x_init_value = Tensor(DT_FLOAT, x_shape);
  SetRandomValuesForMaxPooling<float>(&x_init_value);
  RunTest(x, x_init_value, y, y_shape);
}

TEST_F(NNGradTest, MaxPoolGradV2Helper) {
  TensorShape x_shape({1, 2, 2, 1});
  TensorShape y_shape({1, 1, 1, 1});
  auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape));
  // Setup window and strides so that we only do one MaxPool.