#include "tensorflow/core/common_runtime/eval_const_tensor.h"
#include "tensorflow/core/common_runtime/graph_constructor.h"
#include "tensorflow/core/common_runtime/shape_refiner.h"
#include "tensorflow/core/config/flag_defs.h"
#include "tensorflow/core/config/flags.h"
#include "tensorflow/core/framework/allocation_description.pb.h"
#include "tensorflow/core/framework/attr_value_util.h"
#include "tensorflow/core/framework/cpp_shape_inference.pb.h"

    // These XLA flags are needed to trigger XLA properly from C (more generally
    // non-Python) clients. If this API is called again with `enable` set to
    // false, it is safe to keep these flag values as is.
    tensorflow::MarkForCompilationPassFlags* flags =
        tensorflow::GetMarkForCompilationPassFlags();
    flags->tf_xla_cpu_global_jit = true;
    flags->tf_xla_min_cluster_size = 1;
  } else {

#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace gradients {
namespace internal {
namespace {
using std::vector;

class CustomGradientTest
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());

#include "tensorflow/c/experimental/gradients/array_grad.h"

#include "tensorflow/c/eager/abstract_context.h"

namespace tensorflow {
namespace gradients {
namespace {
class IdentityNGradientFunction : public GradientFunction {
 public:
  Status Compute(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> grad_outputs,

                     absl::Span<AbstractTensorHandle* const> inputs,
                     absl::Span<AbstractTensorHandle*> outputs) {
  return ops::DivNoNan(ctx, inputs[0], inputs[1], &outputs[0], "DivNoNan");
}

class CppGradients
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());

}  // namespace tensorflow

// Due to the usages of flags for this manual test, we need a special `main` to
// ensure our flags are parsed properly as `testing::InitGoogleTest` silently
// ignores other flags. Furthermore, we need this to ensure that the DSO is
// loaded exactly once, if provided.
GTEST_API_ int main(int argc, char** argv) {
  const std::vector<tensorflow::Flag> flag_list = {