// Adds a copy of function `func` and optionally its gradient function `grad`
// to `g`. Once `func`/`grad` is added to `g`, it can be called by creating
// an operation using the function's name.
// Any changes to `func`/`grad` (including deleting it) done after this method
// returns, won't affect the copy of `func`/`grad` in `g`.
// If `func` or `grad` are already in `g`, TF_GraphCopyFunction has no

#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_ARRAY_GRAD_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_ARRAY_GRAD_H_

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

namespace tensorflow {
namespace gradients {
GradientFunction* IdentityNRegisterer(const ForwardOperation& op);
}  // namespace gradients
}  // namespace tensorflow

limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_NN_GRAD_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_NN_GRAD_H_

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

namespace tensorflow {
namespace gradients {
GradientFunction* ReluRegisterer(const ForwardOperation& op);

#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_GRAD_TEST_HELPER_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_GRAD_TEST_HELPER_H_

#include "tensorflow/c/eager/gradients.h"
#include "tensorflow/c/eager/unified_api_testutil.h"

namespace tensorflow {
namespace gradients {
namespace internal {

void CompareNumericalAndAutodiffGradients(
    Model model, Model grad_model, AbstractContext* ctx,

limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_MATH_GRAD_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_MATH_GRAD_H_

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

namespace tensorflow {
namespace gradients {

GradientFunction* AddRegisterer(const ForwardOperation& op);