};

}  // namespace

GradientFunction* ReluRegisterer(const ForwardOperation& op) {
  return new ReluGradientFunction(op.outputs);
}

GradientFunction* SparseSoftmaxCrossEntropyWithLogitsRegisterer(
    const ForwardOperation& op) {
  return new SparseSoftmaxCrossEntropyWithLogitsGradientFunction(op.outputs);
}

GradientFunction* BiasAddRegisterer(const ForwardOperation& op) {

}

GradientFunction* SqrtRegisterer(const ForwardOperation& op) {
  return new SqrtGradientFunction(op.outputs[0]);
}

GradientFunction* NegRegisterer(const ForwardOperation& op) {
  return new NegGradientFunction;
}

GradientFunction* SubRegisterer(const ForwardOperation& op) {
  return new SubGradientFunction;
}

GradientFunction* MulRegisterer(const ForwardOperation& op) {
  return new MulGradientFunction(op.inputs);

#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*> grad_inputs) override {

    Status s = StatusFromTF_Status(status.get());
    CHECK_EQ(errors::OK, s.code()) << s.message();
  }
};

class PassThroughGradientFunction : public GradientFunction {
 public:
  Status Compute(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> grad_outputs,
                 absl::Span<AbstractTensorHandle*> grad_inputs) override {