==============================================================================*/
#include "tensorflow/c/experimental/gradients/tape/tape_operation.h"

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

namespace tensorflow {
namespace gradients {
TapeOperation::TapeOperation(AbstractOperation* parent_op, Tape* tape,
                             const GradientRegistry& registry)
    : AbstractOperation(kTape),

#include "tensorflow/c/experimental/gradients/tape/tape_context.h"

#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/experimental/gradients/tape/tape_operation.h"

namespace tensorflow {
namespace gradients {
TapeContext::TapeContext(AbstractContext* c, Tape* tape,
                         const GradientRegistry& registry)
    : AbstractContext(kTape), parent_ctx_(c), tape_(tape), registry_(registry) {

#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_CONTEXT_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_CONTEXT_H_

#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/experimental/gradients/tape/tape_operation.h"

namespace tensorflow {
namespace gradients {
class TapeContext : public AbstractContext {
 public:
  explicit TapeContext(AbstractContext*, Tape*, const GradientRegistry&);

#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_OPERATION_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_OPERATION_H_

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

namespace tensorflow {
namespace gradients {
class TapeOperation : public AbstractOperation {
 public:
  explicit TapeOperation(AbstractOperation*, Tape*, const GradientRegistry&);
  void Release() override;

)

cc_library(
    name = "tape",
    hdrs = [
        "tape_context.h",
        "tape_operation.h",
    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        ":tape_context",
        ":tape_operation",
        "//tensorflow/c/eager:abstract_context",
        "//tensorflow/c/eager:abstract_operation",
        "//tensorflow/c/eager:gradients_internal",
    ],
)

filegroup(

    absl::Span<AbstractTensorHandle*> outputs) {
  Tape tape(/*persistent=*/false);
  tape.Watch(inputs[0]);
  AbstractTensorHandle* neg_output;
  TF_RETURN_IF_ERROR(ops::Neg(ctx, inputs[0], &neg_output, "Neg"));
  tape.RecordOperation(inputs, {neg_output}, nullptr, "Neg");
  return tape.ComputeGradient(ctx,
                              /*targets=*/{neg_output},

  AbstractTensorHandle* GetHandle() const;

 private:
  AbstractTensorHandle* handle_;
};

// A tracing/immediate-execution agnostic tape.
//
// Gradient functions defined for this tape must support handling null incoming
// gradients.
class Tape : protected eager::GradientTape<AbstractTensorHandle,
                                           GradientFunction, TapeTensor> {
 public:

             absl::Span<AbstractTensorHandle*> outputs) -> Status {
    Tape tape(/*persistent=*/false);
    for (size_t i{}; i < inputs.size(); ++i) {
      tape.Watch(inputs[i]);
    }
    std::vector<AbstractTensorHandle*> temp_outputs(1);
    AbstractContextPtr tape_ctx(new TapeContext(ctx, &tape, grad_registry));
    TF_RETURN_IF_ERROR(
        forward_model(tape_ctx.get(), inputs, absl::MakeSpan(temp_outputs)));

  Tape tape(/*persistent=*/false);
  tape.Watch(inputs[0]);  // Watch x.
  AbstractTensorHandle* exp_output;
  TF_RETURN_IF_ERROR(ops::Exp(ctx, inputs[0], &exp_output, "Exp"));
  std::unique_ptr<GradientFunction> gradient_function(
      new PassThroughGradientFunction);
  tape.RecordOperation(inputs, {exp_output}, gradient_function.release());
  TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx,

    deps = [
        "//tensorflow/c/eager:gradient_checker",
        "//tensorflow/c/eager:gradients_internal",
        "//tensorflow/c/eager:unified_api_testutil",
        "//tensorflow/c/experimental/gradients/tape:tape_context",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
    ],
)

tf_cuda_cc_test(
    name = "nn_grad_test",
    size = "small",
    srcs = [