==============================================================================*/
#include "tensorflow/c/eager/gradient_checker.h"

#include <memory>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/experimental/ops/math_ops.h"
#include "tensorflow/c/tf_tensor.h"

namespace tensorflow {
namespace gradients {

using namespace std;

// ================== Helper functions =================

  std::unique_ptr<GradientFunction> gradient_function(
      new PassThroughGradientFunction);
  tape.RecordOperation(inputs, {exp_output}, gradient_function.release());
  TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx,
                                          /*targets*/ {exp_output},
                                          /*sources=*/inputs,
                                          /*output_gradients=*/{},

Status TapeVSpace::CallBackwardFunction(
    const string& op_type, GradientFunction* gradient_function,
    const std::vector<int64_t>& unneeded_gradients,
    gtl::ArraySlice<AbstractTensorHandle*> output_gradients,
    absl::Span<AbstractTensorHandle*> result) const {
  if (gradient_function == nullptr) {
    return errors::InvalidArgument(
        "Provided null gradient_function for '", op_type, "'.\n",

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

#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/c/experimental/ops/nn_ops.h"
#include "tensorflow/c/tf_status_helper.h"

          grad_it->second.push_back(new_gradients);
          vspace.MarkAsResult(new_gradients);
        }
        out_gradients.push_back(new_gradients);
      }
    }
    VLOG(1) << "Calling gradient function for '" << trace.op_type << "'";
    std::vector<Gradient*> in_gradients(trace.input_tensor_id.size());
    DCHECK(build_default_zeros_grads || zero_indices.empty());
    if (any_gradient_nonzero) {

        ":nn_grad",
        ":not_differentiable",
        "//tensorflow/c/eager:abstract_context",
        "//tensorflow/c/eager:gradients_internal",
    ],
)

tf_cuda_cc_test(
    name = "custom_gradient_test",
    size = "small",
    srcs = [
        "custom_gradient_test.cc",
    ],
    args = ["--heap_check="],  # TODO(b/174752220): Remove
    tags = tf_cuda_tests_tags(),
    deps = [

                                /*transpose_a = */ true,
                                /*transpose_b = */ true, name_grad_B.c_str()));
    }

    // Gradient for A
    grad_inputs[0] = matmul_A_output;

    // Gradient for B
    grad_inputs[1] = matmul_B_output;
    return absl::OkStatus();
  }
  ~MatMulGradientFunction() override {
    for (auto input : forward_inputs_) {
      if (input) {

        ":c_api_unified_internal",
        "//tensorflow/c/experimental/gradients/tape:tape_operation",
        "//tensorflow/core/lib/llvm_rtti",
        "//tensorflow/core/platform:errors",
    ],
)

cc_library(
    name = "gradients_internal",
    srcs = [
        "gradients.cc",
    ],
    hdrs = [
        "gradients.h",
        "gradients_internal.h",
    ],
    visibility = [

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

#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/c/experimental/ops/array_ops.h"

#include "tensorflow/c/eager/gradients_internal.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/array_grad.h"
#include "tensorflow/c/experimental/gradients/math_grad.h"
#include "tensorflow/c/experimental/gradients/not_differentiable.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/c/experimental/ops/array_ops.h"