}

void TF_DeleteShapeAndTypeList(TF_ShapeAndTypeList* shape_list) {
  if (shape_list == nullptr) return;
  for (size_t i = 0; i < shape_list->num_items; ++i) {
    delete[] shape_list->items[i].dims;
  }
  delete[] shape_list->items;
  delete shape_list;
}

void TF_DeleteShapeAndTypeListArray(TF_ShapeAndTypeList** shape_list_array,
                                    int num_items) {

      tf_posix_filesystem::NewReadOnlyMemoryRegionFromFile;
  ops->filesystem_ops->create_dir = tf_posix_filesystem::CreateDir;
  ops->filesystem_ops->delete_file = tf_posix_filesystem::DeleteFile;
  ops->filesystem_ops->delete_dir = tf_posix_filesystem::DeleteDir;
  ops->filesystem_ops->rename_file = tf_posix_filesystem::RenameFile;
  ops->filesystem_ops->copy_file = tf_posix_filesystem::CopyFile;

  CheckTFE_TensorHandleHasFloats(retval_task0, {7, 10, 15, 22});

  TFE_DeleteTensorHandle(retval_task0);
  TFE_DeleteTensorHandle(h0_task0);
  TFE_DeleteTensorHandle(retvals[0]);

  TFE_DeleteOp(matmul);

  TFE_Executor* executor = TFE_ContextGetExecutorForThread(ctx);
  TFE_ExecutorWaitForAllPendingNodes(executor, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteExecutor(executor);

namespace tensorflow {

namespace {

// Managing context for the DLManagedTensor, will manage the lifetime of
// DLManagedTensor. When calling DLManagedTensor::deleter, it will notify the
// original framework of destruction, and this context will be deleted also.
struct TfDlManagedTensorCtx {
  TensorReference reference;
  std::vector<int64_t> shape;
  std::vector<int64_t> strides;
  DLManagedTensor tensor;

      op_name, tape_tensors, input_ids, input_dtypes,
      [gradient_function]() -> GradientFunction* { return gradient_function; },
      [](GradientFunction* ptr) {
        if (ptr) {
          delete ptr;
        }
      });
}
bool Tape::ShouldRecord(
    absl::Span<const AbstractTensorHandle* const> tensors) const {
  std::vector<int64_t> tensor_ids(tensors.size());

#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"

namespace tensorflow {
namespace parallel_device {
namespace {

class OpDeleter {
 public:
  void operator()(TFE_Op* to_delete) const { TFE_DeleteOp(to_delete); }
};

using OpPtr = std::unique_ptr<TFE_Op, OpDeleter>;

using MaybeParallelTensorOwned =
    absl::variant<std::unique_ptr<ParallelTensor>, TensorHandlePtr>;

using MaybeParallelTensorUnowned =

namespace tensorflow {
namespace parallel_device {
namespace {

class OpDeleter {
 public:
  void operator()(TFE_Op* to_delete) const { TFE_DeleteOp(to_delete); }
};

using OpPtr = std::unique_ptr<TFE_Op, OpDeleter>;

class StatusDeleter {
 public:
  void operator()(TF_Status* to_delete) const { TF_DeleteStatus(to_delete); }
};

using StatusPtr = std::unique_ptr<TF_Status, StatusDeleter>;

class ExecutorDeleter {
 public:

  TFE_TensorHandle* retvals[1] = {nullptr};
  int num_retvals = 1;
  TFE_Execute(func, &retvals[0], &num_retvals, status);
  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  ASSERT_EQ(1, num_retvals);
  TFE_DeleteOp(func);
  TFE_DeleteTensorHandle(packed_handle);
  TF_Tensor* t = TFE_TensorHandleResolve(retvals[0], status);
  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_DeleteTensorHandle(retvals[0]);

}

void TF_DeleteFunction(TF_Function* func) {
  if (func == nullptr) {
    return;
  }

  func->record->Unref();
  func->record = nullptr;
  delete func;

    if (!metadata) {
      TF_SetStatusFromGCSStatus(metadata.status(), status);
      return;
    }
    // We have to delete the temporary object after composing.
    auto delete_status = gcs_client->DeleteObject(bucket, temporary_object);
    if (!delete_status.ok()) {
      TF_SetStatusFromGCSStatus(delete_status, status);
      return;
    }
    // We truncate the data that are already uploaded.
    if (!outfile->truncate()) {