::tensorflow::Set_TF_Status_from_Status(status, s);
  if (s.ok()) {
    stats->length = cc_stats.length;
    stats->mtime_nsec = cc_stats.mtime_nsec;
    stats->is_directory = cc_stats.is_directory;
  }
}

void TF_NewWritableFile(const char* filename, TF_WritableFileHandle** handle,
                        TF_Status* status) {
  std::unique_ptr<::tensorflow::WritableFile> f;

    ASSERT_EQ(childpath, nullptr);
    TF_StringStreamDone(children);

    TF_FileStatistics stats;
    TF_FileStat(filepath.c_str(), &stats, s);
    ASSERT_EQ(stats.length, strlen(data));
    ASSERT_FALSE(stats.is_directory);
    ASSERT_GT(stats.mtime_nsec, 0);

    // Trying to delete a non-empty directory should fail.
    TF_DeleteDir(dirpath.c_str(), s);

                                                TF_Status* status);

// Obtains statistics for the given path. If status is TF_OK, *stats is
// updated, otherwise it is not touched.
TF_CAPI_EXPORT extern void TF_FileStat(const char* filename,
                                       TF_FileStatistics* stats,
                                       TF_Status* status);

 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
    status_ = StatusFromTF_Status(status.get());
    ASSERT_EQ(errors::OK, status_.code()) << status_.message();

    {
      AbstractContext* ctx_raw = nullptr;
      status_ =
          BuildImmediateExecutionContext(std::get<1>(GetParam()), &ctx_raw);

  TF_EXPECT_OK(status.status);
  EXPECT_EQ(value, 1);
  EXPECT_EQ(num_compute_calls, 2);
  cache2.LookupOrCompute("c", &value, compute_func, &status);
  TF_EXPECT_OK(status.status);
  EXPECT_EQ(value, 2);
  EXPECT_EQ(num_compute_calls, 3);
  cache2.LookupOrCompute("d", &value, compute_func, &status);
  TF_EXPECT_OK(status.status);
  EXPECT_EQ(value, 3);
  EXPECT_EQ(num_compute_calls, 4);

    TF_Status* out_status) const {
  Status status;
  if (reader_ != nullptr) {
    status = reader_->GetTensor(name, out_tensor);
  } else {
    tensorflow::DataType dtype;
    tensorflow::TensorShape shape;
    status = v2_reader_->LookupDtypeAndShape(name, &dtype, &shape);
    if (status.ok()) {
      out_tensor->reset(new Tensor(dtype, shape));
      status = v2_reader_->Lookup(name, out_tensor->get());

  tensorflow::TensorHandle* handle =
      TensorHandleFromInterface(tensorflow::unwrap(h));
  const tensorflow::Tensor* tensor;
  status->status = handle->Tensor(&tensor);
  if (!status->status.ok()) {
    return nullptr;
  }

  std::vector<int64_t> dev_dims = TensorShapeAsVector(*handle, &status->status);
  if (!status->status.ok()) {
    return nullptr;
  }
  return new TFE_TensorDebugInfo(dev_dims);
}

  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);
  TFE_Context* eager_ctx =
      TF_ExecutionContextGetTFEContext(wrap(ctx), status.get());
  TF_RETURN_IF_ERROR(StatusFromTF_Status(status.get()));
  TFE_TensorHandle* input_eager =
      TestScalarTensorHandle<T, datatype>(eager_ctx, value);
  *tensor =
      unwrap(TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get()));

  // Returns the device ID which created the handle.
  virtual int DeviceId(Status* status) const = 0;
  // Returns a tensor for the handle. If tensor is remote, it will be copied.
  virtual AbstractTensorInterface* Resolve(Status* status) = 0;

  std::string DebugString() const override;

  // Returns a Boolean hint indicating whether callers should prefer
  // `SummarizeValue` to resolving this handle and formatting the tensor.

      ::tensorflow::Set_TF_Status_from_Status(C_STATUS, _s);      \
      TF_OpKernelContext_Failure(CTX, C_STATUS);                  \
      TF_DeleteStatus(C_STATUS);                                  \
      return;                                                     \
    }                                                             \
  } while (0)

#define TF_CLEANUP_AND_RETURN_IF_ERROR(C_STATUS, BUFFER, __VA_ARGS__) \