// TensorFlow, so we need to use `plugin_memory_free_` here.
  char** children = nullptr;
  const int num_children =
      ops_->get_children(filesystem_.get(), translated_name.c_str(), &children,
                         plugin_status.get());
  if (num_children >= 0) {
    for (int i = 0; i < num_children; i++) {
      result->push_back(std::string(children[i]));
      plugin_memory_free_(children[i]);
    }

  // Build an abstract input tensor.
  int64_t dims[] = {2, 2};  // Matrices will be 2 x 2
  int num_dims = sizeof(dims) / sizeof(dims[0]);

  float vals[] = {0.0f, 0.0f, 0.0f, 0.0f};
  TFE_Context* eager_ctx = TF_ExecutionContextGetTFEContext(ctx, status.get());
  TFE_TensorHandle* t =
      TestMatrixTensorHandleWithInput(eager_ctx, vals, dims, num_dims);

  TF_AbstractTensor* at = TF_CreateAbstractTensorFromEagerTensor(

  const size_t block_size = 16;
  int num_requests = 0;
  Notification notification;
  auto fetcher = [&num_requests, &notification, block_size](
                     const string& filename, size_t offset, size_t n,
                     char* buffer, TF_Status* status) -> int64_t {
    EXPECT_EQ(n, block_size);
    EXPECT_EQ(offset, 0);
    num_requests++;
    memset(buffer, 'x', n);
    notification.Notify();