const int num_dims = 2;
  int64_t* dims = new int64_t[num_dims];
  int64_t num_elements = 1;
  dims[0] = batch_size;
  dims[1] = 1;
  for (int64_t i = 0; i < num_dims; ++i) {
    num_elements *= dims[i];
  }
  TF_Tensor* t = TF_AllocateTensor(TF_STRING, dims, num_dims,
                                   sizeof(TF_TString) * num_elements);
  delete[] dims;

  ///   * `statuses` is either null or an array of `num_files` non-null elements
  ///     of type `TF_Status*`.
  ///
  /// If `statuses` is not null, plugins must fill each element with detailed
  /// status for each file, as if calling `path_exists` on each one. Core
  /// TensorFlow initializes the `statuses` array and plugins must use
  /// `TF_SetStatus` to set each element instead of directly assigning.
  ///

// `oper` and `num_dims` with the corresponding number of dimensions. On return,
// for every i where `num_dims[i]` > 0, `dims[i]` will be an array of
// `num_dims[i]` elements. A value of -1 for `num_dims[i]` indicates that the
// i-th shape in the list is unknown.
//
// The elements of `dims` will point to addresses in `storage` which must be
// large enough to hold at least `storage_size` int64_ts.  Ideally, `num_shapes`