def METHOD_NAME(
    data_type: Callable,
    split: bool = True,
    seed: int = 999) -> List[Union[numpy.array, pandas.DataFrame]]:
  """
    Loads test data from the sklearn Iris dataset in a given format,
    either in a single or multiple batches.
    Args:
      data_type: Datatype of the iris test dataset.
      split: Split the dataset in different batches or return single batch.
      seed: Random state for splitting the train and test set.
  """
  dataset = load_iris()
  _, x_test, _, _ = train_test_split(
      dataset['data'], dataset['target'], test_size=.2, random_state=seed)
  if split:
    return [(index, data_type(sample.reshape(1, -1))) for index,
            sample in enumerate(x_test)]
  return [(0, data_type(x_test))]