class_docstr: Celeba_HQ Dataset.
class_docstr_tok: ["Celeba_HQ","Dataset","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager):
      """Returns SplitGenerators."""
      image_tar_file = os.path.join(
          dl_manager.manual_dir, self.builder_config.file_name
      )
      if not tf.io.gfile.exists(image_tar_file):
          # The current celebahq generation code depends on a concrete version of
          # pillow library and cannot be easily ported into tfds.
          msg = "You must download the dataset files manually and place them in: "
          msg += dl_manager.manual_dir
          msg += " as .tar files. See testing/test_data/fake_examples/celeb_a_hq "
          raise AssertionError(msg)
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs={
                  "archive": dl_manager.iter_archive(image_tar_file)
              },
          )
      ]
  
file_path: datasets/tensorflow_datasets/datasets/celeb_a_hq/celeb_a_hq_dataset_builder.py
imports: import os
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 2 for calling the Builder obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: list