code: def download_and_prepare(builder):
    
    print("download_and_prepare for dataset {}...".format(builder.info.full_name))
  
    dl_config = download_config()
  
    if isinstance(builder, tfds.core.BeamBasedBuilder):
      beam = tfds.core.lazy_imports.apache_beam
      # TODO(b/129149715): Restore compute stats. Currently skipped because not
      # beam supported.
      dl_config.compute_stats = tfds.download.ComputeStatsMode.SKIP
      dl_config.beam_options = beam.options.pipeline_options.PipelineOptions()
  
    builder.download_and_prepare(
        download_dir=FLAGS.download_dir,
        download_config=dl_config,
    )
    termcolor.cprint(str(builder.info.as_proto), attrs=["bold"])
  
    if FLAGS.debug:
      dataset = builder.as_dataset(split=tfds.Split.TRAIN)
      pdb.set_trace()
      del dataset
docs: Generate data for a given dataset.