def get_split(config):
  """Select the default split according to the config.

  Args:
    config: (ml_collections.ConfigDict) The experimental config.
  Returns:
    The TFDS split for the experimental setup indicated by the config.
  """
  splits = {
      'train': 'train[:70%]',
      'valid': 'train[70%:90%]',
      'test': 'train[90%:]',
  }
  if config.dataset.split == 'default':
    split_name = 'valid' if config.runner.mode.startswith('eval') else 'train'
    split = splits[split_name]
  elif config.dataset.split in splits:
    split = splits[config.dataset.split]
  else:
    raise ValueError('Unexpected split.')
  return split