def _generate_blended_split_builder_configs()

in tensorflow_datasets/text/star_cfq/star_cfq.py [0:0]

• 37 lines of code
• 17 McCabe index (conditional complexity)

def _generate_blended_split_builder_configs():
  """Generate configs for blended random splits."""
  configs = []
  split_archive_path = 'splits/star-cfq-random-splits-1.0.tar.gz'
  for supplementary_pool in _SUPPLEMENTARY_POOLS:
    for initial_size in _BLENDING_INITIAL_SIZES:
      for supplementary_size in _BLENDING_SUPPLEMENTARY_SIZES:
        # Some splits with 80x n-CFQ/half-n-CFQ sizes are missing, skip them.
        if supplementary_size == 80 and (supplementary_pool in ['n', 'half_n']
                                         or initial_size not in [0, 0.1, 1]):
          continue
        if initial_size != 0:
          configs.append(
              StarCFQConfig(
                  name=f'equal_weighting_{initial_size}x_b_cfq_{supplementary_size}x_{supplementary_pool}_cfq',
                  split_archive_path=split_archive_path,
                  split_path=f'random_splits/train_{initial_size}x_b_cfq_{supplementary_size}x_{supplementary_pool}_cfq__test_1x_b_cfq.json'
              ))
        else:
          configs.append(
              StarCFQConfig(
                  name=f'equal_weighting_0x_b_cfq_{supplementary_size}x_{supplementary_pool}_cfq',
                  split_archive_path=split_archive_path,
                  split_path=f'random_splits/train_{supplementary_size}x_{supplementary_pool}_cfq__test_1x_b_cfq.json'
              ))
  for unique_initial_size in _UNIQUE_INITIAL_SIZES:
    for supplementary_pool in _SUPPLEMENTARY_POOLS:
      for size in _OVERWEIGHTING_SIZES:
        # Splits with 80x n-CFQ/half-n-CFQ sizes are missing, skip them for now.
        if size == 80 and supplementary_pool in ['n', 'half_n']:
          continue
        # This split file is missing, skip it in this version.
        if unique_initial_size == 1 and size == 1 and supplementary_pool == 'half_n':
          continue
        configs.append(
            StarCFQConfig(
                name=f'overweighting_{unique_initial_size}x_unique_{size}x_b_cfq_{size}x_{supplementary_pool}_cfq',
                split_archive_path=split_archive_path,
                split_path=f'random_splits/train_{unique_initial_size}x_unique_{size}x_b_cfq_{size}x_{supplementary_pool}_cfq__test_1x_b_cfq.json'
            ))

  return configs