def __init__()

in iep/data.py [0:0]

• 30 lines of code
• 5 McCabe index (conditional complexity)

  def __init__(self, **kwargs):
    if 'question_h5' not in kwargs:
      raise ValueError('Must give question_h5')
    if 'feature_h5' not in kwargs:
      raise ValueError('Must give feature_h5')
    if 'vocab' not in kwargs:
      raise ValueError('Must give vocab')

    feature_h5_path = kwargs.pop('feature_h5')
    print('Reading features from ', feature_h5_path)
    self.feature_h5 = h5py.File(feature_h5_path, 'r')

    self.image_h5 = None
    if 'image_h5' in kwargs:
      image_h5_path = kwargs.pop('image_h5')
      print('Reading images from ', image_h5_path)
      self.image_h5 = h5py.File(image_h5_path, 'r')

    vocab = kwargs.pop('vocab')
    mode = kwargs.pop('mode', 'prefix')

    question_families = kwargs.pop('question_families', None)
    max_samples = kwargs.pop('max_samples', None)
    question_h5_path = kwargs.pop('question_h5')
    image_idx_start_from = kwargs.pop('image_idx_start_from', None)
    print('Reading questions from ', question_h5_path)
    with h5py.File(question_h5_path, 'r') as question_h5:
      self.dataset = ClevrDataset(question_h5, self.feature_h5, vocab, mode,
                                  image_h5=self.image_h5,
                                  max_samples=max_samples,
                                  question_families=question_families,
                                  image_idx_start_from=image_idx_start_from)
    kwargs['collate_fn'] = clevr_collate
    super(ClevrDataLoader, self).__init__(self.dataset, **kwargs)