def process_and_load_activations()

in tcav/activation_generator.py [0:0]

• 26 lines of code
• 10 McCabe index (conditional complexity)

  def process_and_load_activations(self, bottleneck_names, concepts):
    acts = {}
    if self.acts_dir and not tf.io.gfile.exists(self.acts_dir):
      tf.io.gfile.makedirs(self.acts_dir)

    for concept in concepts:
      if concept not in acts:
        acts[concept] = {}
      for bottleneck_name in bottleneck_names:
        acts_path = os.path.join(self.acts_dir, 'acts_{}_{}'.format(
            concept, bottleneck_name)) if self.acts_dir else None
        if acts_path and tf.io.gfile.exists(acts_path):
          with tf.io.gfile.GFile(acts_path, 'rb') as f:
            acts[concept][bottleneck_name] = np.load(
                f, allow_pickle=True).squeeze()
            tf.compat.v1.logging.info('Loaded {} shape {}'.format(
                acts_path, acts[concept][bottleneck_name].shape))
        else:
          acts[concept][bottleneck_name] = self.get_activations_for_concept(
              concept, bottleneck_name)
          if acts_path:
            tf.compat.v1.logging.info(
                '{} does not exist, Making one...'.format(acts_path))
            tf.io.gfile.mkdir(os.path.dirname(acts_path))
            with tf.io.gfile.GFile(acts_path, 'w') as f:
              np.save(f, acts[concept][bottleneck_name], allow_pickle=False)
    return acts