class_docstr: Ucf101 action recognition dataset.
  
  Note that in contrast to the labels provided in the original dataset, here the
  labels start at zero, not at one.
code: def _generate_examples(self, videos_dir, splits_dir, data_list):
      data_list_path_path = os.path.join(splits_dir, data_list)
      with tf.io.gfile.GFile(
          data_list_path_path, "r"
      ) as data_list_file:
          labels_and_paths = data_list_file.readlines()
      for label_and_path in sorted(labels_and_paths):
          # The train splits contain not only the filename, but also a digit
          # encoding the label separated by a space, which we ignore.
          label_and_path = label_and_path.strip().split(" ")[0]
          label, path = os.path.split(label_and_path)
          # Fix an inconsistency between the names in the list and in the zip file.
          path = path.replace("HandStandPushups", "HandstandPushups")
          video_path = os.path.join(videos_dir, "UCF101", path)
          if not tf.io.gfile.exists(video_path):
              logging.error("Example %s not found", video_path)
              continue
          # We extract the label from the filename.
          yield path, {"video": video_path, "label": label}
  
file_path: datasets/tensorflow_datasets/video/ucf101.py
imports: import os
  from absl import logging
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 3 for calling the Ucf101 obj's underlying member method code with example usage: obj._generate_examples(videos_dir, splits_dir, data_list) without return types