class_docstr: Randomly samples multiple clips of size clip_duration from the videos.
class_docstr_tok: ["Randomly","samples","multiple","clips","of","size","clip_duration","from","the","videos","."]
code: def __call__(
      self,
      last_clip_end_time: Optional[float],
      video_duration: float,
      annotation: Dict[str, Any],
  ) -> ClipInfoList:
      (
          clip_start_list,
          clip_end_list,
          clip_index_list,
          aug_index_list,
          is_last_clip_list,
      ) = (
          self._num_clips * [None],
          self._num_clips * [None],
          self._num_clips * [None],
          self._num_clips * [None],
          self._num_clips * [None],
      )
      for i in range(self._num_clips):
          (
              clip_start_list[i],
              clip_end_list[i],
              clip_index_list[i],
              aug_index_list[i],
              is_last_clip_list[i],
          ) = super().__call__(
              last_clip_end_time, video_duration, annotation
          )
  
      return ClipInfoList(
          clip_start_list,
          clip_end_list,
          clip_index_list,
          aug_index_list,
          is_last_clip_list,
      )
  
imports: import random
  from abc import ABC, abstractmethod
  from fractions import Fraction
  from typing import Any, Dict, List, NamedTuple, Optional, Tuple, Union
label_desc: Use image node_id 2 for calling the RandomMultiClipSampler obj's underlying member method code with example usage: obj.__call__(last_clip_end_time, video_duration, annotation) and returns: ClipInfoList