class_docstr: Evenly splits the video into clips of size clip_duration.
  If truncation_duration is set, clips sampled from [0, truncation_duration].
  If truncation_duration is not set, defaults to UniformClipSampler.
class_docstr_tok: ["Evenly","splits","the","video","into","clips","of","size","clip_duration",".","If","truncation_duration","is","set",",","clips","sampled","from","[","0",",","truncation_duration","]",".","If","truncation_duration","is","not","set",",","defaults","to","UniformClipSampler","."]
code: def __call__(
      self,
      last_clip_end_time: float,
      video_duration: float,
      annotation: Dict[str, Any],
  ) -> ClipInfo:
      truncated_video_duration = video_duration
      if self.truncation_duration is not None:
          truncated_video_duration = min(
              self.truncation_duration, video_duration
          )
  
      return super().__call__(
          last_clip_end_time, truncated_video_duration, annotation
      )
  
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 UniformClipSamplerTruncateFromStart obj's underlying member method code with example usage: obj.__call__(last_clip_end_time, video_duration, annotation) and returns: super