class_docstr: CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
  (https://arxiv.org/abs/1905.04899)
class_docstr_tok: ["CutMix",":","Regularization","Strategy","to","Train","Strong","Classifiers","with","Localizable","Features","(","https",":","\/\/arxiv.org\/abs\/1905.04899",")"]
docstr: Clip value based on minimum value and maximum value.
docstr_tok: ["Clip","value","based","on","minimum","value","and","maximum","value","."]
code: def _clip(self, value: int, min_value: int, max_value: int) -> int:
      """
      Clip value based on minimum value and maximum value.
      """
  
      return min(max(value, min_value), max_value)
  
file_path: pytorchvideo/pytorchvideo/transforms/mix.py
imports: from typing import Any, Dict, Tuple
  import torch
  from pytorchvideo.transforms.functional import convert_to_one_hot
label_desc: Use image node_id 2 for calling the CutMix obj's underlying member method code with example usage: obj._clip(value, min_value, max_value) and returns: min