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: Perform CutMix and return corrected lambda value.
docstr_tok: ["Perform","CutMix","and","return","corrected","lambda","value","."]
code: def _cutmix(
      self, x: torch.Tensor, cutmix_lamda: float
  ) -> Tuple[torch.Tensor, float]:
      """
      Perform CutMix and return corrected lambda value.
      """
  
      yl, yh, xl, xh = self._get_rand_box(x.size(), cutmix_lamda)
      box_area = float((yh - yl) * (xh - xl))
      cutmix_lamda_corrected = 1.0 - box_area / (
          x.size(-2) * x.size(-1)
      )
      x[..., yl:yh, xl:xh] = x.flip(0)[..., yl:yh, xl:xh]
      return x, cutmix_lamda_corrected
  
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 4 for calling the CutMix obj's underlying member method code with example usage: obj._cutmix(x, cutmix_lamda) and returns: x,  cutmix_lamda_corrected