class_docstr: Wrap timm.data.Mixup that avoids the assert that batch size must be even.
      
class_docstr_tok: ["Wrap","timm.data.Mixup","that","avoids","the","assert","that","batch","size","must","be","even","."]
code: def __call__(self, x, target):
      if self.mode == "elem":
          lam = self._mix_elem(x)
      elif self.mode == "pair":
          # We move the assert from the beginning of the function to here
          assert (
              len(x) % 2 == 0
          ), "Batch size should be even when using this"
          lam = self._mix_pair(x)
      else:
          lam = self._mix_batch(x)
      target = mixup_target(
          target, self.num_classes, lam, self.label_smoothing, x.device
      )
      return x, target
  
imports: import torch
  from timm.data import Mixup
  from timm.data.mixup import mixup_target
label_desc: Use image node_id 1 for calling the TimmMixup obj's underlying member method code with example usage: obj.__call__(x, target) and returns: x,  target