class_docstr: A handler class for implementing `MixUp` style scheduling
class_docstr_tok: ["A","handler","class","for","implementing","`","MixUp","`","style","scheduling"]
code: def __init__(
      self,
      alpha: float = 0.5,  # Determine `Beta` distribution in range (0.,inf]
  ):
      self.distrib = Beta(tensor(alpha), tensor(alpha))
  
imports: from __future__ import annotations
  from ..basics import *
  from torch.distributions.beta import Beta
label_desc: Use image node_id 1 to create a new MixHandler object from inherited base classes: Callback with example: obj = MixHandler(alpha)