code: def __init__(
      self,
      *,
      alpha: float = 1.0,
      num_classes: int,
      labels_getter="default",
  ) -> None:
      super().__init__()
      self.alpha = float(alpha)
      self._dist = torch.distributions.Beta(
          torch.tensor([alpha]), torch.tensor([alpha])
      )
  
      self.num_classes = num_classes
  
      self._labels_getter = _parse_labels_getter(labels_getter)
  
imports: import math
  import numbers
  import warnings
  from typing import Any, Callable, Dict, List, Tuple
  import PIL.Image
  import torch
  from torch.nn.functional import one_hot
  from torch.utils._pytree import tree_flatten, tree_unflatten
  from torchvision import transforms, tv_tensors
  from torchvision.transforms.v2 import functional
  from ._transform import _RandomApplyTransform, Transform
  from ._utils import _parse_labels_getter, has_any, is_pure_tensor, query_chw, query_size
label_desc: Use image node_id 1 to create a new _BaseMixUpCutMix object from inherited base classes: Transform with example: obj = _BaseMixUpCutMix()