class_docstr: Select one of transforms to apply. Selected transform will be called with `force_apply=True`.
  Transforms probabilities will be normalized to one 1, so in this case transforms probabilities works as weights.
  
  Args:
      transforms (list): list of transformations to compose.
      p (float): probability of applying selected transform. Default: 0.5.
class_docstr_tok: ["Select","one","of","transforms","to","apply",".","Selected","transform","will","be","called","with","`","force_apply=True","`",".","Transforms","probabilities","will","be","normalized","to","one","1",",","so","in","this","case","transforms","probabilities","works","as","weights",".","Args",":","transforms","(","list",")",":","list","of","transformations","to","compose",".","p","(","float",")",":","probability","of","applying","selected","transform",".","Default",":","0.5","."]
code: def __call__(
      self, *args, force_apply: bool = False, **data
  ) -> typing.Dict[str, typing.Any]:
      if self.replay_mode:
          for t in self.transforms:
              data = t(**data)
          return data
  
      if self.transforms_ps and (
          force_apply or random.random() < self.p
      ):
          idx: int = random_utils.choice(
              len(self.transforms), p=self.transforms_ps
          )
          t = self.transforms[idx]
          data = t(force_apply=True, **data)
      return data
  
imports: from __future__ import division
  import random
  import typing
  import warnings
  from collections import defaultdict
  import numpy
  from ..None import random_utils
  from .bbox_utils import BboxParams, BboxProcessor
  from .keypoints_utils import KeypointParams, KeypointsProcessor
  from .serialization import SERIALIZABLE_REGISTRY, Serializable, get_shortest_class_fullname, instantiate_nonserializable
  from .transforms_interface import BasicTransform
  from .utils import format_args, get_shape
label_desc: Use image node_id 2 for calling the OneOf obj's underlying member method code with example usage: obj.__call__() and returns: data, data