class_docstr: Randomly selects between transforms1 and transforms2,
  with probability p for transforms1 and (1 - p) for transforms2
class_docstr_tok: ["Randomly","selects","between","transforms1","and","transforms2",",","with","probability","p","for","transforms1","and","(","1","-","p",")","for","transforms2"]
code: def __call__(self, img, target):
      if random.random() < self.p:
          return self.transforms1(img, target)
      return self.transforms2(img, target)
  
imports: import random
  import PIL
  import torch
  import torchvision.transforms
  import torchvision.transforms.functional
  from util.box_ops import box_xyxy_to_cxcywh
  from util.misc import interpolate
label_desc: Use image node_id 2 for calling the RandomSelect obj's underlying member method code with example usage: obj.__call__(img, target) and returns: self, self