code: def __call__(self, *imgs):
      i, j, h, w = self.get_params(imgs[0], self.scale, self.ratio)
      # print(i,j,h,w)
      return map(
          lambda x: F.resized_crop(
              x, i, j, h, w, self.size, self.interpolation
          ),
          imgs,
      )
  
imports: import os
  import cv2
  import numpy
  import random
  import torchvision.transforms.functional
  from torchvision.transforms import RandomResizedCrop, ColorJitter, RandomAffine
  import PIL
  from PIL import Image
  import collections
  import settings
label_desc: Use image node_id 2 for calling the RandomResizedCropWithMask obj's underlying member method code with example usage: obj.__call__() and returns: map