code: def pad_if_smaller(self, img, fill=0):
      # 如果图像最小边长小于给定size，则用数值fill进行padding
      min_size = min(img.shape[-2:])
      if min_size < self.size:
          ow, oh = img.size
          padh = self.size - oh if oh < self.size else 0
          padw = self.size - ow if ow < self.size else 0
          img = F.pad(img, [0, 0, padw, padh], fill=fill)
      return img
  
imports: import random
  from typing import List, Union
  from torchvision.transforms import functional
  from torchvision.transforms import transforms
label_desc: Use image node_id 2 for calling the RandomCrop obj's underlying member method code with example usage: obj.pad_if_smaller(img, fill) and returns: img