code: def postprocess_item(self, item: np_dict_type) -> np_dict_type:
      tensor = torch.from_numpy(item[INPUT_KEY])
      tensor = transforms.RandomCrop(self.size)(tensor)
      item[INPUT_KEY] = tensor.numpy()
      return item
  
file_path: carefree-learn/cflearn/data/blocks/cv/crop.py
imports: import torch
  import numpy
  from typing import List
  from typing import Tuple
  from typing import Union
  from torchvision import transforms
  from cftool.types import np_dict_type
  from ....schema import IRuntimeDataBlock
  from ....constants import INPUT_KEY
label_desc: Use image node_id 3 for calling the RandomCropBlock obj's underlying member method code with example usage: obj.postprocess_item(item) and returns: item