code: def check_and_expand(x: list, y: list) -> Tuple[List[Any], List[Any]]:
      if not (isinstance(x, list) and isinstance(y, list)):
          raise TypeError(
              "Input x and y should be lists. Got {} and {} instead.".format(
                  type(x), type(y)
              )
          )
      # assert isinstance(x, list) and isinstance(y, list)
      max_len = max(len(x), len(y))
      if len(x) == len(y):
          return x, y
      elif (
          len(x) * len(y) == max_len
      ):  # Which means at least one of the list is of length 1
          if len(x) == 1:
              x = x * max_len
          else:
              y = y * max_len
          return x, y
      else:
          raise ValueError(
              "The two lists {} and {} cannot be automatically "
              "broadcasted to the same length.".format(x, y)
          )
  
file_path: graph4nlp/graph4nlp/pytorch/data/utils.py
imports: from typing import Any, List, Tuple, Union
  import torch
label_desc: Use image node_id 2 for calling a global function with example usage: check_and_expand(x, y) and returns: x,  y, x,  y