code: def test_reinit_modules_with_regex_strings(self):
      # Comparing all weights of the model is rather complicated, so arbitrarily compare the
      # weights of wpe module.
      reinit_module = "wpe"
      # This MUST be a deep copy, otherwise the parameters will be re-initialized and the
      # test will break.
      preinit_weights = list(
          cached_transformers.get("sshleifer/tiny-gpt2", True)
          .get_submodule(reinit_module)
          .parameters()
      )
  
      postinit_weights = list(
          cached_transformers.get(
              "sshleifer/tiny-gpt2",
              True,
              reinit_modules=(reinit_module,),
          )
          .get_submodule(reinit_module)
          .parameters()
      )
      assert all(
          (
              not torch.equal(pre, post)
              for pre, post in zip(preinit_weights, postinit_weights)
          )
      )
  
imports: import json
  import os
  import pytest
  import torch
  from allennlp.common import cached_transformers
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase
  from transformers import AutoConfig, AutoModel
label_desc: Use image node_id 8 for calling the TestCachedTransformers obj's underlying member method code with example usage: obj.test_reinit_modules_with_regex_strings() without return types