code: def test_eval_mode(self):
      token_embedder = PretrainedTransformerEmbedder(
          "epwalsh/bert-xsmall-dummy", eval_mode=True
      )
      assert (
          token_embedder.training
          and not token_embedder.transformer_model.training
      )
  
      class TrainableModule(torch.nn.Module):
          def __init__(self, fixed_module):
              super().__init__()
              self.fixed_module = fixed_module
  
      trainable = TrainableModule(token_embedder)
      assert (
          trainable.training
          and trainable.fixed_module.training
          and not trainable.fixed_module.transformer_model.training
      )
  
      trainable.train()
      assert not trainable.fixed_module.transformer_model.training
  
imports: import math
  import pytest
  import torch
  from allennlp.common import Params, cached_transformers
  from allennlp.common.testing import AllenNlpTestCase, requires_gpu
  from allennlp.data import Vocabulary
  from allennlp.data.batch import Batch
  from allennlp.data.fields import TextField
  from allennlp.data.instance import Instance
  from allennlp.data.token_indexers import PretrainedTransformerIndexer
  from allennlp.data.tokenizers import PretrainedTransformerTokenizer
  from allennlp.modules.text_field_embedders import BasicTextFieldEmbedder
  from allennlp.modules.token_embedders import PretrainedTransformerEmbedder
label_desc: Use image node_id 12 for calling the TestPretrainedTransformerEmbedder obj's underlying member method code with example usage: obj.test_eval_mode() without return types