code: def test_extend_embedder_vocab(self):
      model_archive = str(
          self.FIXTURES_ROOT
          / "basic_classifier"
          / "serialization"
          / "model.tar.gz"
      )
      trained_model = load_archive(model_archive).model
  
      original_weight = (
          trained_model._text_field_embedder.token_embedder_tokens.weight
      )
      assert tuple(original_weight.shape) == (213, 10)
  
      counter = {"tokens": {"unawarded": 1}}
      trained_model.vocab._extend(counter)
      trained_model.extend_embedder_vocab()
  
      extended_weight = (
          trained_model._text_field_embedder.token_embedder_tokens.weight
      )
      assert tuple(extended_weight.shape) == (214, 10)
  
      assert torch.all(original_weight == extended_weight[:213, :])
  
file_path: allennlp/tests/models/model_test.py
imports: import torch
  import pytest
  from allennlp.common.testing.test_case import AllenNlpTestCase
  from allennlp.models import load_archive, Model
  from allennlp.nn.regularizers import RegularizerApplicator
label_desc: Use image node_id 1 for calling the TestModel obj's underlying member method code with example usage: obj.test_extend_embedder_vocab() without return types