code: def test_resize_tokens_embeddings_more(self):
      config, input_ids, _ = self._get_config_and_data()
  
      def _get_embs(m):
          return (
              m.get_input_embeddings().weight.data.clone(),
              m.get_output_embeddings().weight.data.clone(),
          )
  
      model = (
          MvpForConditionalGeneration(config).eval().to(torch_device)
      )
      input, output = _get_embs(model)
      self.assertTrue(torch.eq(input, output).all())
      new_vocab_size = 45
      model.resize_token_embeddings(new_vocab_size)
      input_new, output_new = _get_embs(model)
      self.assertEqual(
          input_new.shape, (new_vocab_size, config.d_model)
      )
      self.assertEqual(
          output_new.shape, (new_vocab_size, config.d_model)
      )
      self.assertTrue(torch.eq(input_new, output_new).all())
  
imports: import copy
  import tempfile
  import unittest
  import timeout_decorator
  from transformers import MvpConfig, is_torch_available
  from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, require_torch_fp16, slow, torch_device
  from transformers.utils import cached_property
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 11 for calling the MvpHeadTests obj's underlying member method code with example usage: obj.test_resize_tokens_embeddings_more() and returns: m,  m