code: def test_forward_runs_when_initialized_from_params(self):
      # This code just passes things off to `transformers`, so we only have a very simple
      # test.
      params = Params({"model_name": "bert-base-uncased"})
      embedder = PretrainedTransformerEmbedder.from_params(
          params
      ).cuda()
      token_ids = torch.randint(0, 100, (1, 4))
      mask = torch.randint(0, 2, (1, 4)).bool()
      output = embedder(token_ids=token_ids.cuda(), mask=mask.cuda())
      assert tuple(output.size()) == (1, 4, 768)
  
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 2 for calling the TestPretrainedTransformerEmbedder obj's underlying member method code with example usage: obj.test_forward_runs_when_initialized_from_params() without return types