code: def test_transformers_too_short_utt():
      if not is_torch_1_8_plus:
          return
      idim = 400
      postencoder = HuggingFaceTransformersPostEncoder(
          idim, "akreal/tiny-random-bert", 2
      )
      x = torch.randn([2, 3, idim], requires_grad=True)
      x_lengths = torch.LongTensor([3, 2])
      with pytest.raises(Exception):
          y, y_lengths = postencoder(x, x_lengths)
  
imports: import pytest
  import torch
  from packaging.version import parse
  from espnet2.asr.postencoder.hugging_face_transformers_postencoder import HuggingFaceTransformersPostEncoder
label_desc: Use image node_id 2 for calling a global function with example usage: test_transformers_too_short_utt() without return types