code: def testGroverBondVocabPredictor():
      from deepchem.models.torch_models.grover_layers import (
          GroverBondVocabPredictor,
      )
  
      num_bonds = 20
      in_features, vocab_size = 16, 10
      layer = GroverBondVocabPredictor(vocab_size, in_features)
      embedding = torch.randn(num_bonds * 2, in_features)
      result = layer(embedding)
      assert result.shape == (num_bonds, vocab_size)
  
file_path: deepchem/deepchem/models/torch_models/tests/test_grover_layers.py
imports: import pytest
label_desc: Use image node_id 2 for calling a global function with example usage: testGroverBondVocabPredictor() without return types