code: def test_featurize():
      """Test that BertFeaturizer.featurize() correctly featurizes all sequences,
      correctly outputs input_ids and attention_mask."""
      from deepchem.feat.bert_tokenizer import BertFeaturizer
      from transformers import BertTokenizerFast
  
      sequences = [
          "[CLS] D L I P T S S K L V [SEP]",
          "[CLS] V K K A F F A L V T [SEP]",
      ]
      sequence_long = [
          "[CLS] D L I P T S S K L V V K K A F F A L V T [SEP]"
      ]
      tokenizer = BertTokenizerFast.from_pretrained(
          "Rostlab/prot_bert", do_lower_case=False
      )
      featurizer = BertFeaturizer(tokenizer)
      feats = featurizer(sequences)
      long_feat = featurizer(sequence_long)
      assert len(feats) == 2
      assert all([len(f) == 3 for f in feats])
      assert len(long_feat) == 1
      assert len(long_feat[0] == 2)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_featurize() without return types