code: def test_export_custom_bert_model(self):
      from transformers import BertModel
  
      vocab = [
          "[UNK]",
          "[SEP]",
          "[CLS]",
          "[PAD]",
          "[MASK]",
          "some",
          "other",
          "words",
      ]
      with NamedTemporaryFile(mode="w+t") as vocab_file:
          vocab_file.write("\n".join(vocab))
          vocab_file.flush()
          tokenizer = BertTokenizerFast(vocab_file.name)
  
      with TemporaryDirectory() as bert_save_dir:
          model = BertModel(BertConfig(vocab_size=len(vocab)))
          model.save_pretrained(bert_save_dir)
          self._test_export(bert_save_dir, "pt", 12, tokenizer)
  
imports: import unittest
  from pathlib import Path
  from tempfile import NamedTemporaryFile, TemporaryDirectory
  from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
  from transformers.convert_graph_to_onnx import convert, ensure_valid_input, generate_identified_filename, infer_shapes, quantize
  from transformers.testing_utils import require_tf, require_tokenizers, require_torch, slow
label_desc: Use image node_id 3 for calling the OnnxExportTestCase obj's underlying member method code with example usage: obj.test_export_custom_bert_model() without return types