code: def test_bert_get_pretrained(model_name, ctx):
      assert len(list_pretrained_bert()) > 0
      with tempfile.TemporaryDirectory() as root, ctx:
          (
              cfg,
              tokenizer,
              backbone_params_path,
              mlm_params_path,
          ) = get_pretrained_bert(
              model_name, load_backbone=True, load_mlm=True, root=root
          )
          assert cfg.MODEL.vocab_size == len(tokenizer.vocab)
          bert_model = BertModel.from_cfg(cfg)
          bert_model.load_parameters(backbone_params_path)
          bert_mlm_model = BertForMLM(cfg)
          if mlm_params_path is not None:
              bert_mlm_model.load_parameters(mlm_params_path)
          bert_mlm_model = BertForMLM(cfg)
          bert_mlm_model.backbone_model.load_parameters(
              backbone_params_path
          )
  
file_path: gluon-nlp/tests/test_models_bert.py
imports: import pytest
  from numpy.testing import assert_allclose
  import mxnet
  import tempfile
  from gluonnlp.models.bert import BertModel, BertForMLM, BertForPretrain, list_pretrained_bert, get_pretrained_bert
  from gluonnlp.utils.testing import verify_backbone_fp16
label_desc: Use image node_id 3 for calling a global function with example usage: test_bert_get_pretrained(model_name, ctx) without return types