code: def test_albert_get_pretrained(model_name):
      assert len(list_pretrained_albert()) > 0
      with tempfile.TemporaryDirectory() as root:
          (
              cfg,
              tokenizer,
              backbone_params_path,
              mlm_params_path,
          ) = get_pretrained_albert(
              model_name, load_backbone=True, load_mlm=True, root=root
          )
          assert cfg.MODEL.vocab_size == len(tokenizer.vocab)
          albert_model = AlbertModel.from_cfg(cfg)
          albert_model.load_parameters(backbone_params_path)
          albert_mlm_model = AlbertForMLM(cfg)
          if mlm_params_path is not None:
              albert_mlm_model.load_parameters(mlm_params_path)
          # Just load the backbone
          albert_mlm_model = AlbertForMLM(cfg)
          albert_mlm_model.backbone_model.load_parameters(
              backbone_params_path
          )
  
file_path: gluon-nlp/tests/test_models_albert.py
imports: import pytest
  import numpy
  from numpy.testing import assert_allclose
  import mxnet
  import tempfile
  from gluonnlp.models.albert import AlbertModel, AlbertForMLM, AlbertForPretrain, list_pretrained_albert, get_pretrained_albert
label_desc: Use image node_id 6 for calling a global function with example usage: test_albert_get_pretrained(model_name) without return types