class_docstr: ALBERT model
class_docstr_tok: ["ALBERT","model"]
docstr: Gets the tokenizer that is customized for this module.
docstr_tok: ["Gets","the","tokenizer","that","is","customized","for","this","module","."]
code: def get_tokenizer(*args, **kwargs):
      """
      Gets the tokenizer that is customized for this module.
      """
      return AlbertTokenizer.from_pretrained(
          pretrained_model_name_or_path="albert-base-v2",
          *args,
          **kwargs,
      )
  
file_path: PaddleHub/modules/text/language_model/albert-base-v2/module.py
imports: import math
  import os
  from typing import Dict
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddlenlp.metrics import ChunkEvaluator
  from paddlenlp.transformers.albert.modeling import AlbertForSequenceClassification
  from paddlenlp.transformers.albert.modeling import AlbertForTokenClassification
  from paddlenlp.transformers.albert.modeling import AlbertModel
  from paddlenlp.transformers.albert.tokenizer import AlbertTokenizer
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.nlp_module import TransformerModule
  from paddlehub.utils.log import logger
label_desc: Use image node_id 3 for calling the Albert obj's underlying member method code with example usage: obj.get_tokenizer() and returns: AlbertTokenizer