class_docstr: The base class for Embedding models.
class_docstr_tok: ["The","base","class","for","Embedding","models","."]
docstr: Download vocab from url
docstr_tok: ["Download","vocab","from","url"]
code: def _download_vocab(self):
      """
      Download vocab from url
      """
      url = EMBEDDING_URL_ROOT + "/" + f"vocab.{self.embedding_name}"
      get_path_from_url(url, EMBEDDING_HOME)
  
imports: import copy
  import functools
  import inspect
  import io
  import json
  import os
  import six
  from typing import List, Tuple, Union
  import paddle
  import paddle.nn
  from packaging.version import Version
  from paddle.dataset.common import DATA_HOME
  from paddle.utils.download import get_path_from_url
  from paddlehub.module.module import serving, RunModule, runnable
  from paddlehub.utils.log import logger
  from paddlehub.utils.utils import reseg_token_label
  import paddlenlp
  from paddlenlp.embeddings.token_embedding import EMBEDDING_HOME, EMBEDDING_URL_ROOT
  from paddlenlp.data import JiebaTokenizer
  from paddlehub.compat.module.nlp_module import DataFormatError
label_desc: Use image node_id 1 for calling the EmbeddingModule obj's underlying member method code with example usage: obj._download_vocab() without return types