class_docstr: A vocabulary that maps tokens to ints (storing a vocabulary).
  
  Attributes:
      _token_count: A collections.Counter object holding the frequencies of tokens
          in the data used to build the Vocabulary.
      _token2id: A collections.defaultdict instance mapping token strings to
          numerical identifiers.
      _id2token: A list of token strings indexed by their numerical identifiers.
class_docstr_tok: ["A","vocabulary","that","maps","tokens","to","ints","(","storing","a","vocabulary",")",".","Attributes",":","_token_count",":","A","collections.Counter","object","holding","the","frequencies","of","tokens","in","the","data","used","to","build","the","Vocabulary",".","_token2id",":","A","collections.defaultdict","instance","mapping","token","strings","to","numerical","identifiers",".","_id2token",":","A","list","of","token","strings","indexed","by","their","numerical","identifiers","."]
docstr: Process token before following methods:
  * add_token
  * add_documents
  * doc2id
  * token_to_id
  
  Args:
      token (str): token to process.
  
  Returns:
      str: processed token string.
docstr_tok: ["Process","token","before","following","methods",":","*","add_token","*","add_documents","*","doc2id","*","token_to_id","Args",":","token","(","str",")",":","token","to","process",".","Returns",":","str",":","processed","token","string","."]
code: def process_token(self, token):
      """Process token before following methods:
      * add_token
      * add_documents
      * doc2id
      * token_to_id
  
      Args:
          token (str): token to process.
  
      Returns:
          str: processed token string.
      """
      if self._lower:
          token = token.lower()
  
      return token
  
imports: from ....imports import *
label_desc: Use image node_id 8 for calling the Vocabulary obj's underlying member method code with example usage: obj.process_token(token) and returns: token