class_docstr: Detects offensive language using a list of offensive language and phrases from
  https://github.com/LDNOOBW.
class_docstr_tok: ["Detects","offensive","language","using","a","list","of","offensive","language","and","phrases","from","https",":","\/\/github.com\/LDNOOBW","."]
docstr: Determine if text contains any offensive words in the filter.
docstr_tok: ["Determine","if","text","contains","any","offensive","words","in","the","filter","."]
code: def contains_offensive_language(self, text):
      """
      Determine if text contains any offensive words in the filter.
      """
      if not text:
          return None
      if type(text) is str:
          toks = self.tokenize(text.lower())
      elif type(text) is list or type(text) is tuple:
          toks = text
  
      for i in range(len(toks)):
          res = self._check_sequence(toks, i, self.offensive_trie)
          if res:
              return res
  
      return None
  
imports: from parlai.agents.transformer.transformer import TransformerClassifierAgent
  from parlai.core.agents import create_agent, create_agent_from_shared
  from parlai.tasks.dialogue_safety.agents import OK_CLASS, NOT_OK_CLASS
  from parlai.utils.typing import TShared
  from parlai.utils.io import PathManager
  import parlai.utils.logging
  import os
label_desc: Use image node_id 5 for calling the OffensiveStringMatcher obj's underlying member method code with example usage: obj.contains_offensive_language(text) and returns: None, None, res