class_docstr: Configuration of a :class:`.CooccurrenceVectorizer` object
class_docstr_tok: ["Configuration","of","a",":","class",":","`",".CooccurrenceVectorizer","`","object"]
code: def get_required_resources(self):
      return {
          STOP_WORDS: self.filter_stop_words,
          # We require the parser to be trained without stems because we
          # don't normalize and stem when processing in the
          # CooccurrenceVectorizer (in order to run the builtin and
          # custom parser on the same unormalized input).
          # Requiring no stems ensures we'll be able to parse the unstemmed
          # input
          CUSTOM_ENTITY_PARSER_USAGE: CustomEntityParserUsage.WITHOUT_STEMS,
      }
  
imports: from __future__ import unicode_literals
  from snips_nlu.common.from_dict import FromDict
  from snips_nlu.constants import CUSTOM_ENTITY_PARSER_USAGE, NOISE, STEMS, STOP_WORDS, WORD_CLUSTERS
  from snips_nlu.entity_parser.custom_entity_parser import CustomEntityParserUsage
  from snips_nlu.pipeline.configs import Config, ProcessingUnitConfig
  from snips_nlu.resources import merge_required_resources
label_desc: Use image node_id 3 for calling the CooccurrenceVectorizerConfig obj's underlying member method code with example usage: obj.get_required_resources() and returns: dict