class_docstr: Abstraction which performs intent parsing
  
  A custom intent parser must inherit this class to be used in a
  :class:`.SnipsNLUEngine`
class_docstr_tok: ["Abstraction","which","performs","intent","parsing","A","custom","intent","parser","must","inherit","this","class","to","be","used","in","a",":","class",":","`",".SnipsNLUEngine","`"]
docstr: Performs intent parsing on the provided *text*
  
  Args:
      text (str): input
      intents (str or list of str): if provided, reduces the scope of
          intent parsing to the provided list of intents
      top_n (int, optional): when provided, this method will return a
          list of at most top_n most likely intents, instead of a single
          parsing result.
          Note that the returned list can contain less than ``top_n``
          elements, for instance when the parameter ``intents`` is not
          None, or when ``top_n`` is greater than the total number of
          intents.
  
  Returns:
      dict or list: the most likely intent(s) along with the extracted
      slots. See :func:`.parsing_result` and :func:`.extraction_result`
      for the output format.
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code: def parse(self, text, intents, top_n):
      """Performs intent parsing on the provided *text*
  
      Args:
          text (str): input
          intents (str or list of str): if provided, reduces the scope of
              intent parsing to the provided list of intents
          top_n (int, optional): when provided, this method will return a
              list of at most top_n most likely intents, instead of a single
              parsing result.
              Note that the returned list can contain less than ``top_n``
              elements, for instance when the parameter ``intents`` is not
              None, or when ``top_n`` is greater than the total number of
              intents.
  
      Returns:
          dict or list: the most likely intent(s) along with the extracted
          slots. See :func:`.parsing_result` and :func:`.extraction_result`
          for the output format.
      """
      pass
  
file_path: snips-nlu/snips_nlu/intent_parser/intent_parser.py
imports: from abc import abstractmethod, ABCMeta
  from future.utils import with_metaclass
  from snips_nlu.common.abc_utils import classproperty
  from snips_nlu.pipeline.processing_unit import ProcessingUnit
label_desc: Use image node_id 3 for calling the IntentParser obj's underlying member method code with example usage: obj.parse(text, intents, top_n) without return types