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: Extract slots from a text input, with the knowledge of the intent
  
  Args:
      text (str): input
      intent (str): the intent which the input corresponds to
  
  Returns:
      list: the list of extracted slots
  
  Raises:
      IntentNotFoundError: when the intent was not part of the training
          data
docstr_tok: ["Extract","slots","from","a","text","input",",","with","the","knowledge","of","the","intent","Args",":","text","(","str",")",":","input","intent","(","str",")",":","the","intent","which","the","input","corresponds","to","Returns",":","list",":","the","list","of","extracted","slots","Raises",":","IntentNotFoundError",":","when","the","intent","was","not","part","of","the","training","data"]
code: def get_slots(self, text, intent):
      """Extract slots from a text input, with the knowledge of the intent
  
      Args:
          text (str): input
          intent (str): the intent which the input corresponds to
  
      Returns:
          list: the list of extracted slots
  
      Raises:
          IntentNotFoundError: when the intent was not part of the training
              data
      """
      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 5 for calling the IntentParser obj's underlying member method code with example usage: obj.get_slots(text, intent) without return types