class_docstr: Intent parser which consists in two steps: intent classification then
  slot filling
class_docstr_tok: ["Intent","parser","which","consists","in","two","steps",":","intent","classification","then","slot","filling"]
docstr: Persists the object at the given path
docstr_tok: ["Persists","the","object","at","the","given","path"]
code: def persist(self, path):
      """Persists the object at the given path"""
      path.mkdir()
      sorted_slot_fillers = sorted(iteritems(self.slot_fillers))
      slot_fillers = []
      for i, (intent, slot_filler) in enumerate(sorted_slot_fillers):
          slot_filler_name = "slot_filler_%s" % i
          slot_filler.persist(path / slot_filler_name)
          slot_fillers.append(
              {"intent": intent, "slot_filler_name": slot_filler_name}
          )
  
      if self.intent_classifier is not None:
          self.intent_classifier.persist(path / "intent_classifier")
  
      model = {
          "config": self.config.to_dict(),
          "slot_fillers": slot_fillers,
      }
      model_json = json_string(model)
      model_path = path / "intent_parser.json"
      with model_path.open(mode="w") as f:
          f.write(model_json)
      self.persist_metadata(path)
  
imports: from __future__ import unicode_literals
  import json
  import logging
  from builtins import str
  from copy import deepcopy
  from datetime import datetime
  from pathlib import Path
  from future.utils import iteritems, itervalues
  from snips_nlu.common.log_utils import log_elapsed_time, log_result
  from snips_nlu.common.utils import check_persisted_path, elapsed_since, fitted_required, json_string
  from snips_nlu.constants import INTENTS, RES_INTENT_NAME
  from snips_nlu.dataset import validate_and_format_dataset
  from snips_nlu.exceptions import IntentNotFoundError, LoadingError
  from snips_nlu.intent_classifier import IntentClassifier
  from snips_nlu.intent_parser.intent_parser import IntentParser
  from snips_nlu.pipeline.configs import ProbabilisticIntentParserConfig
  from snips_nlu.result import parsing_result, extraction_result
  from snips_nlu.slot_filler import SlotFiller
label_desc: Use image node_id 7 for calling the ProbabilisticIntentParser obj's underlying member method code with example usage: obj.persist(path) without return types