code: def test_should_fit_and_parse_empty_intent(self):
      # Given
      dataset = {
          "intents": {
              "dummy_intent": {
                  "utterances": [{"data": [{"text": " "}]}]
              }
          },
          "language": "en",
          "entities": dict(),
      }
  
      engine = SnipsNLUEngine(resources=self.get_resources("en"))
  
      # When / Then
      engine.fit(dataset)
      engine.parse("ya", intents=["dummy_intent"])
  
imports: from __future__ import unicode_literals
  import io
  import shutil
  import sys
  from builtins import str
  from unittest import skipIf
  from checksumdir import dirhash
  from mock import MagicMock, patch
  from snips_nlu_parsers import get_all_languages
  import snips_nlu
  from snips_nlu.common.io_utils import temp_dir
  from snips_nlu.constants import END, LANGUAGE, LANGUAGE_EN, RES_ENTITY, RES_INPUT, RES_INTENT, RES_INTENT_NAME, RES_MATCH_RANGE, RES_RAW_VALUE, RES_SLOTS, RES_SLOT_NAME, RES_VALUE, START
  from snips_nlu.dataset import Dataset, validate_and_format_dataset
  from snips_nlu.entity_parser import BuiltinEntityParser, CustomEntityParser, CustomEntityParserUsage
  from snips_nlu.exceptions import IntentNotFoundError, InvalidInputError, NotTrained, IncompatibleModelError, PersistingError, LoadingError
  from snips_nlu.intent_parser import IntentParser
  from snips_nlu.nlu_engine import SnipsNLUEngine
  from snips_nlu.pipeline.configs import NLUEngineConfig
  from snips_nlu.resources import load_resources
  from snips_nlu.result import custom_slot, empty_result, intent_classification_result, parsing_result, resolved_slot, unresolved_slot, extraction_result
  from snips_nlu.tests.utils import FixtureTest, MockIntentParser, get_empty_dataset
label_desc: Use image node_id 29 for calling the TestSnipsNLUEngine obj's underlying member method code with example usage: obj.test_should_fit_and_parse_empty_intent() without return types