code: def test_should_parse_intent(self):
      # Given
      dataset_stream = io.StringIO(
          """
  ---
  type: intent
  name: intent1
  utterances:
    - foo bar baz
  
  ---
  type: intent
  name: intent2
  utterances:
    - foo bar ban"""
      )
      dataset = Dataset.from_yaml_files("en", [dataset_stream]).json
      parser = DeterministicIntentParser().fit(dataset)
      text = "foo bar ban"
  
      # When
      parsing = parser.parse(text)
  
      # Then
      probability = 1.0
      expected_intent = intent_classification_result(
          intent_name="intent2", probability=probability
      )
  
      self.assertEqual(expected_intent, parsing[RES_INTENT])
  
imports: from __future__ import unicode_literals
  import io
  from builtins import range
  from copy import deepcopy
  from checksumdir import dirhash
  from mock import patch
  from snips_nlu.common.io_utils import temp_dir
  from snips_nlu.constants import DATA, END, ENTITY, LANGUAGE_EN, RES_ENTITY, RES_INTENT, RES_INTENT_NAME, RES_PROBA, RES_SLOTS, RES_VALUE, SLOT_NAME, START, TEXT, STOP_WORDS
  from snips_nlu.dataset import Dataset
  from snips_nlu.exceptions import IntentNotFoundError, NotTrained
  from snips_nlu.intent_parser.deterministic_intent_parser import DeterministicIntentParser, _deduplicate_overlapping_slots, _get_range_shift
  from snips_nlu.pipeline.configs import DeterministicIntentParserConfig
  from snips_nlu.result import extraction_result, intent_classification_result, unresolved_slot, empty_result, parsing_result
  from snips_nlu.tests.utils import FixtureTest, TEST_PATH
label_desc: Use image node_id 2 for calling the TestDeterministicIntentParser obj's underlying member method code with example usage: obj.test_should_parse_intent() without return types