code: def test_dialogue_sgd_dataset_naive_tokenize():
      utterance = (
          "I am feeling hungry so I would like to find a place to eat."
      )
      tokens = [
          "I",
          " ",
          "am",
          " ",
          "feeling",
          " ",
          "hungry",
          " ",
          "so",
          " ",
          "I",
          " ",
          "would",
          " ",
          "like",
          " ",
          "to",
          " ",
          "find",
          " ",
          "a",
          " ",
          "place",
          " ",
          "to",
          " ",
          "eat",
          ".",
      ]
      assert tokens == DialogueSGDBERTDataset._naive_tokenize(utterance)
  
imports: import pytest
  import torch
  from nemo.collections.nlp.data.dialogue.data_processor.assistant_data_processor import DialogueAssistantDataProcessor
  from nemo.collections.nlp.data.dialogue.data_processor.data_processor import DialogueDataProcessor
  from nemo.collections.nlp.data.dialogue.data_processor.sgd_data_processor import DialogueSGDDataProcessor
  from nemo.collections.nlp.data.dialogue.dataset.dialogue_gpt_classification_dataset import DialogueGPTClassificationDataset
  from nemo.collections.nlp.data.dialogue.dataset.dialogue_s2s_generation_dataset import DialogueS2SGenerationDataset
  from nemo.collections.nlp.data.dialogue.dataset.dialogue_sgd_bert_dataset import DialogueSGDBERTDataset
  from nemo.collections.nlp.metrics.dialogue_metrics import DialogueClassificationMetrics, DialogueGenerationMetrics
  from nemo.collections.nlp.models.dialogue.dialogue_nearest_neighbour_model import DialogueNearestNeighbourModel
label_desc: Use image node_id 11 for calling a global function with example usage: test_dialogue_sgd_dataset_naive_tokenize() without return types