code: def test_dialogue_assistant_data_processor_get_continuous_slots():
      slot_ids = [54, 54, 54, 19, 19, 18, 54, 54, 54]
      empty_slot_id = 54
      bio_slot_ids_to_unified_slot_ids = {18: 18, 19: 19, 54: 54}
      continuous_slots = (
          DialogueAssistantDataProcessor.get_continuous_slots(
              slot_ids, empty_slot_id, bio_slot_ids_to_unified_slot_ids
          )
      )
      assert continuous_slots == {19: [3, 5], 18: [5, 6]}
  
      # here 18 and 19 maps to the same slot (originally variants of B-slot and I-slot)
      slot_ids = [54, 54, 54, 19, 19, 18, 54, 54, 54]
      empty_slot_id = 54
      bio_slot_ids_to_unified_slot_ids = {18: 18, 19: 18, 54: 54}
      continuous_slots = (
          DialogueAssistantDataProcessor.get_continuous_slots(
              slot_ids, empty_slot_id, bio_slot_ids_to_unified_slot_ids
          )
      )
      assert continuous_slots == {18: [3, 6]}
  
      # test if function works when non-empty slots are at boundary
      slot_ids = [18, 54, 54, 19, 19]
      empty_slot_id = 54
      bio_slot_ids_to_unified_slot_ids = {18: 18, 19: 19, 54: 54}
      continuous_slots = (
          DialogueAssistantDataProcessor.get_continuous_slots(
              slot_ids, empty_slot_id, bio_slot_ids_to_unified_slot_ids
          )
      )
      assert continuous_slots == {18: [0, 1], 19: [3, 5]}
  
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 5 for calling a global function with example usage: test_dialogue_assistant_data_processor_get_continuous_slots() without return types