code: def test_dialogue_metric_generation_f1():
      generated_field = "That is so good"
      ground_truth_field = "That is so awesome"
  
      precision, recall, f1 = DialogueGenerationMetrics._get_one_f1(
          generated_field, ground_truth_field
      )
      assert precision == 75
      assert recall == 75
      assert f1 == 75
  
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 1 for calling a global function with example usage: test_dialogue_metric_generation_f1() without return types