code: def test_none_correct(self):
      y_true = [0, 0, 0, 0, 1]
      y_pred = [1, 1, 1, 1, 0]
  
      result = metrics.false_negative_rate(y_true, y_pred)
      assert result == 1
  
imports: import numpy
  import pytest
  import sklearn.metrics
  import fairlearn.metrics
  from fairlearn.metrics._base_metrics import _get_labels_for_confusion_matrix
label_desc: Use image node_id 2 for calling the TestFNR obj's underlying member method code with example usage: obj.test_none_correct() without return types