code: def test_decode(self):
      spans = torch.LongTensor(
          [[1, 2], [3, 4], [3, 7], [5, 6], [14, 56], [17, 80]]
      )
  
      antecedent_indices = torch.LongTensor(
          [
              [0, 0, 0, 0, 0, 0],
              [0, 0, 0, 0, 0, 0],
              [1, 0, 0, 0, 0, 0],
              [2, 1, 0, 0, 0, 0],
              [3, 2, 1, 0, 0, 0],
              [4, 3, 2, 1, 0, 0],
          ]
      )
  
      spans = spans.unsqueeze(0)
      antecedent_indices = antecedent_indices
      # Indices into ``antecedent_indices`` indicating the predicted antecedent
      # index in ``top_spans``.
      predicted_antecedents = torch.LongTensor([-1, 0, -1, -1, 1, 3])
      predicted_antecedents = predicted_antecedents.unsqueeze(0)
      output_dict = {
          "top_spans": spans,
          "antecedent_indices": antecedent_indices,
          "predicted_antecedents": predicted_antecedents,
      }
      output = self.model.decode(output_dict)
  
      clusters = output["clusters"][0]
      gold1 = [(1, 2), (3, 4), (17, 80)]
      gold2 = [(3, 7), (14, 56)]
  
      assert len(clusters) == 2
      assert gold1 in clusters
      assert gold2 in clusters
  
file_path: magnitude/pymagnitude/third_party/allennlp/tests/models/coreference_resolution/coref_test.py
imports: from __future__ import division
  from __future__ import absolute_import
  import torch
  from allennlp.common.testing import ModelTestCase
label_desc: Use image node_id 3 for calling the CorefTest obj's underlying member method code with example usage: obj.test_decode() without return types