code: def test_decode(self):
      decoded_info = self.trainer.decode(
          self.initial_state, self.decoder_step, self.supervision
      )
  
      # Our loss is the negative log sum of the scores from each target sequence.  The score for
      # each sequence in our simple transition system is just `-sequence_length`.
      instance0_loss = math.log(
          math.exp(-3) * 3
      )  # all three sequences have length 3
      instance1_loss = math.log(
          math.exp(-2) + math.exp(-3)
      )  # one has length 2, one has length 3
      expected_loss = -(instance0_loss + instance1_loss) / 2
      assert_almost_equal(
          decoded_info["loss"].data.numpy(), expected_loss
      )
  
file_path: magnitude/pymagnitude/third_party/allennlp/tests/nn/decoding/decoder_trainers/maximum_marginal_likelihood_test.py
imports: from __future__ import division
  from __future__ import absolute_import
  import math
  from numpy.testing import assert_almost_equal
  import torch
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.nn.decoding.decoder_trainers import MaximumMarginalLikelihood
  from ..simple_transition_system import SimpleDecoderState, SimpleDecoderStep
label_desc: Use image node_id 2 for calling the TestMaximumMarginalLikelihood obj's underlying member method code with example usage: obj.test_decode() without return types