old_contents: # pylint: disable=no-self-use,invalid-name
  import torch
  import numpy
  
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.modules.seq2seq_encoders import PassThroughEncoder
  
  
  class TestStackedSelfAttention(AllenNlpTestCase):
      def test_get_dimension_is_correct(self):
          encoder = PassThroughEncoder(input_dim=9)
          assert encoder.get_input_dim() == 9
          assert encoder.get_output_dim() == 9
  
      def test_pass_through_encoder_passes_through(self):
          encoder = PassThroughEncoder(input_dim=9)
          tensor = torch.randn([2, 3, 9])
          output = encoder(tensor)
          numpy.testing.assert_array_almost_equal(tensor.detach().cpu().numpy(),
                                                  output.detach().cpu().numpy())
  
new_contents: # pylint: disable=no-self-use,invalid-name
  import torch
  import numpy
  
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.modules.seq2seq_encoders import PassThroughEncoder
  
  
  class TestPassThroughEncoder(AllenNlpTestCase):
      def test_get_dimension_is_correct(self):
          encoder = PassThroughEncoder(input_dim=9)
          assert encoder.get_input_dim() == 9
          assert encoder.get_output_dim() == 9
  
      def test_pass_through_encoder_passes_through(self):
          encoder = PassThroughEncoder(input_dim=9)
          tensor = torch.randn([2, 3, 9])
          output = encoder(tensor)
          numpy.testing.assert_array_almost_equal(tensor.detach().cpu().numpy(),
                                                  output.detach().cpu().numpy())
  
subject: rename test case (#2441)