old_contents: # coding=utf-8
  # Copyright 2022 The Trax Authors.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  # Copyright 2020 The Trax Authors.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  # Lint as: python3
  """Tests for trax.layers.relattention."""
  
  from absl.testing import absltest
  import numpy as np
  
  import trax.layers as tl
  import trax.layers.research.rel_attention as ra
  
  
  class RelAttentionTest(absltest.TestCase):
  
    def test_fast_shift_matrix(self):
      layer = ra._fast_matrix_shift
      x = np.array([[[[-3., -2., -1., 0.], [-3., -2., -1.,
                                            0.], [-3., -2., -1., 0.],
                      [-3., -2., -1., 0.]]]]).astype(np.float32)
  
      y = layer(x)
      self.assertEqual(y.dtype, np.float32)
      self.assertEqual(
          tl.to_list(y), [[[[0., 0., -3., -2.], [-1., 0., 0., -3.],
                            [-2., -1., 0., 0.], [-3., -2., -1., 0.]]]])
  
  if __name__ == '__main__':
    absltest.main()
  
new_contents: # coding=utf-8
  # Copyright 2022 The Trax Authors.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  # Copyright 2020 The Trax Authors.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  """Tests for trax.layers.relattention."""
  
  from absl.testing import absltest
  import numpy as np
  
  import trax.layers as tl
  import trax.layers.research.rel_attention as ra
  
  
  class RelAttentionTest(absltest.TestCase):
  
    def test_fast_shift_matrix(self):
      layer = ra._fast_matrix_shift
      x = np.array([[[[-3., -2., -1., 0.], [-3., -2., -1.,
                                            0.], [-3., -2., -1., 0.],
                      [-3., -2., -1., 0.]]]]).astype(np.float32)
  
      y = layer(x)
      self.assertEqual(y.dtype, np.float32)
      self.assertEqual(
          tl.to_list(y), [[[[0., 0., -3., -2.], [-1., 0., 0., -3.],
                            [-2., -1., 0., 0.], [-3., -2., -1., 0.]]]])
  
  if __name__ == '__main__':
    absltest.main()
  
subject: Remove unused comments related to Python 2 compatibility.