content: # Copyright 2017 Google Inc.
  #
  # 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.
  """
  Unit tests for loss-related operations.
  """
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  
  from seq2seq import losses as seq2seq_losses
  import tensorflow as tf
  import numpy as np
  
  
  class CrossEntropySequenceLossTest(tf.test.TestCase):
    """
    Test for `sqe2seq.losses.sequence_mask`.
    """
  
    def setUp(self):
      super(CrossEntropySequenceLossTest, self).setUp()
      tf.logging.set_verbosity(tf.logging.INFO)
      self.batch_size = 4
      self.sequence_length = 10
      self.vocab_size = 50
  
    def test_op(self):
      logits = np.random.randn(self.sequence_length, self.batch_size,
                               self.vocab_size)
      logits = logits.astype(np.float32)
      sequence_length = np.array([1, 2, 3, 4])
      targets = np.random.randint(0, self.vocab_size,
                                  [self.sequence_length, self.batch_size])
      losses = seq2seq_losses.cross_entropy_sequence_loss(logits, targets,
                                                          sequence_length)
  
      with self.test_session() as sess:
        losses_ = sess.run(losses)
  
      # Make sure all losses not past the sequence length are > 0
      np.testing.assert_array_less(np.zeros_like(losses_[:1, 0]), losses_[:1, 0])
      np.testing.assert_array_less(np.zeros_like(losses_[:2, 1]), losses_[:2, 1])
      np.testing.assert_array_less(np.zeros_like(losses_[:3, 2]), losses_[:3, 2])
  
      # Make sure all losses past the sequence length are 0
      np.testing.assert_array_equal(losses_[1:, 0], np.zeros_like(losses_[1:, 0]))
      np.testing.assert_array_equal(losses_[2:, 1], np.zeros_like(losses_[2:, 1]))
      np.testing.assert_array_equal(losses_[3:, 2], np.zeros_like(losses_[3:, 2]))
  
  
  if __name__ == "__main__":
    tf.test.main()
  