code: # -*- coding: utf-8 -*-
  # Copyright 2018 Google LLC. All Rights Reserved.
  #
  # 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 the math operations."""
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  # Dependency imports
  
  import tensorflow as tf
  import tensorflow_compression as tfc
  
  
  class MathTest(tf.test.TestCase):
  
    def _test_upper_bound(self, gradient):
      inputs = tf.placeholder(dtype=tf.float32)
      outputs = tfc.upper_bound(inputs, 0, gradient=gradient)
      pgrads, = tf.gradients([outputs], [inputs], [tf.ones_like(inputs)])
      ngrads, = tf.gradients([outputs], [inputs], [-tf.ones_like(inputs)])
  
      inputs_feed = [-1, 1]
      outputs_expected = [-1, 0]
      if gradient == "disconnected":
        pgrads_expected = [1, 0]
        ngrads_expected = [-1, 0]
      elif gradient == "identity":
        pgrads_expected = [1, 1]
        ngrads_expected = [-1, -1]
      else:
        pgrads_expected = [1, 1]
        ngrads_expected = [-1, 0]
  
      with self.test_session() as sess:
        outputs, pgrads, ngrads = sess.run(
            [outputs, pgrads, ngrads], {inputs: inputs_feed})
        self.assertAllEqual(outputs, outputs_expected)
        self.assertAllEqual(pgrads, pgrads_expected)
        self.assertAllEqual(ngrads, ngrads_expected)
  
    def test_upper_bound_disconnected(self):
      self._test_upper_bound("disconnected")
  
    def test_upper_bound_identity(self):
      self._test_upper_bound("identity")
  
    def test_upper_bound_identity_if_towards(self):
      self._test_upper_bound("identity_if_towards")
  
    def test_upper_bound_invalid(self):
      with self.assertRaises(ValueError):
        self._test_upper_bound("invalid")
  
    def _test_lower_bound(self, gradient):
      inputs = tf.placeholder(dtype=tf.float32)
      outputs = tfc.lower_bound(inputs, 0, gradient=gradient)
      pgrads, = tf.gradients([outputs], [inputs], [tf.ones_like(inputs)])
      ngrads, = tf.gradients([outputs], [inputs], [-tf.ones_like(inputs)])
  
      inputs_feed = [-1, 1]
      outputs_expected = [0, 1]
      if gradient == "disconnected":
        pgrads_expected = [0, 1]
        ngrads_expected = [0, -1]
      elif gradient == "identity":
        pgrads_expected = [1, 1]
        ngrads_expected = [-1, -1]
      else:
        pgrads_expected = [0, 1]
        ngrads_expected = [-1, -1]
  
      with self.test_session() as sess:
        outputs, pgrads, ngrads = sess.run(
            [outputs, pgrads, ngrads], {inputs: inputs_feed})
        self.assertAllEqual(outputs, outputs_expected)
        self.assertAllEqual(pgrads, pgrads_expected)
        self.assertAllEqual(ngrads, ngrads_expected)
  
    def test_lower_bound_disconnected(self):
      self._test_lower_bound("disconnected")
  
    def test_lower_bound_identity(self):
      self._test_lower_bound("identity")
  
    def test_lower_bound_identity_if_towards(self):
      self._test_lower_bound("identity_if_towards")
  
    def test_lower_bound_invalid(self):
      with self.assertRaises(ValueError):
        self._test_lower_bound("invalid")
  
  
  if __name__ == "__main__":
    tf.test.main()
  
apis: tensorflow.ones_like tensorflow.placeholder tensorflow.test.main