text: # Copyright 2015 The TensorFlow Authors. 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 tensorflow.ops.reverse_sequence_op."""
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import numpy as np
  import tensorflow as tf
  
  
  class WhereOpTest(tf.test.TestCase):
  
    def _testWhere(self, x, truth, expected_err_re=None):
      with self.test_session():
        ans = tf.where(x)
        self.assertEqual([None, x.ndim], ans.get_shape().as_list())
        if expected_err_re is None:
          tf_ans = ans.eval()
          self.assertAllClose(tf_ans, truth, atol=1e-10)
        else:
          with self.assertRaisesOpError(expected_err_re):
            ans.eval()
  
    def testWrongNumbers(self):
      with self.test_session():
        with self.assertRaises(ValueError):
          tf.where([False, True], [1, 2], None)
        with self.assertRaises(ValueError):
          tf.where([False, True], None, [1, 2])
  
    def testBasicMat(self):
      x = np.asarray([[True, False], [True, False]])
  
      # Ensure RowMajor mode
      truth = np.asarray([[0, 0], [1, 0]], dtype=np.int64)
  
      self._testWhere(x, truth)
  
    def testBasic3Tensor(self):
      x = np.asarray(
          [[[True, False], [True, False]], [[False, True], [False, True]],
           [[False, False], [False, True]]])
  
      # Ensure RowMajor mode
      truth = np.asarray(
          [[0, 0, 0], [0, 1, 0], [1, 0, 1], [1, 1, 1], [2, 1, 1]],
          dtype=np.int64)
  
      self._testWhere(x, truth)
  
    def testThreeArgument(self):
      x = np.array([[-2, 3, -1], [1, -3, -3]])
      np_val = np.where(x > 0, x*x, -x)
      with self.test_session():
        tf_val = tf.where(tf.constant(x) > 0, x*x, -x).eval()
      self.assertAllEqual(tf_val, np_val)
  
  if __name__ == "__main__":
    tf.test.main()
  