old_contents: #  Copyright 2015-present Scikit Flow 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.
  
  import numpy as np
  import tensorflow as tf
  
  from skflow import ops
  
  
  class DropoutTest(tf.test.TestCase):
  
      def test_dropout_float(self):
          with self.test_session():
              x = tf.placeholder(tf.float32, [5, 5])
              y = ops.dropout(x, 0.5)
              probs = tf.get_collection(ops.DROPOUTS)
              self.assertEqual(len(probs), 1)
  
  
  if __name__ == '__main__':
      tf.test.main()
  
new_contents: #  Copyright 2015-present Scikit Flow 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.
  
  import numpy as np
  import tensorflow as tf
  
  from skflow import ops
  
  
  class DropoutTest(tf.test.TestCase):
  
      def test_dropout_float(self):
          with self.test_session() as session:
              x = tf.placeholder(tf.float32, [5, 5])
              y = ops.dropout(x, 0.5)
              probs = tf.get_collection(ops.DROPOUTS)
              session.run(tf.initialize_all_variables())
              self.assertEqual(len(probs), 1)
              self.assertEqual(session.run(probs[0]), 0.5)
  
      def test_dropout_tensor(self):
          with self.test_session():
              x = tf.placeholder(tf.float32, [5, 5])
              y = tf.get_variable("prob", [], initializer=tf.constant_initializer(0.5))
              z = ops.dropout(x, y)
              probs = tf.get_collection(ops.DROPOUTS)
              self.assertEqual(probs, [y])
  
  
  if __name__ == '__main__':
      tf.test.main()
  
subject: Test for dropout probability be a tensor