# Copyright 2015 Google Inc. 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.session_ops."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import tensorflow as tf


class SessionOpsTest(tf.test.TestCase):

  def testHandleBasic(self):
    with self.test_session() as sess:
      # Return a handle.
      a = tf.constant(10)
      b = tf.constant(5)
      c = tf.mul(a, b)
      h = tf.get_session_handle(c)
      h = sess.run(h)

      # Feed a tensor handle.
      f, x = tf.get_session_tensor(tf.int32)
      y = tf.mul(x, 10)
      self.assertEqual(500, sess.run(y, feed_dict={f: h.handle}))

  def testHandleEval(self):
    with self.test_session() as sess:
      # Return a handle.
      a = tf.constant(10)
      b = tf.constant(5)
      c = tf.mul(a, b)
      h = tf.get_session_handle(c)
      h = sess.run(h)

      # Get the tensor from its handle.
      self.assertEqual(50, h.eval())

  def testHandleAndValue(self):
    with self.test_session() as sess:
      # Return a handle and a value.
      a = tf.constant(10)
      b = tf.constant(5)
      c = tf.mul(a, b)
      h = tf.get_session_handle(c)
      v = tf.mul(a, c)
      h, v = sess.run([h, v])

      self.assertEqual(50, h.eval())
      self.assertEqual(500, v)

  def testHandleCond(self):
    with self.test_session() as sess:
      # Return a handle and a value
      a = tf.constant(10)
      b = tf.constant(5)
      p = tf.less(a, b)
      c = tf.mul(a, b)
      h = tf.get_session_handle(c)
      p, h = sess.run([p, h])

      # Run by feeding a tensor handle.
      f, x = tf.get_session_tensor(tf.int32)
      if p:
        y = tf.mul(x, 10)
      else:
        y = tf.mul(x, 100)
      result = sess.run(y, feed_dict={f: h.handle})

      self.assertEqual(5000, result)

  def testHandleForLoop(self):
    with self.test_session() as sess:
      # Initialize a handle.
      a = tf.constant(0)
      h = tf.get_session_handle(a)
      h = sess.run(h)

      # Do some computation.
      f, x = tf.get_session_tensor(tf.int32)
      # Must define the loop body outside the loop.
      h_x = tf.get_session_handle(tf.add(x, 1))
      for _ in range(100):
        # This exercises garbage collection.
        h = sess.run(h_x, feed_dict={f: h.handle})

      self.assertEqual(100, h.eval())

  def testHandleWhileLoop(self):
    with self.test_session() as sess:
      # Initialize a handle.
      a = tf.constant(0)
      h = tf.get_session_handle(a)
      h = sess.run(h)

      # Do some computation.
      f, x = tf.get_session_tensor(tf.int32)
      b = tf.constant(100)
      p = tf.less(x, b)
      # Must define the loop body outside the loop.
      h_x = tf.get_session_handle(tf.add(x, 1))
      while True:
        rp, h = sess.run([p, h_x], feed_dict={f: h.handle})
        if not rp:
          break

      self.assertEqual(101, h.eval())

  def testHandleMover(self):
    with self.test_session() as sess:
      # Return a handle.
      a = tf.constant(10)
      b = tf.constant(5)
      c = tf.mul(a, b)
      h = tf.get_session_handle(c)
      h = sess.run(h)

      # Feed a tensor handle.
      f, x = tf.get_session_tensor(tf.int32)
      y = tf.mul(x, 10)
      self.assertEqual(500, sess.run(y, feed_dict={f: h.handle}))

      # Feed another tensor handle.
      with tf.device("/gpu:0"):
        a = tf.constant(10)
        h = tf.get_session_handle(a)
        h = sess.run(h)
        self.assertEqual(100, sess.run(y, feed_dict={f: h.handle}))

  def testHandleDeleter(self):
    with self.test_session() as sess:
      # Return a handle.
      a = tf.constant(10)
      b = tf.constant(5)
      c = tf.mul(a, b)
      h = tf.get_session_handle(c)
      h = sess.run(h)

      # Delete using a raw tensor handle.
      h = h.get_raw_handle()
      f, x = tf.delete_session_tensor()
      sess.run(x, feed_dict={f: h})

if __name__ == "__main__":
  tf.test.main()
