# 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()