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# 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.python.framework.random_seed."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.framework import random_seed
from tensorflow.python.platform import test
class RandomSeedTest(test.TestCase):
def testRandomSeed(self):
test_cases = [
# Each test case is a tuple with input to get_seed:
# (input_graph_seed, input_op_seed)
# and output from get_seed:
# (output_graph_seed, output_op_seed)
((None, None), (None, None)),
((None, 1), (random_seed.DEFAULT_GRAPH_SEED, 1)),
((1, None), (1, 0)), # 0 will be the default_graph._lastid.
((1, 1), (1, 1)),
((0, 0), (0, 2**31 - 1)), # Avoid nondeterministic (0, 0) output
((2**31 - 1, 0), (0, 2**31 - 1)), # Don't wrap to (0, 0) either
((0, 2**31 - 1), (0, 2**31 - 1)), # Wrapping for the other argument
]
for tc in test_cases:
tinput, toutput = tc[0], tc[1]
random_seed.set_random_seed(tinput[0])
g_seed, op_seed = random_seed.get_seed(tinput[1])
msg = 'test_case = {0}, got {1}, want {2}'.format(tinput,
(g_seed, op_seed),
toutput)
self.assertEqual((g_seed, op_seed), toutput, msg=msg)
random_seed.set_random_seed(None)
if __name__ == '__main__':
test.main()
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