# Copyright (c) 2018 PaddlePaddle 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. from __future__ import print_function import unittest import numpy as np from op_test import OpTest import paddle import paddle.static as static paddle.enable_static() class TestSeedOpFixSeed(OpTest): def setUp(self): self.op_type = "seed" self.inputs = {} self.attrs = {"seed": 123} self.outputs = {"Out": np.asarray((123)).astype('int')} def test_check_output(self): self.check_output() class TestSeedOpDiffSeed(OpTest): def setUp(self): self.op_type = "seed" self.inputs = {} self.attrs = {"seed": 0} self.outputs = {"Out": np.asarray((123)).astype('int')} def test_check_output(self): self.check_output(no_check_set=["Out"]) class TestDropoutWithRandomSeedGenerator(unittest.TestCase): def setUp(self): paddle.framework.random.set_random_seed_generator('seed0', 123) paddle.framework.random.set_random_seed_generator('seed1', 123) self.rng0 = paddle.framework.random.get_random_seed_generator('seed0') self.rng1 = paddle.framework.random.get_random_seed_generator('seed1') self.places = [paddle.CPUPlace()] if paddle.is_compiled_with_cuda(): self.places.append(paddle.CUDAPlace(0)) def check_static_result(self, place): import paddle.distributed.fleet.meta_parallel.parallel_layers.random as random with static.program_guard(static.Program(), static.Program()): res1 = random.determinate_seed('seed0') exe = static.Executor(place) res_list = [res1] for i in range(2): out1, = exe.run(static.default_main_program(), fetch_list=res_list) self.assertEqual(out1, np.cast['int32'](self.rng1.random())) def test_static(self): for place in self.places: self.check_static_result(place=place) if __name__ == '__main__': unittest.main()