62 lines
1.7 KiB
Python
62 lines
1.7 KiB
Python
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import threading
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import time
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import unittest
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import numpy as np
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import paddle
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from paddle import nn
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class SimpleNet(nn.Layer):
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def __init__(self, in_dim, out_dim):
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super().__init__()
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self.fc = nn.Linear(in_dim, out_dim)
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def forward(self, x):
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return self.fc(x)
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class TestCases(unittest.TestCase):
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@paddle.no_grad()
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def thread_1_main(self):
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time.sleep(8)
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def thread_2_main(self):
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in_dim = 10
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out_dim = 3
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net = SimpleNet(in_dim, out_dim)
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for _ in range(1000):
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x = paddle.to_tensor(np.random.rand(32, in_dim).astype('float32'))
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self.assertTrue(x.stop_gradient)
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x = net(x)
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self.assertFalse(x.stop_gradient)
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def test_main(self):
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threads = []
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for _ in range(10):
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threads.append(threading.Thread(target=self.thread_1_main))
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threads.append(threading.Thread(target=self.thread_2_main))
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for t in threads:
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t.start()
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for t in threads:
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t.join()
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if __name__ == "__main__":
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unittest.main()
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