wehub-resource-sync
69 lines
2.0 KiB
Python
69 lines
2.0 KiB
Python
# Copyright (c) 2020 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 unittest
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import numpy as np
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import paddle
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from paddle import base, nn
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class LeNetDygraph(paddle.nn.Layer):
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def __init__(self):
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super().__init__()
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self.features = nn.Sequential(
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nn.Conv2D(1, 6, 3, stride=1, padding=1),
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nn.ReLU(),
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paddle.nn.MaxPool2D(2, 2),
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nn.Conv2D(6, 16, 5, stride=1, padding=0),
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nn.ReLU(),
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paddle.nn.MaxPool2D(2, 2),
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)
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def forward(self, inputs):
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x = self.features(inputs)
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return x
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class TestLayerChildren(unittest.TestCase):
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def func_apply_init_weight(self):
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with base.dygraph.guard():
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net = LeNetDygraph()
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net.eval()
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net_layers = nn.Sequential(*list(net.children()))
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net_layers.eval()
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x = paddle.rand([2, 1, 28, 28])
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y1 = net(x)
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y2 = net_layers(x)
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np.testing.assert_allclose(y1.numpy(), y2.numpy())
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return y1, y2
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def test_func_apply_init_weight(self):
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paddle.seed(102)
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self.new_y1, self.new_y2 = self.func_apply_init_weight()
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paddle.seed(102)
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self.ori_y1, self.ori_y2 = self.func_apply_init_weight()
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# compare ori dygraph and new egr
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np.testing.assert_array_equal(self.ori_y1.numpy(), self.new_y1.numpy())
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np.testing.assert_array_equal(self.ori_y2.numpy(), self.new_y2.numpy())
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if __name__ == '__main__':
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unittest.main()
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