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43 lines
1.3 KiB
43 lines
1.3 KiB
7 years ago
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# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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7 years ago
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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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7 years ago
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#
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7 years ago
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# http://www.apache.org/licenses/LICENSE-2.0
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7 years ago
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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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from op_test import OpTest
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class TestHingeLossOp(OpTest):
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def setUp(self):
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self.op_type = 'hinge_loss'
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samples_num = 64
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logits = np.random.uniform(-10, 10, (samples_num, 1)).astype('float32')
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labels = np.random.randint(0, 2, (samples_num, 1)).astype('float32')
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self.inputs = {
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'Logits': logits,
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'Labels': labels,
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}
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loss = np.maximum(1.0 - (2 * labels - 1) * logits, 0)
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self.outputs = {'Loss': loss}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(['Logits'], 'Loss', max_relative_error=0.008)
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if __name__ == '__main__':
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unittest.main()
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