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100 lines
2.8 KiB
100 lines
2.8 KiB
# Copyright (c) 2018 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.fluid.core as core
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from op_test import OpTest
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from scipy.special import expit
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from test_activation_op import TestRelu, TestTanh, TestSqrt, TestAbs
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class TestMKLDNNReluDim2(TestRelu):
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def setUp(self):
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super(TestMKLDNNReluDim2, self).setUp()
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self.attrs = {"use_mkldnn": True}
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class TestMKLDNNTanhDim2(TestTanh):
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def setUp(self):
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super(TestMKLDNNTanhDim2, self).setUp()
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self.attrs = {"use_mkldnn": True}
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class TestMKLDNNSqrtDim2(TestSqrt):
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def setUp(self):
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super(TestMKLDNNSqrtDim2, self).setUp()
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self.attrs = {"use_mkldnn": True}
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class TestMKLDNNAbsDim2(TestAbs):
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def setUp(self):
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super(TestMKLDNNAbsDim2, self).setUp()
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self.attrs = {"use_mkldnn": True}
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class TestMKLDNNReluDim4(TestRelu):
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def setUp(self):
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super(TestMKLDNNReluDim4, self).setUp()
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x = np.random.uniform(-1, 1, [2, 4, 3, 5]).astype("float32")
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# The same reason with TestAbs
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x[np.abs(x) < 0.005] = 0.02
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out = np.maximum(x, 0)
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self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(x)}
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self.outputs = {'Out': out}
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self.attrs = {"use_mkldnn": True}
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class TestMKLDNNTanhDim4(TestTanh):
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def setUp(self):
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super(TestMKLDNNTanhDim4, self).setUp()
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self.inputs = {
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'X': np.random.uniform(0.1, 1, [2, 4, 3, 5]).astype("float32")
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}
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self.outputs = {'Out': np.tanh(self.inputs['X'])}
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self.attrs = {"use_mkldnn": True}
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class TestMKLDNNSqrtDim4(TestSqrt):
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def setUp(self):
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super(TestMKLDNNSqrtDim4, self).setUp()
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self.inputs = {
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'X': np.random.uniform(0.1, 1, [2, 4, 3, 5]).astype("float32")
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}
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self.outputs = {'Out': np.sqrt(self.inputs['X'])}
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self.attrs = {"use_mkldnn": True}
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class TestMKLDNNAbsDim4(TestAbs):
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def setUp(self):
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super(TestMKLDNNAbsDim4, self).setUp()
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x = np.random.uniform(-1, 1, [2, 4, 3, 5]).astype("float32")
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# The same reason with TestAbs
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x[np.abs(x) < 0.005] = 0.02
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self.inputs = {'X': x}
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self.outputs = {'Out': np.abs(self.inputs['X'])}
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self.attrs = {"use_mkldnn": True}
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if __name__ == '__main__':
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unittest.main()
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