53 lines
1.7 KiB
53 lines
1.7 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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from __future__ import print_function
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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 TestProximalAdagradOp(OpTest):
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def setUp(self):
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self.op_type = "proximal_adagrad"
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w = np.random.random((102, 105)).astype("float32")
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m = np.random.random((102, 105)).astype("float32")
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g = np.random.random((102, 105)).astype("float32")
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lr = np.array([0.1]).astype("float32")
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l1 = 0.1
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l2 = 0.2
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self.inputs = {'Param': w, 'Grad': g, 'Moment': m, 'LearningRate': lr}
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self.attrs = {'l1': l1, 'l2': l2}
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param_out = 0.0
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moment_out = m + g * g
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prox_param = w - lr * g / np.sqrt(moment_out)
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if l1 > 0.0:
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x = np.abs(prox_param) - lr * l1
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x[x < 0] = 0
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param_out = np.sign(prox_param) * (x / (1.0 + lr * l2))
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else:
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param_out = prox_param / (1.0 + lr * l2)
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self.outputs = {'ParamOut': param_out, 'MomentOut': moment_out}
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def test_check_output(self):
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self.check_output()
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if __name__ == "__main__":
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unittest.main()
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