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91 lines
2.7 KiB
91 lines
2.7 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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import unittest
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import numpy as np
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from op_test import OpTest
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class TestMomentumOp1(OpTest):
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def setUp(self):
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self.op_type = "momentum"
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param = np.random.random((123, 321)).astype("float32")
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grad = np.random.random((123, 321)).astype("float32")
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velocity = np.zeros((123, 321)).astype("float32")
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learning_rate = np.array([0.001]).astype("float32")
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mu = 0.0001
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use_nesterov = False
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self.inputs = {
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'Param': param,
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'Grad': grad,
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'Velocity': velocity,
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'LearningRate': learning_rate
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}
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self.attrs = {'mu': mu}
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velocity_out = mu * velocity + grad
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if use_nesterov:
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param_out = param - grad * learning_rate + \
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velocity_out * mu * learning_rate
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else:
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param_out = param - learning_rate * velocity_out
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self.outputs = {'ParamOut': param_out, 'VelocityOut': velocity_out}
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def test_check_output(self):
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self.check_output()
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class TestMomentumOp2(OpTest):
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'''Test Momentum with default values for attributes
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'''
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def setUp(self):
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self.op_type = "momentum"
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param = np.random.random((123, 321)).astype("float32")
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grad = np.random.random((123, 321)).astype("float32")
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velocity = np.zeros((123, 321)).astype("float32")
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learning_rate = np.array([0.001]).astype("float32")
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mu = 0.0001
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use_nesterov = True
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self.inputs = {
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'Param': param,
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'Grad': grad,
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'Velocity': velocity,
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'LearningRate': learning_rate
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}
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self.attrs = {'mu': mu, 'use_nesterov': use_nesterov}
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velocity_out = mu * velocity + grad
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if use_nesterov:
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param_out = param - grad * learning_rate + \
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velocity_out * mu * learning_rate
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else:
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param_out = param - learning_rate * velocity_out
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self.outputs = {'ParamOut': param_out, 'VelocityOut': velocity_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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