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79 lines
2.5 KiB
79 lines
2.5 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 TestFTRLOp(OpTest):
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def setUp(self):
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self.op_type = "ftrl"
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w = np.random.random((102, 105)).astype("float32")
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g = np.random.random((102, 105)).astype("float32")
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sq_accum = np.full((102, 105), 0.1).astype("float32")
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linear_accum = np.full((102, 105), 0.1).astype("float32")
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lr = np.array([0.01]).astype("float32")
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l1 = 0.1
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l2 = 0.2
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lr_power = -0.5
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self.inputs = {
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'Param': w,
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'SquaredAccumulator': sq_accum,
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'LinearAccumulator': linear_accum,
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'Grad': g,
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'LearningRate': lr
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}
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self.attrs = {
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'l1': l1,
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'l2': l2,
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'lr_power': lr_power,
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'learning_rate': lr
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}
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new_accum = sq_accum + g * g
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if lr_power == -0.5:
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linear_out = linear_accum + g - (
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(np.sqrt(new_accum) - np.sqrt(sq_accum)) / lr) * w
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else:
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linear_out = linear_accum + g - ((np.power(
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new_accum, -lr_power) - np.power(sq_accum, -lr_power)) / lr) * w
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x = (l1 * np.sign(linear_out) - linear_out)
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if lr_power == -0.5:
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y = (np.sqrt(new_accum) / lr) + (2 * l2)
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pre_shrink = x / y
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param_out = np.where(np.abs(linear_out) > l1, pre_shrink, 0.0)
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else:
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y = (np.power(new_accum, -lr_power) / lr) + (2 * l2)
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pre_shrink = x / y
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param_out = np.where(np.abs(linear_out) > l1, pre_shrink, 0.0)
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sq_accum_out = sq_accum + g * g
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self.outputs = {
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'ParamOut': param_out,
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'SquaredAccumOut': sq_accum_out,
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'LinearAccumOut': linear_out
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}
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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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