test_huber_loss_op.py 2.0 KB
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#   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");
# you may not use this file except in compliance with the License.
# 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
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

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import unittest
import numpy as np
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from op_test import OpTest
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def huber_loss_forward(val, delta):
    abs_val = abs(val)
    if abs_val <= delta:
        return 0.5 * val * val
    else:
        return delta * (abs_val - 0.5 * delta)


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class TestHuberLossOp(OpTest):
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    def setUp(self):
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        self.op_type = 'huber_loss'
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        samples_num = 64
        delta = 1.0
        self.inputs = {
            'X': np.random.uniform(0, 1., (samples_num, 1)).astype('float32'),
            'Y': np.random.uniform(0, 1., (samples_num, 1)).astype('float32'),
        }
        residual = self.inputs['Y'] - self.inputs['X']
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        loss = np.vectorize(huber_loss_forward)(residual,
                                                delta).astype('float32')
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        self.attrs = {'delta': delta}
        self.outputs = {
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            'Residual': residual,
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            'Out': loss.reshape((samples_num, 1))
        }

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    def test_check_output(self):
        self.check_output()
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    def test_check_grad_normal(self):
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        self.check_grad(['X', 'Y'], 'Out', max_relative_error=0.008)
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    def test_check_grad_ingore_x(self):
        self.check_grad(
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            ['Y'], 'Out', max_relative_error=0.008, no_grad_set=set("residual"))
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    def test_check_grad_ingore_y(self):
        self.check_grad(
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            ['X'], 'Out', max_relative_error=0.008, no_grad_set=set('residual'))
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if __name__ == '__main__':
    unittest.main()