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Paddle/python/paddle/fluid/tests/unittests/test_huber_loss_op.py

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# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# 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.
import unittest
import numpy as np
from op_test import OpTest
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)
class TestHuberLossOp(OpTest):
def setUp(self):
self.op_type = 'huber_loss'
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']
loss = np.vectorize(huber_loss_forward)(residual,
delta).astype('float32')
self.attrs = {'delta': delta}
self.outputs = {
'Residual': residual,
'Out': loss.reshape((samples_num, 1))
}
def test_check_output(self):
self.check_output()
def test_check_grad_normal(self):
self.check_grad(['X', 'Y'], 'Out', max_relative_error=0.008)
def test_check_grad_ingore_x(self):
self.check_grad(
['Y'], 'Out', max_relative_error=0.008, no_grad_set=set("residual"))
def test_check_grad_ingore_y(self):
self.check_grad(
['X'], 'Out', max_relative_error=0.008, no_grad_set=set('residual'))
if __name__ == '__main__':
unittest.main()