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

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2.3 KiB

# 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.
from __future__ import division
import unittest
import numpy as np
from op_test import OpTest
def kldiv_loss(x, target, reduction):
output = target * (np.log(target) - x)
loss = np.where(target >= 0, output, np.zeros_like(x))
if reduction == "batchmean":
return loss.sum() / x.shape[0]
if reduction == "mean":
return loss.mean()
if reduction == "sum":
return loss.sum()
return loss
class TestKLDivLossOp(OpTest):
def setUp(self):
self.initTestCase()
self.op_type = 'kldiv_loss'
x = np.random.uniform(-10, 10, self.x_shape).astype('float32')
target = np.random.uniform(-10, 10, self.x_shape).astype('float32')
self.attrs = {"reduction": self.reduction}
self.inputs = {
'X': x,
'Target': target,
}
loss = kldiv_loss(x, target, self.reduction)
self.outputs = {'Loss': loss.astype('float32')}
def test_check_output(self):
self.check_output()
def test_check_grad(self):
self.check_grad(
['X'], 'Loss', no_grad_set=set(["Target"]), max_relative_error=0.06)
def initTestCase(self):
self.x_shape = (2, 5, 5)
self.reduction = 'batchmean'
class TestKLDivLossOp2(TestKLDivLossOp):
def initTestCase(self):
self.x_shape = (3, 2, 7, 7)
self.reduction = 'none'
class TestKLDivLossOp3(TestKLDivLossOp):
def initTestCase(self):
self.x_shape = (2, 3, 5, 7, 9)
self.reduction = 'mean'
class TestKLDivLossOp4(TestKLDivLossOp):
def initTestCase(self):
self.x_shape = (5, 7)
self.reduction = 'sum'
if __name__ == "__main__":
unittest.main()