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Paddle/python/paddle/nn/functional/loss.py

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# Copyright (c) 2020 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.
# TODO: define loss functions of neural network
from ...fluid.layers import bpr_loss #DEFINE_ALIAS
from ...fluid.layers import center_loss #DEFINE_ALIAS
from ...fluid.layers import cross_entropy #DEFINE_ALIAS
from ...fluid.layers import dice_loss #DEFINE_ALIAS
from ...fluid.layers import iou_similarity #DEFINE_ALIAS
from ...fluid.layers import kldiv_loss #DEFINE_ALIAS
from ...fluid.layers import log_loss #DEFINE_ALIAS
from ...fluid.layers import mse_loss #DEFINE_ALIAS
from ...fluid.layers import npair_loss #DEFINE_ALIAS
from ...fluid.layers import rank_loss #DEFINE_ALIAS
from ...fluid.layers import sigmoid_cross_entropy_with_logits #DEFINE_ALIAS
from ...fluid.layers import sigmoid_focal_loss #DEFINE_ALIAS
from ...fluid.layers import smooth_l1 #DEFINE_ALIAS
from ...fluid.layers import softmax_with_cross_entropy #DEFINE_ALIAS
from ...fluid.layers import square_error_cost #DEFINE_ALIAS
from ...fluid.layers import ssd_loss #DEFINE_ALIAS
from ...fluid.layers import teacher_student_sigmoid_loss #DEFINE_ALIAS
from ...fluid.layers import edit_distance #DEFINE_ALIAS
from ...fluid.layers import huber_loss #DEFINE_ALIAS
from ...fluid.layers import margin_rank_loss #DEFINE_ALIAS
from ...fluid.layers import sampled_softmax_with_cross_entropy #DEFINE_ALIAS
__all__ = [
'bpr_loss',
'center_loss',
'cross_entropy',
'dice_loss',
'edit_distance',
'huber_loss',
'iou_similarity',
'kldiv_loss',
'log_loss',
'margin_rank_loss',
'mse_loss',
# 'nce',
'npair_loss',
'rank_loss',
'sampled_softmax_with_cross_entropy',
'sigmoid_cross_entropy_with_logits',
'sigmoid_focal_loss',
'smooth_l1',
'softmax_with_cross_entropy',
'square_error_cost',
'ssd_loss',
'teacher_student_sigmoid_loss'
]