loss.py

#   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'
]