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# Copyright (c) 2021 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 paddle
import paddle.nn as nn
import paddle.nn.functional as F
from paddleseg.cvlibs import manager
@manager.LOSSES.add_component
class MRSD(nn.Layer):
def __init__(self, eps=1e-6):
super().__init__()
self.eps = eps
def forward(self, logit, label, mask=None):
"""
Forward computation.
Args:
logit (Tensor): Logit tensor, the data type is float32, float64.
label (Tensor): Label tensor, the data type is float32, float64. The shape should equal to logit.
mask (Tensor, optional): The mask where the loss valid. Default: None.
"""
if len(label.shape) == 3:
label = label.unsqueeze(1)
sd = paddle.square(logit - label)
loss = paddle.sqrt(sd + self.eps)
if mask is not None:
mask = mask.astype('float32')
if len(mask.shape) == 3:
mask = mask.unsqueeze(1)
loss = loss * mask
loss = loss.sum() / (mask.sum() + self.eps)
mask.stop_gradient = True
else:
loss = loss.mean()
return loss