# -*- coding: utf-8 -*- 

# Copyright 2020 Huawei Technologies Co., Ltd

#

# 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 torch import nn





class SELayer(nn.Module):

    def __init__(self, channel, reduction=16):

        super(SELayer, self).__init__()

        self.avg_pool = nn.AdaptiveAvgPool2d(1)

        self.fc = nn.Sequential(

            nn.Linear(channel, channel // reduction, bias=False),

            nn.ReLU(inplace=True),

            nn.Linear(channel // reduction, channel, bias=False),

            nn.Sigmoid()

        )



    def forward(self, x):

        b, c, h, w = x.size()

        y = self.avg_pool(x).view(b, c)

        y = self.fc(y).view(b, c, 1, 1)

        return x * y.repeat(1,1,h,w)