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import os, sys | |
from libs import * | |
from .layers import * | |
class LightSEModule(nn.Module): | |
def __init__(self, | |
in_channels, | |
reduction = 16, | |
): | |
super(LightSEModule, self).__init__() | |
self.pool = nn.AdaptiveAvgPool1d(1) | |
self.s_conv = DSConv1d( | |
in_channels, in_channels//reduction, | |
kernel_size = 1, | |
) | |
self.act_fn = nn.ReLU() | |
self.e_conv = DSConv1d( | |
in_channels//reduction, in_channels, | |
kernel_size = 1, | |
) | |
def forward(self, | |
input, | |
): | |
attention_scores = self.pool(input) | |
attention_scores = self.s_conv(attention_scores) | |
attention_scores = self.act_fn(attention_scores) | |
attention_scores = self.e_conv(attention_scores) | |
return input*torch.sigmoid(attention_scores) |