def __init__(self, in_channels, reduction=4): super().__init__() channels = in_channels // reduction self.layers = nn.Sequential( nn.AdaptiveAvgPool2d(1), Conv2d(in_channels, channels, kernel_size=1, norm_layer='bn', activation='relu6'), Conv2d(channels, in_channels, kernel_size=1, bias=False), HardSigmoid(True), )
def __init__(self, in_channels, channels): super().__init__() self.pool = nn.AdaptiveAvgPool2d(1) self.layers = nn.Sequential( nn.Linear(in_channels, channels), nn.ReLU6(True), nn.Linear(channels, in_channels), HardSigmoid(inplace=True), )
def __init__(self, in_channels, reduction=4): super().__init__() channels = in_channels // reduction self.avgpool = nn.AdaptiveAvgPool2d(1) self.layers = nn.Sequential( nn.Linear(in_channels, channels), nn.ReLU6(True), nn.Linear(channels, in_channels), HardSigmoid(True), )