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),
)