def __init__(self, channel, reduction=16):
super(CALayer, self).__init__()
self.avg_pool = nn.AdaptiveAvgPool2d(1)
self.c1 = ops.BasicBlock(channel , channel // reduction, 1, 1, 0)
self.c2 = ops.BasicBlockSig(channel // reduction, channel , 1, 1, 0)
def __init__(self, channel, reduction=16):
super(CALayer, self).__init__()
self.avg_pool = nn.AdaptiveAvgPool2d(1)
self.c1 = ops.BasicBlock(channel , channel // reduction, 3, 1, 3, 3)
self.c2 = ops.BasicBlock(channel , channel // reduction, 3, 1, 5, 5)
self.c3 = ops.BasicBlock(channel , channel // reduction, 3, 1, 7, 7)
self.c4 = ops.BasicBlockSig((channel // reduction)*3, channel , 3, 1, 1)
def __init__(self, channel, reduction=16):
super(CALayer, self).__init__()
# global pooling
self.avg_pool = nn.AdaptiveAvgPool2d(1)
# laplacian attention
self.c1 = ops.BasicBlock(channel, channel // reduction, 3, 1, 3, 3)
self.c2 = ops.BasicBlock(channel, channel // reduction, 3, 1, 5, 5)
self.c3 = ops.BasicBlock(channel, channel // reduction, 3, 1, 7, 7)
self.c4 = ops.BasicBlockSig((channel // reduction) * 3, channel, 3, 1,
1) # sigmoid