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Update PSA.py #84

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49 changes: 29 additions & 20 deletions model/attention/PSA.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,28 +4,38 @@
from torch.nn import init



class PSA(nn.Module):

def __init__(self, channel=512,reduction=4,S=4):
def __init__(self, channel=512, reduction=4, S=4):
super().__init__()
self.S=S
self.S = S

self.convs=[]
for i in range(S):
self.convs.append(nn.Conv2d(channel//S,channel//S,kernel_size=2*(i+1)+1,padding=i+1))
self.convs = nn.ModuleList(
[nn.Conv2d(channel // S, channel // S, kernel_size=2 * (i + 1) + 1, padding=(i + 1)) for i in range(S)])
# self.convs=[]
# for i in range(S):
# self.convs.append(nn.Conv2d(channel//S,channel//S,kernel_size=2*(i+1)+1,padding=i+1))

self.se_blocks=[]
for i in range(S):
self.se_blocks.append(nn.Sequential(
self.se_blocks = nn.ModuleList(
nn.Sequential(
nn.AdaptiveAvgPool2d(1),
nn.Conv2d(channel//S, channel // (S*reduction),kernel_size=1, bias=False),
nn.Conv2d(channel // S, channel // (S * reduction), kernel_size=1, bias=False),
nn.ReLU(inplace=True),
nn.Conv2d(channel // (S*reduction), channel//S,kernel_size=1, bias=False),
nn.Conv2d(channel // (S * reduction), channel // S, kernel_size=1, bias=False),
nn.Sigmoid()
))

self.softmax=nn.Softmax(dim=1)
) for i in range(S)
)
# self.se_blocks=[]
# for i in range(S):
# self.se_blocks.append(nn.Sequential(
# nn.AdaptiveAvgPool2d(1),
# nn.Conv2d(channel//S, channel // (S*reduction),kernel_size=1, bias=False),
# nn.ReLU(inplace=True),
# nn.Conv2d(channel // (S*reduction), channel//S,kernel_size=1, bias=False),
# nn.Sigmoid()
# ))

self.softmax = nn.Softmax(dim=1)


def init_weights(self):
Expand Down Expand Up @@ -68,11 +78,10 @@ def forward(self, x):


if __name__ == '__main__':
input=torch.randn(50,512,7,7)
psa = PSA(channel=512,reduction=8)
output=psa(input)
a=output.view(-1).sum()
device = torch.device('cuda')
input = torch.randn(8, 512, 7, 7).to(device)
psa = PSA(channel=512, reduction=8).to(device)
output = psa(input)
a = output.view(-1).sum()
a.backward()
print(output.shape)