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CaoGang2018 2020-05-31 10:27:29 +08:00
parent b38eccc3b2
commit db37310f79
1 changed files with 28 additions and 5 deletions
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util/model.py
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@ -6,16 +6,39 @@ import torch.nn.functional as F
class pool_model(nn.Module): class pool_model(nn.Module):
def __init__(self): def __init__(self):
super(pool_model, self).__init__() super(pool_model, self).__init__()
self.pool1 = nn.AdaptiveAvgPool2d(1) # self.pool1 = nn.AdaptiveAvgPool2d(1)
self.pool2 = nn.AdaptiveMaxPool2d(1) self.pool2 = nn.AdaptiveMaxPool2d(1)
def forward(self, x): def ave_pool(self, x, cc):
tmp1 = self.pool1(x) b, c, h, w = x.shape
men_pool = t.zeros(b, c)
for i in range(b):
count = 0
tmp = x[i,:, 0, 0]
# exit()
# print(tmp.shape)
for m in range(h):
for n in range(w):
if cc[i][m][n]:
tmp += x[i,:, m, n]
count += 1
if count == 0:
men_pool[i] = tmp
else:
men_pool[i] = tmp / count
# print(count)
return men_pool
def forward(self, x, cc):
tmp1 = self.ave_pool(x, cc)
tmp2 = self.pool2(x) tmp2 = self.pool2(x)
b, c, _, _ = tmp1.shape b, c, _, _ = tmp2.shape
# print(tmp1.shape) # print(tmp1.shape)
# print(tmp2.shape)
return t.cat((tmp1, tmp2), dim=1).reshape(b, -1) return t.cat((tmp1, tmp2.reshape(b, c)), dim=1).reshape(b, -1)
# x = t.ones(2, 512, 7, 7) # x = t.ones(2, 512, 7, 7)
# model = pool_model() # model = pool_model()