googlenet_v3.py 文件源码

def __call__(self, x, train=True):
        h = self.conv1(x, train)
        h = self.conv2(h, train)
        h = self.conv3(h, train)
        h = F.max_pooling_2d(h, ksize=(3, 3), stride=(2, 2), pad=(1, 1))
        h = self.conv4(h, train)
        h = self.conv5(h, train)
        h = self.conv6(h, train)
        h = self.inception_f5_1(h, train)
        h = self.inception_f5_2(h, train)
        h = self.inception_f5_3(h, train)
        h = self.inception_f6_1(h, train)
        h = self.inception_f6_2(h, train)
        h = self.inception_f6_3(h, train)
        h = self.inception_f6_4(h, train)
        h = self.inception_f6_5(h, train)
        h = self.inception_f7_1(h, train)
        h = self.inception_f7_2(h, train)
        num, categories, y, x = h.data.shape
        # global average pooling
        h = F.reshape(F.average_pooling_2d(h, (y, x)), (num, categories))
        h = F.dropout(h, ratio=0.2, train=train)
        h = self.linear(h)
        return h