ArtNet.py 文件源码

def __call__(self, x):
        conv1_1 = F.relu(self.vgg.conv1_1(x))
        conv1_2 = F.relu(self.vgg.conv1_2(conv1_1))
        pool1 = F.average_pooling_2d(conv1_2, 2, stride=2)

        conv2_1 = F.relu(self.vgg.conv2_1(pool1))
        conv2_2 = F.relu(self.vgg.conv2_2(conv2_1))
        pool2 = F.average_pooling_2d(conv2_2, 2, stride=2)

        conv3_1 = F.relu(self.vgg.conv3_1(pool2))
        conv3_2 = F.relu(self.vgg.conv3_2(conv3_1))
        conv3_3 = F.relu(self.vgg.conv3_3(conv3_2))
        conv3_4 = F.relu(self.vgg.conv3_4(conv3_3))
        pool3 = F.average_pooling_2d(conv3_4, 2, stride=2)

        conv4_1 = F.relu(self.vgg.conv4_1(pool3))
        conv4_2 = F.relu(self.vgg.conv4_2(conv4_1))
        conv4_3 = F.relu(self.vgg.conv4_3(conv4_2))
        conv4_4 = F.relu(self.vgg.conv4_4(conv4_3))
        pool4 = F.average_pooling_2d(conv4_4, 2, stride=2)

        conv5_1 = F.relu(self.vgg.conv5_1(pool4))

        return tuple([conv1_1, conv2_1, conv3_1, conv4_1, conv5_1, conv4_2])