vgg16.py 文件源码

def __call__(self, x, t=None):
        h = x
        h = F.relu(self.conv1_1(h))
        h = F.relu(self.conv1_2(h))
        h = F.max_pooling_2d(h, 2, stride=2)

        h = F.relu(self.conv2_1(h))
        h = F.relu(self.conv2_2(h))
        h = F.max_pooling_2d(h, 2, stride=2)

        h = F.relu(self.conv3_1(h))
        h = F.relu(self.conv3_2(h))
        h = F.relu(self.conv3_3(h))
        h = F.max_pooling_2d(h, 2, stride=2)

        h = F.relu(self.conv4_1(h))
        h = F.relu(self.conv4_2(h))
        h = F.relu(self.conv4_3(h))
        h = F.max_pooling_2d(h, 2, stride=2)

        h = F.relu(self.conv5_1(h))
        h = F.relu(self.conv5_2(h))
        h = F.relu(self.conv5_3(h))
        h = F.max_pooling_2d(h, 2, stride=2)

        h = F.dropout(F.relu(self.fc6(h)), ratio=.5)
        h = F.dropout(F.relu(self.fc7(h)), ratio=.5)
        h = self.fc8(h)
        fc8 = h

        self.score = fc8

        if t is None:
            assert not chainer.config.train
            return

        self.loss = F.softmax_cross_entropy(fc8, t)
        self.accuracy = F.accuracy(self.score, t)
        return self.loss