nin.py 文件源码

def __call__(self, x, t):
        h = F.max_pooling_2d(F.relu(self.mlpconv1(x)), 3, stride=2)
        h = F.max_pooling_2d(F.relu(self.mlpconv2(h)), 3, stride=2)
        h = F.max_pooling_2d(F.relu(self.mlpconv3(h)), 3, stride=2)
        h = self.mlpconv4(F.dropout(h))
        h = F.reshape(F.average_pooling_2d(h, 6), (len(x), 1000))

        loss = F.softmax_cross_entropy(h, t)
        chainer.report({'loss': loss, 'accuracy': F.accuracy(h, t)}, self)
        return loss