P4CNN_RP.py 文件源码

def __call__(self, x, t, train=True, finetune=False):

        h = self.l1(x, train, finetune)
        # h = F.dropout(h, self.dr, train)
        h = F.max(h, axis=-3, keepdims=False)

        h = self.l2(h, train, finetune)
        h = F.max(h, axis=-3, keepdims=False)

        h = F.max_pooling_2d(h, ksize=2, stride=2, pad=0)

        h = self.l3(h, train, finetune)
        h = F.max(h, axis=-3, keepdims=False)

        # h = F.dropout(h, self.dr, train)
        h = self.l4(h, train, finetune)
        h = F.max(h, axis=-3, keepdims=False)
        # h = F.dropout(h, self.dr, train)
        h = self.l5(h, train, finetune)
        h = F.max(h, axis=-3, keepdims=False)
        # h = F.dropout(h, self.dr, train)
        h = self.l6(h, train, finetune)
        h = F.max(h, axis=-3, keepdims=False)

        h = self.top(h)

        h = F.max(h, axis=-3, keepdims=False)
        h = F.max(h, axis=-1, keepdims=False)
        h = F.max(h, axis=-1, keepdims=False)

        return F.softmax_cross_entropy(h, t), F.accuracy(h, t)