CNN.py 文件源码

def __call__(self, xs):

        if self.freeze:
            self.embed.disable_update()
        xs = self.embed(xs)
        batchsize, height, width = xs.shape
        xs = F.reshape(xs, (batchsize, 1, height, width))
        conv3_xs = self.conv3(xs)
        conv4_xs = self.conv4(xs)
        conv5_xs = self.conv5(xs)
        h1 = F.max_pooling_2d(F.relu(conv3_xs), conv3_xs.shape[2])
        h2 = F.max_pooling_2d(F.relu(conv4_xs), conv4_xs.shape[2])
        h3 = F.max_pooling_2d(F.relu(conv5_xs), conv5_xs.shape[2])
        concat_layer = F.concat([h1, h2, h3], axis=1)
        with chainer.using_config('train', True):
            y = self.l1(F.dropout(F.tanh(concat_layer)))
        return y