net.py 文件源码

def __init__(self, in_ch):
        layers = {}
        w = chainer.initializers.Normal(0.02)
        layers['c0'] = L.Convolution2D(in_ch, 64, 3, 1, 1, initialW=w)
        layers['c1'] = CBR(64, 128, bn=True, sample='down', activation=F.leaky_relu, dropout=False)
        layers['c2'] = CBR(128, 256, bn=True, sample='down', activation=F.leaky_relu, dropout=False)
        layers['c3'] = CBR(256, 512, bn=True, sample='down', activation=F.leaky_relu, dropout=False)
        layers['c4'] = CBR(512, 512, bn=True, sample='down', activation=F.leaky_relu, dropout=False)
        layers['c5'] = CBR(512, 512, bn=True, sample='down', activation=F.leaky_relu, dropout=False)
        layers['c6'] = CBR(512, 512, bn=True, sample='down', activation=F.leaky_relu, dropout=False)
        layers['c7'] = CBR(512, 512, bn=True, sample='down', activation=F.leaky_relu, dropout=False)
        super(Encoder, self).__init__(**layers)