models.py 文件源码

def __init__(self, in_ch=3, out_len=128, base_size=128, down_layers=4, use_bn=True, w_init=None):
        layers = {}

        self.down_layers = down_layers
        if use_bn:
            norm = 'bn'
        else:
            norm = None

        act = F.relu
        #if w_init is None:
        #    w_init = chainer.initializers.Normal(0.02)

        layers['c_first'] = NNBlock(in_ch, base_size, nn='down_conv', norm=None, activation=act,  w_init=w_init)
        base = base_size

        for i in range(down_layers-1):
            layers['c'+str(i)] = NNBlock(base, base*2, nn='down_conv', norm=norm, activation=act,  w_init=w_init)
            base*=2

        layers['c_last'] = NNBlock(None, out_len, nn='linear', norm=None, activation=None, w_init=w_init)

        super(DCGANEncoder, self).__init__(**layers)