discriminators.py 文件源码

def __init__(self, in_ch=3, base_size=128, down_layers=4, use_bn=True, w_init=None, output_len=38):
        layers = {}

        self.down_layers = down_layers

        if use_bn:
            norm = 'bn'
        else:
            norm = None

        act = F.leaky_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_0'] = NNBlock(None, 1, nn='linear', norm=None, activation=None, w_init=w_init)
        layers['c_last_1_0'] = NNBlock(None, output_len, nn='linear', norm=None, activation=None, w_init=None)
        #layers['c_last_1_1'] = NNBlock(1024, 1024, nn='linear', norm=None, activation=F.leaky_relu, w_init=None)
        #layers['c_last_1_2'] = NNBlock(1024, output_len, nn='linear', norm=None, activation=None, w_init=None)

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