model.py 文件源码

def __init__(self, feature_map_nc, output_nc, w_init=None):
        super(Generator, self).__init__(
            c1=L.Convolution2D(None, feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            c2=L.Convolution2D(None, 2*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            c3=L.Convolution2D(None, 4*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            c4=L.Convolution2D(None, 8*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            c5=L.Convolution2D(None, 8*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            c6=L.Convolution2D(None, 8*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            c7=L.Convolution2D(None, 8*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            c8=L.Convolution2D(None, 8*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            dc1=L.Deconvolution2D(None, 8*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            dc2=L.Deconvolution2D(None, 8*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            dc3=L.Deconvolution2D(None, 8*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            dc4=L.Deconvolution2D(None, 8*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            dc5=L.Deconvolution2D(None, 4*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            dc6=L.Deconvolution2D(None, 2*feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            dc7=L.Deconvolution2D(None, feature_map_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            dc8=L.Deconvolution2D(None, output_nc, ksize=4, stride=2, pad=1, initialW=w_init),
            b2=L.BatchNormalization(2*feature_map_nc),
            b3=L.BatchNormalization(4*feature_map_nc),
            b4=L.BatchNormalization(8*feature_map_nc),
            b5=L.BatchNormalization(8*feature_map_nc),
            b6=L.BatchNormalization(8*feature_map_nc),
            b7=L.BatchNormalization(8*feature_map_nc),
            b8=L.BatchNormalization(8*feature_map_nc),
            b1_d=L.BatchNormalization(8*feature_map_nc),
            b2_d=L.BatchNormalization(8*feature_map_nc),
            b3_d=L.BatchNormalization(8*feature_map_nc),
            b4_d=L.BatchNormalization(8*feature_map_nc),
            b5_d=L.BatchNormalization(4*feature_map_nc),
            b6_d=L.BatchNormalization(2*feature_map_nc),
            b7_d=L.BatchNormalization(feature_map_nc)
        )