iwgan.py 文件源码

def __init__(self, n_hidden, activate='sigmoid', size=64, ch=512, wscale=0.02):
        assert (size % 8 == 0)
        initial_size = size // 8
        self.n_hidden = n_hidden
        if activate == 'sigmoid':
            self.activate = F.sigmoid
        elif activate == 'tanh':
            self.activate = F.tanh
        else:
            raise ValueError('invalid activate function')
        self.ch = ch
        self.initial_size = initial_size
        w = chainer.initializers.Normal(wscale)
        super(Generator, self).__init__(
            l0=L.Linear(self.n_hidden, initial_size * initial_size * ch, initialW=w),
            dc1=L.Deconvolution2D(ch // 1, ch // 2, 4, 2, 1, initialW=w),
            dc2=L.Deconvolution2D(ch // 2, ch // 4, 4, 2, 1, initialW=w),
            dc3=L.Deconvolution2D(ch // 4, ch // 8, 4, 2, 1, initialW=w),
            dc4=L.Deconvolution2D(ch // 8, 3, 3, 1, 1, initialW=w),
        )