[FIXED] How can generator get input noise z?

Issue

Hi I'm looking this GAN implementation code. code here

My question is generator class has no input parameter when defining class Generator(#38 from the link) But when training, generator gets input z(#141 from the link). I looked into the nn.Module class which is parent of class Generator but I can't find input parameter for noise z. Can anyone help?

class Generator(nn.Module):    #38
    def __init__(self):
        super(Generator, self).__init__()

        def block(in_feat, out_feat, normalize=True):
            layers = [nn.Linear(in_feat, out_feat)]
            if normalize:
                layers.append(nn.BatchNorm1d(out_feat, 0.8))
            layers.append(nn.LeakyReLU(0.2, inplace=True))
            return layers

        self.model = nn.Sequential(
            *block(opt.latent_dim, 128, normalize=False),
            *block(128, 256),
            *block(256, 512),
            *block(512, 1024),
            nn.Linear(1024, int(np.prod(img_shape))),
            nn.Tanh()
        )

    def forward(self, z):
        img = self.model(z)
        img = img.view(img.size(0), *img_shape)
        return img

generator = Generator()    #88

gen_imgs = generator(z)    #141

I tried looking for nn.Module, variable() in pytorch docs and still can't get what I wanted.

Solution

Consider every quoted line (38, 88 and 141):

• On line 38 is a definition of class, by putting nn.Module in brackets it's declaring inheritance of class Generator from class nn.Module (which is common way to define your own neural network).
• On line 88 instance of class Generator is created -- for parameters it needs all what's inside brackets of __init__ (line 39), besides self, that's why brackets on line 88 is empty.
• And on line 141 there is a calling of genearator, behavior here defined by method forward (line 58) and there is one parameter to be passed -- z.

Again, line 88 creates an instance, line 141 calls forward method of an instance.

Answered By - draw