# custom weights initialization called on ``netG`` and ``netD``
def weights_init(m):
    classname = m.__class__.__name__
    if classname.find('Conv') != -1:
        [nn.init.normal_](https://docs.pytorch.org/docs/stable/nn.init.html#torch.nn.init.normal_ "torch.nn.init.normal_")(m.weight.data, 0.0, 0.02)
    elif classname.find('BatchNorm') != -1:
        [nn.init.normal_](https://docs.pytorch.org/docs/stable/nn.init.html#torch.nn.init.normal_ "torch.nn.init.normal_")(m.weight.data, 1.0, 0.02)
        [nn.init.constant_](https://docs.pytorch.org/docs/stable/nn.init.html#torch.nn.init.constant_ "torch.nn.init.constant_")(m.bias.data, 0)