def METHOD_NAME(self):
    for m in self.sublayers():
        if isinstance(m, nn.Conv2D):
            n = m._kernel_size[0] * m._kernel_size[1] * m._out_channels
            fill_(m.weight, 1)
        elif isinstance(m, nn.BatchNorm2D):
            fill_(m.weight, 1)
            zero_(m.bias)
    return self.sublayers()