I have
class VeryUsefullLegacyParent(nn.Module):
  def __init__(self,n):
    self.b = nn.Parameter(torch.zeros(n))

I want to create
class MyChild(VeryUsefullLegacyParent):
  def __init__(self, a: torch.Tensor):
    super(MyChild, self).__init__(len(a))
    self.b = nn.functional.sigmoid(a)

My aim to get a gradient w.r.t a (and deeper). But I can’t replace b in such straighforward way, beacause it already registered as a model parameter. I want to use the same name for this variable,  because I have a lot of functions working with VeryUsefullLegacyParent that access this variable.