"module.parametrizations.weight.original".
Parametrizations may be concatenated by registering several
   parametrizations on the same attribute.
The training mode of a registered parametrization is updated on
   registration to match the training mode of the host module
Parametrized parameters and buffers have an inbuilt caching system
   that can be activated using the context manager "cached()".
A "parametrization" may optionally implement a method with
   signature
  def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]]

This method is called on the unparametrized tensor when the first
   parametrization is registered to compute the initial value of the
   original tensor. If this method is not implemented, the original
   tensor will be just the unparametrized tensor.
If all the parametrizations registered on a tensor implement
   right_inverse it is possible to initialize a parametrized tensor
   by assigning to it, as shown in the example below.