Consider adding a "TopLevel" keyword that stands in for the top level bound of a corresponding type variable

Summary

Please consider a new typing keyword that stands in for the top level type of a corresponding type variable.

Motivation

Consider a test here and the corresponding definition of DistributionInfo here. The test loses all typing information because I used DistributionInfo[Any, Any, Any]. So if I want typing information, I have to use:

def test_flatten(generator: Generator,
                 distribution_info: DistributionInfo[NaturalParametrization[ExpectationParmetrization, JaxComplexArray],
                                                     ExpectationParametrization[NaturalParmetrization],
                                                     NumpyComplexArray]) -> None:

I would much rather just do

def test_flatten(generator: Generator,
                 distribution_info: DistributionInfo[TopLevel, TopLevel, TopLevel]) -> None:

It's not just shorter, but it reduces churn if the type definitions change. Note that TopLevel is recursive (it chooses the top level of the nested types too).

Inizia con i tests collegati tests/test_flatten.py e tests/distribution_info.py per capire quali informazioni di tipizzazione vanno perse quando viene usato DistributionInfo[Any, Any, Any]. Chiarisci la semantica ricorsiva prevista di TopLevel e in cosa differisce dal comportamento esistente delle variabili di tipo. Il lavoro è completato quando la proposta contiene una specifica precisa e un percorso di validazione concordato.