Allow coercion of Julia types to NumPy dtypes

**Is your feature request related to a problem? Please describe.** We're using Julia types as dtypes, but a third-party library does `np.dtype(jl_type)`. Maybe there's a way to support this as an upstream feature for everyone. **Describe the solution you'd like** Ideally, I'd like something like an implementation of the [`__numpy_dtype__`](https://numpy.org/doc/stable/user/basics.interoperability.html#dtype-interoperability) protocol or supported Julia types. This could even be implemented on [some kinds of structs](https://numpy.org/doc/stable/glossary.html#term-structured-data-type). **Describe alternatives you've considered** Maybe we could solve this upstream by converting back and forth, but a simple conversion is always helpful. **Additional context** Originally reported by @ilan-gold and @amalia-k510 in https://github.com/pydata/sparse/issues/915