[eudsl-python-extras] support types as GenericAlias for input arg annotations

[makslevental]

This PR adds support for using the upstream types as bare arg annotions for func.funcs:

@func
def f_same_type_args(
    x: RankedTensorType[[2, 3], F32Type],
    y: RankedTensorType[[2, 3], F32Type],
) -> RankedTensorType[[2, 3], F32Type]: ...

emits

func.func private @f_same_type_args(tensor<2x3xf32>, tensor<2x3xf32>) -> tensor<2x3xf32>

This is thanks to a PR @PragmaTwice recently landed upstream (I can't remember which one exactly...).

As well, we now support the completely "correct" version of this:

@func
def f_mixed_args(
    a: Value[F32Type],
    b: Value[VectorType[[4], F32Type]],
    c: Value[MemRefType[[2, 3], F32Type]],
):
    return b

where tab-complete will now actually do the correct thing as well, and the IR emitted is

func.func @f_mixed_args(%[[A:.*]]: f32, %[[B:.*]]: vector<4xf32>, %[[C:.*]]: memref<2x3xf32>) -> vector<4xf32>

This is thanks to a PR @superbobry landed recently.

NOTE: this actually fixes a long-standing issue with the bindings/extras/DSL: namely that you could not write @funcs without having an active ir.Context (because you cannot actually instantiate ir.Type without an active ir.Context). Since these GenericAliases are unevaluated until we actually emit the func.func, we can now write these safely without an active context.

[makslevental]

unrelated but just a test I forgot to check in here