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added type hints #849
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added type hints #849
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So CI seems to fail for test with the following difference (so essentially in a single repr there is a list instead of a tuple)
This comes from class Instruction(NamedValue, _HasMetadata):
operands: list[Value]
def replace_usage(self, old: Constant, new: Constant) -> None:
if old in self.operands:
ops: list[Value] = []
for op in self.operands:
ops.append(new if op is old else op)
self.operands = ops # remove tuple() here
self._clear_string_cache() However, that tuple type doesn't really make sense in the broader spectrum, since in class CallInstr(Instruction):
@callee.setter
def callee(self, newcallee: Function) -> None:
self.operands[0] = newcallee I'd argue that There is also an additional error due to |
(Labelled as Waiting on Reviewer as this is waiting for some feedback about the CI issues) Apologies for the delay in getting back to you about this - The 0.39 / Numba 0.56 release has occupied the majority of maintainers' time recently. |
Hello! I have a similar issue of wanting type annotations for llvmlite and ended up here :) Is there a plan to circle back to this PR eventually? I imagine it's lower priority than supporting new LLVM versions but would be a nice QoL update. Happy to contribute |
@enathang Thanks for the ping, and for offering to contribute - as none of the maintainers are very familliar with type annotations, it would be great if you could guide us a little - do you have any thoughts on the comments in #849 (comment)? I think being able to address them will help un-stick this PR. |
Hey @gmarkall ! I'm also not super familiar with type annotations, but I'll throw my hat in the ring regardless :) The main issue of the comment doesn't seem to be a type annotation issue per-se. Mostly, it's "should the operands for Instruction be represented as a tuple or a list?" Based on the current unit tests, they're represented as a tuple. However, the code treats it as a list, including mutating specific elements of it (which is impossible for tuples because they're static but fine for lists because they're dynamic.) If we want to stick with tuples, the question is: why are we trying to mutate the tuple (and why is python letting us)? Is it actually a list under the hood or is it truly a tuple? If we want to switch to a list, the trade-off is mostly performance afaik. Tuples have nice memory layout properties that lists do not. So the path forward is:
@marvinvanaalst can correct me if I've missed anything, mostly I'm rephrasing his comments for my own understanding. I'll try to get everything up and running where I can answer (1). If there are any un-obvious reasons why the operands were set to be tuples ([sklam] was the original implementer according to git blame), I'd love to hear their opinion. |
@enathang Thanks for thinking about this and adding some detailed thoughts and a path forward!
My guess would be that it's supposed to be a list - presumably the tests that pass a tuple avoid causing anything to happen that would result in them being mutated? I'd guess that the right way forward is to just say that they should be lists, and annotate as such. I think most uses I've noticed in Numba pass lists to instructions - I have a vague recollection of trying to convert some lists to tuples in the Numba codebase for the general reasons that tuples tend to be preferable to lists, and running into issues as a result.
That would be great - let us know if you need any guidance, and I look forward to seeing what you discover! |
Well yes, it's a OOP design issue really.
In I'd also still be open to help out on this issue, we will just have to see how much work it is going forward to merge this.
A third option is to use a type that works for both, like |
Since #848 contained too many non-typing related changes, here is the cleaner version.
I commented out the type hints that require the typing-extensions package like
Literal[0, 1, 2, 3]
foropt
inllvmpy.passes.create_pass_manager_builder
. If you don't have anything against adding that dependency, I'd happily add it back in, as it does carry additional information.I had to punt on several occasions and go for
type: ignore
, mainly because mypy / pylance don't like mixin classes.There are also a number of typecasts that I did. I usually added a
FIXME
such that they are double-checked.@gmarkall let me know if I forgot to clean up something, it has been a long day ;)