Propagate constexpr through tl.minimum and tl.maximum?

[blaine-rister]

I noticed that tl.minimum and tl.maximum do not seem to propagate constexprs.
https://github.com/openai/triton/blob/22af8d80458ee4e6269779dae0a3c34b755aade2/python/triton/language/core.py#L569

Would it be feasible to add this functionality? I'm guessing it would be possible to check if both args are constexpr in the function's implementation.

This could be useful for performing more advanced reshaping operations in TorchInductor. We would like to convert 1D tensor shape into an ND one, which could be expressed with tl.minimum. However, calling tl.minimum seems to drop the constexpr property of its inputs. See pytorch/pytorch#125077 for some additional context.

As an alternative, there might be a way to support similar functionality in constexprs using python builtins, such as min(x,y) = x * (x <= y) + y * (y < x). But tl.minimum(x,y) would be more concise.