Add tier 2 partial evaluation pass.

[markshannon]

Once an optimization pass is in place, it enables external contributors to make improvements.
It happened with the tier 1 specializer and is happening now with the tier 2 optimizer and JIT.
We should add the partial evaluation pass, so that external contributors can help with that.

The aim of the partial evaluation pass is to do computation, allocation and deallocation during optimization, so it doesn't need to be done at runtime.

We should add this pass, starting with a few very simple optimizations as placeholders for the full pass to be added later.
These optimizations should include:

• Float unboxing
• Temporary tuple elimination

We can start with the very simple optimization : BUILD_TUPLE 2; _RETURN_VALUE; UNPACK 2 -> _RETURN_PAIR before adding more complex optimizations in the future.

Linked PRs

• GH-120619: Clean up RETURN_VALUE instruction #120624
• gh-120619: Tier 2 partial evaluation pass foundations #123652
• gh-120619: Optimize through _Py_FRAME_GENERAL #124518
• gh-120619: Strength reduce function guards, support 2-operand instruction forms #124846
• gh-120619: Tier 2 partial evaluator foundations #124910
• gh-126902: Strength reduce _CHECK_FUNCTION #126856

[Fidget-Spinner]

@markshannon do you mind if I assign myself to this?

[markshannon]

This is a fairly large feature, so I'd like to do some reasonably detailed design work before we start implementing this.

Fell free to add any thoughts you have about the design here, or in https://github.com/faster-cpython/ideas, but I'd advise against starting coding just yet.

[Fidget-Spinner]

I propose this algorithm, starting with the simplest optimization: LOAD_FAST; POP_TOP -> _NOP, or constant propagation.
faster-cpython/ideas#561 (comment)