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refactor fudge_inference, handle effect vars #131911
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@bors try @rust-timer queue |
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refactor fudge_inference, handle effect vars this makes it easier to use fudging outside of `fudge_inference_if_ok`, which is likely necessary to handle inference variable leaks on rollback. We now also uses exhaustive matches where possible and improve the code to handle effect vars. r? `@compiler-errors` `@BoxyUwU`
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Finished benchmarking commit (18ddfc8): comparison URL. Overall result: ❌ regressions - no action neededBenchmarking this pull request likely means that it is perf-sensitive, so we're automatically marking it as not fit for rolling up. While you can manually mark this PR as fit for rollup, we strongly recommend not doing so since this PR may lead to changes in compiler perf. @bors rollup=never Instruction countThis is the most reliable metric that we have; it was used to determine the overall result at the top of this comment. However, even this metric can sometimes exhibit noise.
Max RSS (memory usage)Results (secondary -2.7%)This is a less reliable metric that may be of interest but was not used to determine the overall result at the top of this comment.
CyclesResults (secondary -6.5%)This is a less reliable metric that may be of interest but was not used to determine the overall result at the top of this comment.
Binary sizeThis benchmark run did not return any relevant results for this metric. Bootstrap: 781.3s -> 782.228s (0.12%) |
@bors r+ |
☀️ Test successful - checks-actions |
Finished benchmarking commit (54791ef): comparison URL. Overall result: ❌ regressions - no action needed@rustbot label: -perf-regression Instruction countThis is the most reliable metric that we have; it was used to determine the overall result at the top of this comment. However, even this metric can sometimes exhibit noise.
Max RSS (memory usage)Results (primary 0.1%)This is a less reliable metric that may be of interest but was not used to determine the overall result at the top of this comment.
CyclesThis benchmark run did not return any relevant results for this metric. Binary sizeThis benchmark run did not return any relevant results for this metric. Bootstrap: 781.579s -> 782.091s (0.07%) |
this makes it easier to use fudging outside of
fudge_inference_if_ok
, which is likely necessary to handle inference variable leaks on rollback.We now also uses exhaustive matches where possible and improve the code to handle effect vars.
r? @compiler-errors @BoxyUwU