Remove usages of QueryNormalizer in the compiler

[compiler-errors]

I want to get rid of the QueryNormalizer, possibly changing it to be special cased just for normalizing erasing regions, or perhaps adapting normalize_erasing_regions to use the assoc type normalizer if caching is sufficient and removing it altogther.

This removes the last two usages of .query_normalize in the compiler. There are a few usages left in rustdoc and clippy, which exist only because the query normalizer is more resilient to errors and non-well-formed alias types. I will remove those next.

r? lcnr or reassign

[jackh726]

I certainly see the appeal of having a "querified" way to normalize, but....good riddance to this thing

@bors r+

[bors]

📌 Commit 00a0ef4 has been approved by jackh726

It is now in the queue for this repository.

[compiler-errors]

with the new trait solver, we definitely have even less of a reason to have a query based normalizer

[Kobzol]

@rust-timer build 5f929e7

[rust-timer]

Finished benchmarking commit (5f929e7): comparison URL.

Overall result: ❌✅ regressions and improvements - please read the text below

Benchmarking 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.

Next Steps: If you can justify the regressions found in this try perf run, please indicate this with @rustbot label: +perf-regression-triaged along with sufficient written justification. If you cannot justify the regressions please fix the regressions and do another perf run. If the next run shows neutral or positive results, the label will be automatically removed.

@bors rollup=never
@rustbot label: -S-waiting-on-perf +perf-regression

Instruction count

This 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.

	mean	range	count
Regressions ❌ (primary)	0.4%	[0.2%, 1.1%]	17
Regressions ❌ (secondary)	6.3%	[0.8%, 11.5%]	10
Improvements ✅ (primary)	-	-	0
Improvements ✅ (secondary)	-0.4%	[-0.7%, -0.3%]	19
All ❌✅ (primary)	0.4%	[0.2%, 1.1%]	17

Max RSS (memory usage)

Results (primary -0.9%, secondary -1.1%)

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.

	mean	range	count
Regressions ❌ (primary)	1.0%	[0.6%, 1.4%]	2
Regressions ❌ (secondary)	2.1%	[2.1%, 2.1%]	1
Improvements ✅ (primary)	-2.7%	[-3.2%, -2.3%]	2
Improvements ✅ (secondary)	-2.8%	[-2.8%, -2.7%]	2
All ❌✅ (primary)	-0.9%	[-3.2%, 1.4%]	4

Cycles

Results (secondary 4.9%)

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.

	mean	range	count
Regressions ❌ (primary)	-	-	0
Regressions ❌ (secondary)	6.3%	[2.1%, 11.3%]	10
Improvements ✅ (primary)	-	-	0
Improvements ✅ (secondary)	-2.4%	[-2.5%, -2.4%]	2
All ❌✅ (primary)	-	-	0

Binary size

This benchmark run did not return any relevant results for this metric.

Bootstrap: 775.645s -> 769.912s (-0.74%)
Artifact size: 325.97 MiB -> 325.67 MiB (-0.09%)

[jackh726]

@compiler-errors we should probably address the perf in some way

[compiler-errors]

Yeah I'll probably just revert this with a FIXME lol

I don't think caching is sufficient in the old solver, so we may just need to wait until the new solver is gone to deal with this (or at least we're comfortable using the new solver within specific queries). I don't think the perf can be addressed, and changing how projection caching works in the old solver is really risky lol.