Make behavior of Cholesky caching more clear

[esantorella]

Motivation

General context: Caching is confusing and can lead to subtle issues. I have been trying to understand it better in order to reduce memory usage and improve runtime, since I've been seeing cache misses and tensors persisting longer than necessary. This PR doesn't fix that, but does make things a tiny bit more transparent.

Two things are making the "_cache_root_decomposition" method harder to understand than necessary:

1. It sets self._baseline_L and returns None rather than just returning baseline_L, so when someone sees a call to _cache_root_decomposition they will not immediately realize self._baseline_L has been set.
2. It is uses two different kinds of caching: it sets self._baseline_L and it also invisibly uses LinearOperator's caching.

This PR makes things more transparent by

• Adding comments
• Returning baseline_L rather than setting it as a side effect

Have you read the Contributing Guidelines on pull requests?

Yes

Test Plan

Unit tests

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[codecov]

Codecov Report

Merging #1504 (d7c1ab4) into main (6f92f2f) will not change coverage.
The diff coverage is 100.00%.

@@            Coverage Diff            @@
##              main     #1504   +/-   ##
=========================================
  Coverage   100.00%   100.00%           
=========================================
  Files          143       143           
  Lines        12760     12759    -1     
=========================================
- Hits         12760     12759    -1     

Impacted Files	Coverage Δ
botorch/acquisition/cached_cholesky.py	100.00% <100.00%> (ø)
botorch/acquisition/monte_carlo.py	100.00% <100.00%> (ø)
botorch/acquisition/multi_objective/monte_carlo.py	100.00% <100.00%> (ø)

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[Balandat]

Thanks, this makes things a lot cleaner!

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@esantorella has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.