Add Ops for LU Factorization

[jessegrabowski]

Description

This PR will add the following Ops:

• lu
• lu_factor
• lu_solve

As well as dispatches for numba/jax (and maybe torch, though help is welcome there).

The reason for wanting these is that it will make the gradients of solve faster. I think this is a major reason why jax has faster gradients than us (at least when solve is implicated). They route everything to lu_solve(lu_factor(A), b), and reuse lu_factor(A) in the backward pass.

Related Issue

• Closes #
• Related to #

Checklist

• Checked that the pre-commit linting/style checks pass
• Included tests that prove the fix is effective or that the new feature works
• Added necessary documentation (docstrings and/or example notebooks)
• If you are a pro: each commit corresponds to a relevant logical change

Type of change

• New feature / enhancement
• Bug fix
• Documentation
• Maintenance
• Other (please specify):

---

📚 Documentation preview 📚: https://pytensor--1218.org.readthedocs.build/en/1218/

[ricardoV94]

Any benchmarks on solve written with these Ops?

[jessegrabowski]

Working on that next, just ironing out some bugs in the lu_solve Op (which is what all this is building towards)

[codecov]

Codecov Report

Attention: Patch coverage is 74.80720% with 98 lines in your changes missing coverage. Please review.

Project coverage is 82.07%. Comparing base (676296c) to head (1e42069).
Report is 47 commits behind head on main.

Files with missing lines	Patch %	Lines
...ensor/link/numba/dispatch/linalg/solve/lu_solve.py	41.50%	31 Missing ⚠️
...sor/link/numba/dispatch/linalg/decomposition/lu.py	66.66%	20 Missing ⚠️
...k/numba/dispatch/linalg/decomposition/lu_factor.py	56.81%	19 Missing ⚠️
pytensor/link/numba/dispatch/slinalg.py	71.42%	8 Missing and 6 partials ⚠️
pytensor/tensor/slinalg.py	92.20%	6 Missing and 6 partials ⚠️
pytensor/link/jax/dispatch/slinalg.py	92.30%	1 Missing and 1 partial ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1218      +/-   ##
==========================================
+ Coverage   82.05%   82.07%   +0.02%     
==========================================
  Files         203      206       +3     
  Lines       48863    49174     +311     
  Branches     8695     8720      +25     
==========================================
+ Hits        40093    40359     +266     
- Misses       6619     6656      +37     
- Partials     2151     2159       +8     

Files with missing lines	Coverage Δ
pytensor/link/numba/dispatch/basic.py	80.38% <ø> (ø)
...tensor/link/numba/dispatch/linalg/solve/general.py	51.72% <100.00%> (+7.17%)	⬆️
pytensor/tensor/blockwise.py	90.40% <100.00%> (+4.75%)	⬆️
pytensor/tensor/elemwise.py	90.01% <ø> (+0.41%)	⬆️
pytensor/link/jax/dispatch/slinalg.py	85.33% <92.30%> (+3.70%)	⬆️
pytensor/tensor/slinalg.py	93.10% <92.20%> (-0.30%)	⬇️
pytensor/link/numba/dispatch/slinalg.py	69.76% <71.42%> (+0.66%)	⬆️
...k/numba/dispatch/linalg/decomposition/lu_factor.py	56.81% <56.81%> (ø)
...sor/link/numba/dispatch/linalg/decomposition/lu.py	66.66% <66.66%> (ø)
...ensor/link/numba/dispatch/linalg/solve/lu_solve.py	41.50% <41.50%> (ø)

... and 2 files with indirect coverage changes

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.