Decompose Tridiagonal Solve into core steps #1382
Merged
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
ricardoV94
force-pushed
the
decompose_tridiagonal_solve
branch
from
cc4fab6 to
c72326e
Compare
|
Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
ricardoV94
force-pushed
the
decompose_tridiagonal_solve
branch
4 times, most recently
from
2436cd1 to
aceab09
Compare
ricardoV94
added
enhancement
Member
|
Is this blocked by anything? Or just needs a bit of polishing to make mypy happy etc |
Member
Author
|
Needs a bit rework after the LU PR |
ricardoV94
force-pushed
the
decompose_tridiagonal_solve
branch
4 times, most recently
from
209f71f to
9652c5d
Compare
ricardoV94
force-pushed
the
decompose_tridiagonal_solve
branch
5 times, most recently
from
70da029 to
6bc5484
Compare
ricardoV94
force-pushed
the
decompose_tridiagonal_solve
branch
3 times, most recently
from
be7aa49 to
6c985c9
Compare
jessegrabowski
requested changes
Jun 9, 2025
Comment on lines
+135
to
+152
| dummy_arrays = [ | ||
| np.zeros((), dtype=inp.type.dtype) for inp in (dl, d, du, du2, ipiv) | ||
| ] | ||
| # Seems to always be float64? | ||
| out_dtype = get_lapack_funcs("gttrs", dummy_arrays).dtype |
Member
There was a problem hiding this comment.
Same here -- get_lapack_output_dtype_from_inputs?
Member
Author
There was a problem hiding this comment.
What do you mean? Is there such a helper? Google doesn't return anything
Member
There was a problem hiding this comment.
I meant make that function to hold the logic for making dummy arrays and getting the out_dtype form get_lapack_funcs
ricardoV94
force-pushed
the
decompose_tridiagonal_solve
branch
from
6c985c9 to
2e6c90f
Compare
ricardoV94
force-pushed
the
decompose_tridiagonal_solve
branch
from
2e6c90f to
758fcdd
Compare
jessegrabowski
approved these changes
Jun 10, 2025
Member
jessegrabowski
left a comment
jessegrabowski
left a comment
There was a problem hiding this comment.
Approving now, idk if there's more you want to adjust but I'm happy
ricardoV94
force-pushed
the
decompose_tridiagonal_solve
branch
from
758fcdd to
d037bd0
Compare
ricardoV94
force-pushed
the
decompose_tridiagonal_solve
branch
from
d037bd0 to
acd9219
Compare
ricardoV94
force-pushed
the
decompose_tridiagonal_solve
branch
from
acd9219 to
4847344
Compare
Codecov Report❌ Patch coverage is Additional details and impacted files@@ Coverage Diff @@
## main #1382 +/- ##
==========================================
- Coverage 82.12% 82.09% -0.03%
==========================================
Files 211 212 +1
Lines 49757 49965 +208
Branches 8819 8858 +39
==========================================
+ Hits 40862 41018 +156
- Misses 6715 6757 +42
- Partials 2180 2190 +10
🚀 New features to boost your workflow:
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This PR builds on top of #1396, extending it to the tridiagonal case.
It also adds a rewrite for when extracting diagonals out a symbolically allocated diagonal matrix (via set_subtensor or AllocDiag after it gets inlined during specialization)
TODO: