Kernel compute #120
Merged
Kernel compute #120
Conversation
This file contains 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
- Minimal Kronecker kernel. The inverse is highly inefficient - this can be improved! - Added white noise kernel. - Added diagonal computation abstraction. - Added minimal computation abstraction for kernel combinations (i.e., for * and +). Main issues: - Though we can replace the computations in the gps.py, we might miss out with caching stuff e.g., the Cholesky decomposition in the dense computation case. Is there a sensible way around this? - As a further point to the preceding point, we should not be computing the gram matrix in general (yes I known we need to in the dense setting). - Think about computation savings for KL divergences - how can we resolve these? Minor issues: - Need to discuss the best way to add some computation methods - it might be tidier than just adding a load of static methods altogether. - Need tests.
Need to add/update tests/ check code is correct.
Need to write complete tests for covariance operators, then can get on with revamping the rest of the codebase and tests for other modules.
Missing matmul, and need to improve the solve tests to ensure there are now issues with shapes.
Codecov Report
@@ Coverage Diff @@
## v0.5_update #120 +/- ##
===============================================
- Coverage 99.24% 98.27% -0.97%
===============================================
Files 14 15 +1
Lines 1185 1333 +148
===============================================
+ Hits 1176 1310 +134
- Misses 9 23 +14
Flags with carried forward coverage won't be shown. Click here to find out more.
📣 We’re building smart automated test selection to slash your CI/CD build times. Learn more |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
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.
Pull request type
This PR will add infrastructure for memory efficient operations with Gram matrices and allow custom solves.