Closed mmcdermott closed 1 month ago
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Files that changed from the base of the PR and between f687e9e2c8edcfd1b7a1d9d0eaf01da54da17ea3 and f2e0466beeeb03ba476903d3dc020d229e3f6425.
The changes in the pull request focus on simplifying the handling of nested ragged tensors in the ragged_numpy.py
file. Key modifications include flattening nested lists into a single array during tensor initialization, streamlining the load
method by removing unnecessary checks, enhancing the __getitem__
method for clarity in slicing, and refining the concatenate
method for better error handling. Additionally, adjustments were made to the benchmarking configuration in the .github/workflows/benchmark.yaml
file, altering alert thresholds and failure behaviors.
Files | Change Summary |
---|---|
src/nested_ragged_tensors/ragged_numpy.py |
Simplified initialization by flattening nested lists, streamlined load , modified __getitem__ for clarity, refined concatenate for error handling. |
.github/workflows/benchmark.yaml |
Adjusted benchmarking job configuration by lowering alert threshold and changing failure behavior. |
Objective | Addressed | Explanation |
---|---|---|
Tensors should not be split into lists of lists until densification (#21) | ✅ |
In the land of tensors, so deep and wide,
A rabbit hops forth with changes to guide.
Flattened arrays, oh what a delight,
Slicing and loading, all done just right!
With clearer paths and errors in sight,
Our code now dances, oh what a sight! 🐇✨
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Attention: Patch coverage is 93.54839%
with 2 lines
in your changes missing coverage. Please review.
Project coverage is 92.49%. Comparing base (
1b41e1b
) to head (f2e0466
).
:white_check_mark: All tests successful. No failed tests found.
Files with missing lines | Patch % | Lines |
---|---|---|
src/nested_ragged_tensors/ragged_numpy.py | 93.54% | 2 Missing :warning: |
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This currently causes a significant reduction in overall speed, and, unexpectedly (and unimportantly) a degradation in preparation time: I'll try some different ways to densify the data.
Skipping the subdivision into lists and also not using np.put
is apparently the best version of this change.
Closes #21
Summary by CodeRabbit
New Features
Bug Fixes
Refactor
Chores