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mmcdermott / nested_ragged_tensors

Utilities for efficiently working with, saving, and loading, collections of connected nested ragged tensors in PyTorch
MIT License
7 stars 1 forks source link

Made splitting only happen at densification. #30

Closed mmcdermott closed 1 month ago

mmcdermott commented 1 month ago

Closes #21

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Commits Files that changed from the base of the PR and between f687e9e2c8edcfd1b7a1d9d0eaf01da54da17ea3 and f2e0466beeeb03ba476903d3dc020d229e3f6425.

Walkthrough

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.

Changes

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.

Assessment against linked issues

Objective Addressed Explanation
Tensors should not be split into lists of lists until densification (#21) ✅

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Flattened arrays, oh what a delight,
Slicing and loading, all done just right!
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codecov-commenter commented 1 month ago

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Codecov Report

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:
Additional details and impacted files ```diff @@ Coverage Diff @@ ## main #30 +/- ## ========================================== - Coverage 92.77% 92.49% -0.28% ========================================== Files 2 2 Lines 332 333 +1 ========================================== Hits 308 308 - Misses 24 25 +1 ```

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

mmcdermott commented 1 month ago

This currently causes a significant reduction in overall speed, and, unexpectedly (and unimportantly) a degradation in preparation time: image I'll try some different ways to densify the data.

mmcdermott commented 1 month ago

Skipping the subdivision into lists and also not using np.put is apparently the best version of this change.