PERF: fast-path no-op roll cases#31894
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eendebakpt
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Jul 7, 2026
| for ax, offset in shifts.items(): | ||
| offset %= a.shape[ax] or 1 # If `a` is empty, nothing matters. | ||
| if offset: | ||
| roll_needed = True |
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This adds a (tiny) bit of overhead for all cases. How important is the case where no roll is needed? Or where axis is empty?
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would show up as a slower benchmark if it was noticeable no?
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either way, I have more PRs that build on top of this and recover whatever (imo, negligible) losses there might be.
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PR summary
Fast-paths two no-op
np.rollcases:axis=()Addresses gh-12389.
Benchmarks from
spin bench --compare main HEAD -t bench_manipulate.DimsManipulations:time_roll_empty_axes: 59-64% fastertime_roll_zero_shift: 16-18% fasterFirst time committer introduction
I am a NumPy user/contributor looking at small, focused performance improvements in common array operations. I will handle review discussion and follow-up changes directly.
AI Disclosure
LLM / Harness: hybrid.
AI assistance was used to inspect the codebase, run local commands and benchmarks, draft PR text, and help prepare candidate patches. I reviewed the generated suggestions, selected the final changes, and am responsible for the code, submission, and follow-up discussion. Some PR text and candidate code edits were drafted with AI assistance; the final patch and text were reviewed and edited by me.