skip length-one axes when choosing flat stride in init_iter_all#569
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neutrinoceros merged 5 commits intoJun 3, 2026
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Nice. Thank you for addressing these. Can you add regression tests too ? The example reproducers from issues you're fixing are probably good enough already. |
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Jun 2, 2026
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Great. Though these are really two different test cases. I suggest splitting them or, if it makes sense, to parametrize the one test function. |
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Parametrized it into the two cases (issue381, issue393). |
| # issue #393 (F-contiguous branch) | ||
| np.arange(1 * 192 * 121, dtype=np.float64).reshape(1, 192, 121).transpose(0, 2, 1), | ||
| ), | ||
| ids=("issue381", "issue393"), |
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| ids=("issue381", "issue393"), | |
| ids=("C-contiguous", "F-contiguous"), |
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Done, switched the ids to C-contiguous/F-contiguous.
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Jun 3, 2026
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Thanks a lot for triaging and fixing these @sahvx655-wq ! |
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When a reduce-all function gets a transposed view whose size-1 axis carries a large stride (
np.zeros((1,500,2)).transpose(1,2,0),np.zeros((1,192,121)).transpose(0,2,1)), the stride-picking loops in init_iter_all skip only zero strides and grab that axis's huge stride, so iteration runs off the buffer (issues #381, #393: garbage from nanmax or a segfault). Skip length-one axes there too, since their stride is never traversed.