Comments (2)
jriehl
commented on June 23, 2024
The example should work if you lower the indentation level of return result one level.
OTOH, the example as typed is an interesting bug because it illustrates a shortcoming in my fix for issue #25. The premature return statement is causing the nominal loop exit target to be (correctly) identified as dead code, and eliminated. The loop transformation code doesn't account for this possibility, and crashes.
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jriehl
commented on June 23, 2024
Fixed, per unit test added to numba.tests.test_sum.TestSum2d.
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Related Issues (20)
- Update changelog script to account for missing author info on github.
- `searchsorted` with dtype `datetime64` stopped working in `njit` mode going from 0.58.1 to 0.59 HOT 2
- GPU target doesn't emit compile events HOT 1
- explicit specialization does not respect caching HOT 3
- Bug: (regression) cooperative grid sync w/ cache=True - working in 0.58.1, not working in 0.59.0 HOT 4
- np.median raises AssertionError for empty arrays while numpy returns nan HOT 1
- Integrate ZLUDA for AMD CUDA HOT 3
- `nextafter` (via both `math` and `numpy`) missing for CUDA
- Fill out `python -m numba -s` field for `CUDA Libraries Test Output` (even if GPU is absent) HOT 1
- Overloaded function is compiled more than once with the same signature HOT 4
- Regression: searchsorted drastically slower in tight loops HOT 3
- test_sum1d_pyobj crashes on aarch64-linux on 0.59.0 HOT 5
- `AttributeError` for inlined generic functions with py312 pep-695 type-parameter syntax HOT 5
- [numba.cuda] StructModel + FP16 fails with CUDA because make_attribute_wrapper assumes default_manager HOT 1
- No matching implimentation for `np.empty` in guvectorized function with `NUMBA_DISABLE_JIT=1` and related caching issue HOT 4
- Casting error HOT 3
- overload_methoded function shouldn't set `no_cpython_wrapper` as `False` HOT 2
- How about unifying `int32` and `Literal[int](0)` as `int32`, rather than `int64` HOT 2
- The `np.size()` Function Fails HOT 1
- I get super bad performance when using zip() and parallel=True HOT 3
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