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Related Issues (20)
- `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 4
- 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
- CUDA target respect NUMBA_OPT environment variable HOT 4
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