Comments (1)
This is due to importing from the source directory. I suppose a check could be added but it doesn't seem like a big issue.
from numba.
Related Issues (20)
- TypingError when conditionally shadowing variable HOT 2
- numba.typed.List fails for F-contiguous np.ndarrays if one is also C-contiguous HOT 1
- No implementation of function `Function(<built-in function setitem>)` found for signature: `setitem(readonly array(uint64, 3d, C), int64, array(int64, 1d, C))` HOT 1
- numba.core.errors.CompilerError: Failed in nopython mode pipeline (step: analyzing bytecode) / Illegal IR, del found at: del foo HOT 1
- numpy.std() results differ with and without numba HOT 4
- cumprod method doesn't upcast unsigned integer array
- A tuple of uint64 (> 2**63 but < 2**64) as the key of numba Dict HOT 3
- NumPy 2.0 incompatibility - A use of `np.complex_` still remains
- NumPy 2.0 incompatibility: RNG's `__getstate__()` returns `None`
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- using rtsys in objmode incur pickle issue HOT 8
- nb.optional doesn't work with nb.types.NamedTuple HOT 5
- Caching is useless on higher order functions
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- jit wrapped numpy sort & unique is more than 5x slower HOT 9
- Failure in `test_TestPrangeSpecific` HOT 2
- Numba 0.60.0 Checklist HOT 1
- Inverting matrices with large condition numbers HOT 1
- unsupported keyword arguments and type inference unification limitation with `np.maximum` HOT 1
- numba HOT 1
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from numba.