Comments (3)
I only glanced at this, but negative indexing is not yet supported (the wrap-around). That might cause this (I didn't verify for your case).
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Yes. It seems that it overrides malloc internal structure. It seems to not work with l_j = out[j](it seems to create copy instead of view).
(Sorry to say but my main complaint ATM is that it is hard to predict what is supported so it is mostly trial an error).
from numba.
Indeed, I'll document this behaviour. I'm closing this for now, wraparound is on the todo list.
from numba.
Related Issues (20)
- Test fail on LLVM15 `test_noinline_on_main_call` HOT 3
- Cannot cache function with jitclass as argument
- Test failure on LLVM15: `test_remainder_float` HOT 7
- ~~True return True HOT 1
- Numba functions do not consider global variables from other modules as compile time constant. HOT 12
- RuntimeError: cannot cache function '_make_tree': no locator available HOT 5
- Can't execute python tests directly without using runtests.py HOT 2
- Memory leak when applying numba to an inner function HOT 1
- Errors not being raised when running code in parallel HOT 1
- Source/AST Frontend for Numba HOT 10
- typed.List __repr__() HOT 3
- Bug in the compiler in 0.60 : 'tuple' object has no attribute 'name' HOT 1
- Numba much slower than `np.sum`, and more sensitive to summation axis HOT 1
- First-class function type initializes too late
- inefficient matrix multiplication with its transpose HOT 4
- np.count_nonzero is incorrect when setting axis=0 for 1-dimensional array HOT 2
- Installation fails on termux Python 3.11 HOT 3
- Compilation failure with NumPy 2.0.1 HOT 2
- isfinite(inf) raises FloatingPointError in vectorized functions HOT 5
- TypingError When Accessing Attributes of Nested JitClasses HOT 4
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from numba.