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Fix issue in bytecode analysis where target and next are same. - #7149
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As title. Fixes numba#5097 Fixes numba#5680
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This fixes the issue for my reproducer too: from numba import cuda
import numpy as np
@cuda.jit(debug=True)
def f(x, y):
i = 0
for xv, yv in zip(x, y):
if xv != x[i]:
pass
i += 1
x = np.asarray((10, 9, 8, 7, 6))
y = np.asarray((1, 2, 3, 4, 5))
f[1, 1](x, y)which used to fail with: |
sklam
approved these changes
Jun 25, 2021
sklam
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I confirmed that this patch works.
btw, I'm surprise to see that this can happen and CPython is not optimizing it into a unconditional-jump
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As title.
Fixes #5097
Fixes #5680