Hi,
I'm getting some strange behavior with logaddexp2.reduce:
from itertools import permutations
import numpy as np
x = np.array([-53.584962500721154, -1.5849625007211563, -0.5849625007211563])
for p in permutations([0,1,2]):
print p, np.logaddexp2.reduce(x[list(p)])
Essentially, the result depends on the order of the array...and we get
nans in the "bad" orders. Likely, this also affects logaddexp.
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