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Floating-point arithmetic (lemmy.ml)

submitted 9 months ago by [email protected] to c/[email protected]

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[–] [email protected] 80 points 9 months ago (9 children)

Took me 2 hours to find out why the final output of a neural network was a bunch of NaN. This is always very annoying but I can't really complain, it make sense. Just sucks.

[–] [email protected] 13 points 9 months ago (7 children)

I guess you can always just add an assert not data.isna().any() in strategic locations

[–] [email protected] 29 points 9 months ago (4 children)

That could be a nice way. Sadly it was in a C++ code base (using tensorflow). Therefore no such nice things (would be slow too). I skill-issued myself thinking a struct would be 0 -initialized but MyStruct input; would not while MyStruct input {}; will (that was the fix). Long story.

[–] [email protected] 5 points 9 months ago* (last edited 9 months ago)

If you use the GNU libc the feenableexcept function, which you can use to enable certain floating point exceptions, could be useful to catch unexpected/unwanted NaNs

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