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Floating-point arithmetic (lemmy.ml)

submitted 7 months ago by [email protected] to c/[email protected]

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[–] [email protected] 78 points 7 months ago (2 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.

[–] kurwa 44 points 7 months ago

I hope it was garlic NaN at least.

[–] [email protected] 13 points 7 months ago (1 children)

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

[–] [email protected] 27 points 7 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.

[–] fkn 12 points 7 months ago

I too have forgotten to memset my structs in c++ tensorflow after prototyping in python.

[–] [email protected] 3 points 7 months ago* (last edited 7 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

[–] [email protected] 1 points 7 months ago

Oof. This makes me appreciate the abstractions in Go. It's a small thing but initializing structs with zero values by default is nice.

[–] [email protected] 1 points 7 months ago

Oof. C++ really is a harsh mistress.