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.
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.
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.
I hope it was garlic NaN at least.
I guess you can always just add an
assert not data.isna().any()in strategic locationsThat 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 whileMyStruct input {};will (that was the fix). Long story.I too have forgotten to memset my structs in c++ tensorflow after prototyping in python.
Oof. C++ really is a harsh mistress.