Comments (5)
The default parameters should work without problems. Can you say more about your environment (Python version, OS, compiler version, etc.)?
You might want to give CLSTM a try as well; it's the same algorithm in C++.
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My environment:
python 2.7.6
Ubuntu 14.04.1 LTS \n \l
gcc version 4.8.4
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I'm getting the same errors. I've tried clipping the values, but the model seems keeping very high error rates (I'm experimenting with training samples taken from a mobile camera, since we want to recognize receipts uploaded with mobiles)
def ffunc(x):
"Nonlinearity used for gates."
# cliping to avoid overflows
return 1.0/(1.0+exp(clip(-x, None, 700)))
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Sorry for not responding earlier. Can you provide a backtrace?
You might also add a line of python to the main program to turn overflows into errors (when I get around to it, I may do this myself).
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Should be fixed with #201.
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