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NaN panics #4
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Having NaNs suggests that we might have a vanishing gradient problem here. |
Why changing the random seed do help in this scenario? |
As I understand it, the vanishing/exploding gradient problem really depends on the particular training dynamics, as in most non-linear systems. So changing the random seed may OR may not help. |
During my training, I find that the *sVal(https://github.com/fumin/ntm/blob/master/addressing.go#L194) can easily reach NaN, can this be properly solved, instead of panicing???
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