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Cost functions.
Note: All of these functions return one cost per example. So it is your job to perform a tensor.sum over the individual example losses.
To Do:







Imports: T, xlogx

This is the crossentropy over a binomial event, in which each dimension is an independent binomial trial. To Do: This is essentially duplicated as nnet_ops.binary_crossentropy Warning: OUTPUT and TARGET are reversed in nnet_ops.binary_crossentropy 
This is a KL divergence over a binomial event, in which each dimension is an independent binomial trial. Note: We do not compute the mean, because if target and output have different shapes then the result will be garbled. 
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