Mercurial > pylearn
diff cost.py @ 451:d99fefbc9324
Added a KL-divergence.
author | Joseph Turian <turian@gmail.com> |
---|---|
date | Thu, 04 Sep 2008 14:46:30 -0400 |
parents | 2bb67e978c28 |
children | 3daabc7f94ff |
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--- a/cost.py Thu Sep 04 14:46:17 2008 -0400 +++ b/cost.py Thu Sep 04 14:46:30 2008 -0400 @@ -6,6 +6,7 @@ """ import theano.tensor as T +from xlogx import xlogx def quadratic(target, output, axis=1): return T.mean(T.sqr(target - output), axis) @@ -16,3 +17,12 @@ @warning: OUTPUT and TARGET are reversed in nnet_ops.binary_crossentropy """ return -T.mean(target * T.log(output) + (1 - target) * T.log(1 - output), axis=axis) + +def KL_divergence(target, output): + """ + @note: We do not compute the mean, because if target and output have + different shapes then the result will be garbled. + """ + return -(target * T.log(output) + (1 - target) * T.log(1 - output)) \ + + (xlogx(target) + xlogx(1 - target)) +# return cross_entropy(target, output, axis) - cross_entropy(target, target, axis)