Mercurial > pylearn
changeset 383:344d1f874af7
Small fix
| author | Joseph Turian <turian@gmail.com> |
|---|---|
| date | Tue, 08 Jul 2008 01:59:42 -0400 |
| parents | b4efd192d880 |
| children | edec18614a70 |
| files | nnet_ops.py sparse_random_autoassociator/graph.py |
| diffstat | 2 files changed, 4 insertions(+), 4 deletions(-) [+] |
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--- a/nnet_ops.py Tue Jul 08 01:58:16 2008 -0400 +++ b/nnet_ops.py Tue Jul 08 01:59:42 2008 -0400 @@ -386,4 +386,4 @@ @note: We do not sum, crossentropy is computed by component. @todo: Rewrite as a scalar, and then broadcast to tensor. """ - return -(target * t.log(output) + (1 - target) * t.log(1 - output)) + return -(target * tensor.log(output) + (1 - target) * tensor.log(1 - output))
--- a/sparse_random_autoassociator/graph.py Tue Jul 08 01:58:16 2008 -0400 +++ b/sparse_random_autoassociator/graph.py Tue Jul 08 01:59:42 2008 -0400 @@ -6,7 +6,7 @@ from globals import MARGIN -from pylearn.nnet_ops import sigmoid, crossentropy_softmax_1hot +from pylearn.nnet_ops import sigmoid, binary_crossentropy from theano import tensor as t from theano.tensor import dot xnonzero = t.dvector() @@ -29,9 +29,9 @@ # xnonzero sensitive loss: #nonzeroloss = hingeloss(ynonzero - t.max(yzero) - MARGIN - xnonzero) #zeroloss = hingeloss(-t.max(-(ynonzero - xnonzero)) - yzero - MARGIN) -loss = t.sum(nonzeroloss) + t.sum(zeroloss) +#loss = t.sum(nonzeroloss) + t.sum(zeroloss) -#loss = t.sum(binary_crossentropy(ynonzero, xnonzero)) + t.sum(binary_crossentropy(yzero, t.constant(0))) +loss = t.sum(binary_crossentropy(ynonzero, xnonzero)) + t.sum(binary_crossentropy(yzero, t.constant(0))) (gw1nonzero, gb1, gw2nonzero, gw2zero, gb2nonzero, gb2zero) = t.grad(loss, [w1nonzero, b1, w2nonzero, w2zero, b2nonzero, b2zero])