Mercurial > pylearn
changeset 974:f2cdcc71ece1
mcRBM - added L1 penalties and normal sign convention to contrastive grad
| author | James Bergstra <bergstrj@iro.umontreal.ca> |
|---|---|
| date | Mon, 23 Aug 2010 16:02:02 -0400 |
| parents | aa201f357d7b |
| children | 38e66e0da66a |
| files | pylearn/algorithms/mcRBM.py |
| diffstat | 1 files changed, 18 insertions(+), 3 deletions(-) [+] |
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--- a/pylearn/algorithms/mcRBM.py Mon Aug 23 15:59:40 2010 -0400 +++ b/pylearn/algorithms/mcRBM.py Mon Aug 23 16:02:02 2010 -0400 @@ -161,7 +161,7 @@ lr = [lr for p in params] except TypeError: pass - updates = [(p, p + plr * gp) for (plr, p, gp) in zip(lr, params, grads)] + updates = [(p, p - plr * gp) for (plr, p, gp) in zip(lr, params, grads)] return updates def as_shared(x, name=None, dtype=floatX): @@ -295,7 +295,7 @@ def free_energy_given_v(self, v): return free_energy_given_v(self.params, v) - def contrastive_gradient(self, pos_v, neg_v): + def contrastive_gradient(self, pos_v, neg_v, U_l1_penalty=0, W_l1_penalty=0): """Return a list of gradient expressions for self.params :param pos_v: positive-phase sample of visible units @@ -306,7 +306,22 @@ gpos_FE = theano.tensor.grad(pos_FE.sum(), self.params) gneg_FE = theano.tensor.grad(neg_FE.sum(), self.params) - return [ gn - gp for (gp,gn) in zip(gpos_FE, gneg_FE)] + rval = [ gp - gn for (gp,gn) in zip(gpos_FE, gneg_FE)] + rval[0] = rval[0] - TT.sign(self.U)*U_l1_penalty + rval[1] = rval[1] - TT.sign(self.W)*W_l1_penalty + return rval + +from pylearn.dataset_ops.protocol import TensorFnDataset +from pylearn.dataset_ops.memo import memo +import scipy.io +@memo +def load_mcRBM_demo_patches(): + d = scipy.io.loadmat('/u/bergstrj/cvs/articles/2010/spike_slab_RBM/src/marcaurelio/training_colorpatches_16x16_demo.mat') + totnumcases = d["whitendata"].shape[0] + #d = d["whitendata"][0:np.floor(totnumcases/batch_size)*batch_size,:].copy() + d = d["whitendata"].copy() + return d + if __name__ == '__main__':