Mercurial > pylearn
changeset 918:bb8ef344d0a9
majorminer op - make it only work on one track at a time
| author | James Bergstra <bergstrj@iro.umontreal.ca> |
|---|---|
| date | Fri, 19 Mar 2010 23:32:23 -0400 |
| parents | 09212b8a1edd |
| children | 3901d06e2d96 |
| files | pylearn/dataset_ops/majorminer.py |
| diffstat | 1 files changed, 7 insertions(+), 9 deletions(-) [+] |
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--- a/pylearn/dataset_ops/majorminer.py Fri Mar 19 23:31:38 2010 -0400 +++ b/pylearn/dataset_ops/majorminer.py Fri Mar 19 23:32:23 2010 -0400 @@ -32,22 +32,20 @@ return hash(type(self)) def make_node(self, idx): - _idx = theano.tensor.as_tensor_variable(idx, ndim=1) + _idx = theano.tensor.as_tensor_variable(idx, ndim=0) return theano.Apply(self, [_idx], [theano.sparse.csr_matrix('MajorMiner.tag_counts'), - theano.generic('MajorMiner.:track_path')]) + theano.generic('MajorMiner.track_path')]) def perform(self, node, (idx,), out_storage): global _meta - lil = scipy.sparse.lil_matrix((len(idx), len(_meta.tags)), dtype='int8') - tracks = [] - for j,i in enumerate(idx): - for tag_id, count in _meta.track_tags[i]: - lil[j,tag_id] = count - tracks.append(_meta.tracks[i]) + lil = scipy.sparse.lil_matrix((1, len(_meta.tags)), dtype='int8') + + for tag_id, count in _meta.track_tags[idx]: + lil[0,tag_id] = count out_storage[0][0] = lil.tocsr() - out_storage[1][0] = tracks + out_storage[1][0] = _meta.tracks[idx] def grad(self, inputs, output): return [None for i in inputs]