Mercurial > pylearn
changeset 347:3aa9e5a5802a
Automated merge with ssh://projects@lgcm.iro.umontreal.ca/hg/pylearn
author | Frederic Bastien <bastienf@iro.umontreal.ca> |
---|---|
date | Tue, 17 Jun 2008 14:46:15 -0400 |
parents | 9de4274ad5ba (diff) a22ea54a19ed (current diff) |
children | 952129cd55cb |
files | _test_dataset.py |
diffstat | 2 files changed, 16 insertions(+), 1 deletions(-) [+] |
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--- a/_test_dataset.py Tue Jun 17 14:46:10 2008 -0400 +++ b/_test_dataset.py Tue Jun 17 14:46:15 2008 -0400 @@ -599,6 +599,15 @@ del a, ds + def test_RenamedFieldsDataSet(self): + a = numpy.random.rand(10,4) + ds = ArrayDataSet(a,Example(['x','y','z','w'],[slice(3),3,[0,2],0])) + ds = FieldsSubsetDataSet(ds,['x','y','z'],['x1','y1','z1']) + + test_all(a,ds) + + del a, ds + def test_MinibatchDataSet(self): raise NotImplementedError() def test_HStackedDataSet(self):
--- a/statscollector.py Tue Jun 17 14:46:10 2008 -0400 +++ b/statscollector.py Tue Jun 17 14:46:15 2008 -0400 @@ -1,7 +1,13 @@ # Here is how I see stats collectors: -# def my_stats((residue,nll),(regularizer)): +def my_stats(graph): + graph.mse=examplewise_mean(square_norm(graph.residue)) + graph.training_loss=graph.regularizer+examplewise_sum(graph.nll) + return [graph.mse,graph.training_loss] + + +# def my_stats(residue,nll,regularizer): # mse=examplewise_mean(square_norm(residue)) # training_loss=regularizer+examplewise_sum(nll) # set_names(locals())