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(-) [+]
line wrap: on
line diff
--- 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())