# HG changeset patch
# User delallea@opale.iro.umontreal.ca
# Date 1211917749 14400
# Node ID c047238e5b3fcbd3a8c43830cf87c6ef00cc2bac
# Parent  38beb81f4e8be838a2ec7b36eeb4754ffb049951
Fixed by James

diff -r 38beb81f4e8b -r c047238e5b3f mlp_factory_approach.py
--- a/mlp_factory_approach.py	Tue May 27 13:46:03 2008 -0400
+++ b/mlp_factory_approach.py	Tue May 27 15:49:09 2008 -0400
@@ -46,7 +46,7 @@
         #TODO: why should we have to unpack target like this?
         # tbm : creates problem...
         for input, target in input_target:
-            rval= self.update_fn(input, target[:,0], *params)
+            rval= self.update_fn(input, target, *params)
             #print rval[0]
 
     def __call__(self, testset, fieldnames=['output_class'],input='input',target='target'):
@@ -136,7 +136,7 @@
             for stp in self.early_stopper():
                 rval.update(
                     minset.minibatches([input, target], minibatch_size=min(32,
-                        len(trainset))))
+                        len(minset))))
                 #print 'mlp.__call__(), we did an update'
                 if stp.set_score:
                     stp.score = rval(valset, ['loss_01'])
@@ -171,7 +171,7 @@
                 , linker='c&py'
                 , early_stopper = lambda:stopper.NStages(100,1))
 
-        model1 = learn_algo(training_set1,input='input',target='target')
+        model1 = learn_algo(training_set1)
 
         model2 = learn_algo(training_set2)