--- a/deep/stacked_dae/v_sylvain/sgd_optimization.py	Wed Mar 24 15:14:24 2010 -0400
+++ b/deep/stacked_dae/v_sylvain/sgd_optimization.py	Thu Mar 25 12:20:27 2010 -0400
@@ -87,6 +87,8 @@
     def pretrain(self,dataset):
         print "STARTING PRETRAINING, time = ", datetime.datetime.now()
         sys.stdout.flush()
+        
+        un_fichier=int(819200.0/self.hp.minibatch_size) #Number of batches in a P07 batch
 
         start_time = time.clock()  
         ## Pre-train layer-wise 
@@ -113,7 +115,7 @@
                     
                     #When we pass through the data only once (the case with P07)
                     #There is approximately 800*1024=819200 examples per file (1k per example and files are 800M)
-                    if self.hp.pretraining_epochs_per_layer == 1 and count%819200 == 0:
+                    if self.hp.pretraining_epochs_per_layer == 1 and count%un_fichier == 0:
                         print 'Pre-training layer %i, epoch %d, cost '%(i,num_files),c
                         num_files+=1
                         sys.stdout.flush()