--- a/deep/stacked_dae/v_sylvain/nist_sda.py	Mon Apr 26 22:36:07 2010 -0400
+++ b/deep/stacked_dae/v_sylvain/nist_sda.py	Tue Apr 27 08:18:10 2010 -0400
@@ -144,7 +144,10 @@
         All hidden units output are input of the logistic regression\n\n')
         optimizer.reload_parameters('params_pretrain.txt')
         optimizer.finetune(datasets.nist_all(),datasets.nist_P07(),max_finetune_epoch_NIST,ind_test=1,special=1,decrease=decrease_lr)
-        
+    if finetune_choice == 4:
+        print ('\n\n\tFinetune with PNIST07\n\n')
+        optimizer.reload_parameters('params)pretrain.txt')
+        optimizer.finetune(datasets.PNIST07(),datasets.nist_all(),max_finetune_epoch_NIST,ind_test=2,decrease=decrease_lr,dataset_test2=datasets.nist_P07())    
         
     if finetune_choice==-1:
         print('\nSERIE OF 4 DIFFERENT FINETUNINGS')
@@ -169,6 +172,11 @@
         optimizer.reload_parameters('params_pretrain.txt')
         optimizer.finetune(datasets.nist_all(),datasets.nist_P07(),max_finetune_epoch_NIST,ind_test=1,special=1,decrease=decrease_lr)
         channel.save()
+        print ('\n\n\tFinetune with PNIST07\n\n')
+        sys.stdout.flush()
+        optimizer.reload_parameters('params)pretrain.txt')
+        optimizer.finetune(datasets.PNIST07(),datasets.nist_all(),max_finetune_epoch_NIST,ind_test=2,decrease=decrease_lr,dataset_test2=datasets.nist_P07())    
+        
     
     channel.save()