# HG changeset patch
# User SylvainPL <sylvain.pannetier.lebeuf@umontreal.ca>
# Date 1271254653 14400
# Node ID c2331b8e4b895b720a7b7e9c17a64afec7c99d1e
# Parent  18dc860a4ef4fd8cd915c1c711a3fc705525810c
Ajout d'une ligne faisant rapetisser le finetune_lr pour NIST lorsqu'on a P07+NIST

diff -r 18dc860a4ef4 -r c2331b8e4b89 deep/stacked_dae/v_sylvain/sgd_optimization.py
--- a/deep/stacked_dae/v_sylvain/sgd_optimization.py	Sun Apr 11 19:52:52 2010 -0400
+++ b/deep/stacked_dae/v_sylvain/sgd_optimization.py	Wed Apr 14 10:17:33 2010 -0400
@@ -202,7 +202,11 @@
         total_mb_index = 0
         minibatch_index = 0
         parameters_finetune=[]
-        learning_rate = self.hp.finetuning_lr  #The initial finetune lr
+        
+        if ind_test == 21:
+            learning_rate = self.hp.finetuning_lr / 10.0
+        else:
+            learning_rate = self.hp.finetuning_lr  #The initial finetune lr
 
 
         while (epoch < num_finetune) and (not done_looping):
@@ -320,10 +324,11 @@
             pickle.dump(parameters_finetune,f)
             f.close()
         
-        elif ind_test== 0:    #To keep a track of the value of the parameters
+        elif ind_test == 0 | ind_test == 20:    #To keep a track of the value of the parameters
             f = open('params_finetune_P07.txt', 'w')
             pickle.dump(parameters_finetune,f)
             f.close()
+               
 
         elif ind_test== 1:    #For the run with 2 finetunes. It will be faster.
             f = open('params_finetune_NIST.txt', 'w')