--- a/pylearn/algorithms/mcRBM.py	Thu Sep 01 13:35:15 2011 -0400
+++ b/pylearn/algorithms/mcRBM.py	Fri Sep 09 10:49:54 2011 -0400
@@ -375,7 +375,7 @@
         
         """
         try:
-            return self.W.value.shape[0]
+            return self.W.get_value(borrow=True, return_internal_type=True).shape[0]
         except AttributeError:
             return self.W.shape[0]
 
@@ -387,7 +387,7 @@
         
         """
         try:
-            return self.U.value.shape[1]
+            return self.U.get_value(borrow=True, return_internal_type=True).shape[1]
         except AttributeError:
             return self.U.shape[1]
 
@@ -399,7 +399,7 @@
         
         """
         try:
-            return self.W.value.shape[1]
+            return self.W.get_value(borrow=True, return_internal_type=True).shape[1]
         except AttributeError:
             return self.W.shape[1]
 
@@ -580,7 +580,7 @@
         
         """
         try:
-            return self.P.value.shape[1]
+            return self.P.get_value(borrow=True, return_internal_type=True).shape[1]
         except AttributeError:
             return self.P.shape[1]
 
@@ -669,7 +669,7 @@
         rval = cls.alloc(rbm, visible_batch, batchsize, initial_lr_per_example, rng, l1_penalty,
                 l1_penalty_start, learn_rate_multipliers, lr_anneal_start, persistent_chains)
 
-        rval.p_mask = sharedX((rbm.P.value!=0).astype('float32'), 'p_mask')
+        rval.p_mask = sharedX((rbm.P.get_value(borrow=True)!=0).astype('float32'), 'p_mask')
 
         rval.p_lr = p_lr
         rval.p_training_start=p_training_start