simplified code a little bit.

theano/tensor/opt.py

@@ -1230,7 +1230,7 @@ def local_subtensor_lift(node):
                 return [u.owner.op(*new_inputs)]
 
 
-def greedy_local_optimizer(list_optimizations, out, no_opt):
+def greedy_local_optimizer(list_optimizations, out):
     '''
     This function traverses the computation graph described by all
     ``node`` in the graph before the variable out but that are not in the env.
@@ -1240,13 +1240,17 @@ def greedy_local_optimizer(list_optimizations, out, no_opt):
     the graph of the indices of a subtensor.
 
     We should not apply optimizations on node that are in env.
-    So we don't optimize node in no_opt.
+    So we don't optimize node that have an attribute env.
+
+    :note: This don't do an equilibrium... So if there is optimization
+           in the list, there can be case when calling this function
+           multiple time do think at each call.
     '''
     def local_recursive_function( list_opt, out, optimized_vars, depth):
         if not out.owner :
             return [out], optimized_vars
         node = out.owner
-        if node in no_opt:
+        if hasattr(node, 'env'):
             return node.outputs, optimized_vars
         for idx, inp in enumerate(node.inputs):
             if inp in optimized_vars:
@@ -1399,24 +1403,16 @@ def merge_two_slices(slice1, len1, slice2, len2):
         start = T.switch(T.le(flen,0), 0, start)
         stop  = T.switch(T.le(flen,0), 0, stop)
 
-        # Find the list of nodes in the env.
-        # We should not optimize them here!
-        list_no_opt = set()
-        for sl in [slice1, slice2]:
-            if isinstance(sl, slice):
-                for idx in [sl.start, sl.stop, sl.step]:
-                    if isinstance(idx, Variable):
-                        list_no_opt.update(idx.env.nodes)
-            if isinstance(sl, Variable):
-                list_no_opt.update(sl.env.nodes)
-
         # The canonical form of the slice is pretty complicated
         # and is not simplified. We simplify it in advance here
         # as otherwise this create too many useless optimization that
         # DebugMode must check.
-        start = greedy_local_optimizer( list_opt, start, list_no_opt)
-        stop  = greedy_local_optimizer( list_opt, stop, list_no_opt)
-        step  = greedy_local_optimizer( list_opt, step, list_no_opt)
+        start = greedy_local_optimizer( list_opt, start)
+        stop  = greedy_local_optimizer( list_opt, stop)
+        step  = greedy_local_optimizer( list_opt, step)
+        start = greedy_local_optimizer( list_opt, start)
+        stop  = greedy_local_optimizer( list_opt, stop)
+        step  = greedy_local_optimizer( list_opt, step)
 
         #start = theano.printing.Print('start')(start)
         #stop  = theano.printing.Print('stop')(stop)