don't warn about missed memory optimization about view/destroy map when it is about scalar.

theano/compile/debugmode.py

@@ -531,6 +531,11 @@ def _check_inputs(node, storage_map, r_vals, dr_vals, active_nodes, clobber_dr_v
         for oo,ii in vmap.iteritems():
             out_var = storage_map[node.outputs[oo]][0]
             in_var = storage_map[node.inputs[ii[0]]][0]
+            # We don't try to optimize simple scalar, as this is not worth our time
+            # This happen at least in Subtensor when the output is a scalar
+            # But this depend on the version of numpy!
+            if getattr(out_var,'size',2)==1:
+                continue
             if not _may_share_memory(out_var, in_var):
                 #when a subtensor return a tensor of ndim==0, numpy seam to return a copy.
                 #when have an empty ndarray(happen with output guard) it is not the same. why?