make grad method enforce right number of dimensions

theano/gradient.py

@@ -873,6 +873,7 @@ def _populate_grad_dict(var_to_node_to_idx,
     # populate grad_dict[var] and return it
     def access_grad_cache(var):
         if var not in grad_dict:
+            # If var is not in grad_dict already, we must compute it
             if var in var_to_node_to_idx:
                 terms = []
                 node_to_idx = var_to_node_to_idx[var]
@@ -895,6 +896,11 @@ def _populate_grad_dict(var_to_node_to_idx,
                         if isinstance(term.type, DisconnectedType):
                             continue
 
+                        if hasattr(var,'ndim') and term.ndim != var.ndim:
+                            raise ValueError(("%s.grad returned a term with"
+                                " %d dimensions, but %d are required.") % (
+                                    str(node.op), term.ndim, var.ndim))
+
                         terms.append(term)
 
                 # Add up the terms to get the total gradient on this variable
@@ -911,6 +917,7 @@ def _populate_grad_dict(var_to_node_to_idx,
                 # this variable isn't connected to the cost in the computational
                 # graph
                 grad_dict[var] = DisconnectedType()()
+        # end if cache miss
         return grad_dict[var]
 
     rval = [access_grad_cache(elem) for elem in wrt]