fixed a check for undefined grads in scan_module that could be triggered

theano/gradient.py

@@ -753,6 +753,11 @@ def _populate_var_to_node_to_idx(outputs, wrt, consider_constant):
 
     return var_to_app_to_idx
 
+class NullTypeGradError(TypeError):
+    """
+    Raised when grad encounters a NullType.
+    """
+    pass
 
 def _populate_grad_dict(var_to_node_to_idx,
         grad_dict, wrt, cost_name=None):
@@ -1010,7 +1015,7 @@ def _populate_grad_dict(var_to_node_to_idx,
                                         type(term)))
 
                         if isinstance(term.type, NullType):
-                            raise TypeError("tensor.grad "
+                            raise NullTypeGradError("tensor.grad "
                                 "encountered a NaN. " +\
                                     term.type.why_null)
 

theano/scan_module/scan_op.py

@@ -1261,11 +1261,10 @@ class Scan(PureOp):
                              if x in diff_inputs]
             for x in consider_inps:
                 try:
-                    _gmp = gradient.grad_sources_inputs(
-                        [(y, g_y)],
-                        [x])
-                    gmp[x] = _gmp[x]
-                except TypeError:
+                    gmp[x] = gradient.grad(cost=None,
+                            known_grads={y: g_y},
+                        wrt=x)
+                except gradient.NullTypeGradError:
                     # It means the gradient is undefined (which implies
                     # is connected)
                     gmp[x] = x