fix bug looking for dtype of scalar, when scalars only have type.dtype

theano/gradient.py

@@ -449,10 +449,10 @@ def grad(cost, wrt, g_cost=None, consider_constant=None,
         # g_cost may be Disconnected or NullType. A creative use of the function,
         # sure, but nonetheless one we can and should support. So before we try
         # to cast it make sure it even has a dtype
-        if hasattr(g_cost, 'dtype') and cost.dtype not in tensor.discrete_dtypes:
+        if hasattr(g_cost.type, 'dtype') and cost.dtype not in tensor.discrete_dtypes:
             # Here we enforce the constraint that floating point variables have
             # the same dtype as their gradient.
-            g_cost = g_cost.astype(cost.dtype)
+            g_cost = g_cost.astype(cost.type.dtype)
         # DO NOT enforce g_cost to be 0 if cost is an integer.
         # This is to be enforced by the Op.grad method for the Op that outputs cost.
         assert g_cost not in tensor.discrete_dtypes