added a specific exception for disconnected inputs, so it can be

theano/gradient.py

@@ -365,7 +365,7 @@ def grad(cost, wrt, consider_constant=None,
         (or if all links are non-differentiable). The possible values are:
         - 'ignore': considers that the gradient on these parameters is zero.
         - 'warn': consider the gradient zero, and print a warning.
-        - 'raise': raise an exception.
+        - 'raise': raise DisconnectedInputError.
 
     :type add_names: bool
     :param add_names: If True, variables generated by grad will be named
@@ -499,7 +499,7 @@ def grad(cost, wrt, consider_constant=None,
             elif disconnected_inputs == 'warn':
                 warnings.warn(message, stacklevel=2)
             elif disconnected_inputs == 'raise':
-                raise ValueError(message)
+                raise DisconnectedInputError(message)
             else:
                 raise ValueError("Invalid value for keyword "
                         "'disconnected_inputs', valid values are "
@@ -719,7 +719,13 @@ class NullTypeGradError(TypeError):
     """
     Raised when grad encounters a NullType.
     """
-    pass
+
+class DisconnectedInputError(ValueError):
+    """
+    Raised when grad is asked to compute the gradient
+    with respect to a disconnected input and
+    disconnected_inputs='raise'.
+    """
 
 def _populate_grad_dict(var_to_node_to_idx,
         grad_dict, wrt, cost_name=None):