added a unit test of the disconnected gradient tracking system

theano/tests/test_gradient.py

@@ -522,6 +522,8 @@ def test_undefined_cost_grad():
         # Tests that if we say the cost is not differentiable via the
         # known_grads mechanism, it is treated as such by the rest of the
         # system.
+        # This is so that Ops that are built around minigraphs like OpFromGraph
+        # and scan can implement Op.grad by passing ograds to known_grads
 
         x = theano.tensor.iscalar()
         y = theano.tensor.iscalar()
@@ -533,6 +535,24 @@ def test_undefined_cost_grad():
             return
         raise AssertionError("An undefined gradient has been ignored.")
 
+def test_disconnected_cost_grad():
+
+        # Tests that if we say the cost is disconnected via the
+        # known_grads mechanism, it is treated as such by the rest of the
+        # system.
+        # This is so that Ops that are built around minigraphs like OpFromGraph
+        # and scan can implement Op.grad by passing ograds to known_grads
+
+        x = theano.tensor.iscalar()
+        y = theano.tensor.iscalar()
+        cost = x + y
+        assert cost.dtype in theano.tensor.discrete_dtypes
+        try:
+            grads = theano.tensor.grad(cost, [x, y], known_grads = {cost: gradient.DisconnectedType()() },
+                    disconnected_inputs='raise')
+        except theano.gradient.DisconnectedInputError:
+            return
+        raise AssertionError("A disconnected gradient has been ignored.")
 
 if __name__ == '__main__':
     unittest.main()