Add test for R_Op of OpFromGrah with multiple outputs

tests/compile/test_builders.py

@@ -310,6 +310,41 @@ class TestOpFromGraph(unittest_tools.InferShapeTester):
         dvval2 = fn(xval, Wval, duval)
         np.testing.assert_array_almost_equal(dvval2, dvval, 4)
 
+    def test_rop_multiple_outputs(self):
+        a = vector()
+        M = matrix()
+        b = dot(a, M)
+        op_matmul = OpFromGraph([a, M], [b, -b])
+
+        x = vector()
+        W = matrix()
+        du = vector()
+
+        xval = np.random.random((16,)).astype(config.floatX)
+        Wval = np.random.random((16, 16)).astype(config.floatX)
+        duval = np.random.random((16,)).astype(config.floatX)
+
+        y = op_matmul(x, W)[0]
+        dv = Rop(y, x, du)
+        fn = function([x, W, du], dv)
+        result_dvval = fn(xval, Wval, duval)
+        expected_dvval = np.dot(duval, Wval)
+        np.testing.assert_array_almost_equal(result_dvval, expected_dvval, 4)
+
+        y = op_matmul(x, W)[1]
+        dv = Rop(y, x, du)
+        fn = function([x, W, du], dv)
+        result_dvval = fn(xval, Wval, duval)
+        expected_dvval = -np.dot(duval, Wval)
+        np.testing.assert_array_almost_equal(result_dvval, expected_dvval, 4)
+
+        y = pt.add(*op_matmul(x, W))
+        dv = Rop(y, x, du)
+        fn = function([x, W, du], dv)
+        result_dvval = fn(xval, Wval, duval)
+        expected_dvval = np.zeros_like(np.dot(duval, Wval))
+        np.testing.assert_array_almost_equal(result_dvval, expected_dvval, 4)
+
     @pytest.mark.parametrize(
         "cls_ofg", [OpFromGraph, partial(OpFromGraph, inline=True)]
     )