diff --git a/src/TensorFlowNET.Core/Variables/ResourceVariable.Operators.cs b/src/TensorFlowNET.Core/Variables/ResourceVariable.Operators.cs
index b96576e5..a874832f 100644
--- a/src/TensorFlowNET.Core/Variables/ResourceVariable.Operators.cs
+++ b/src/TensorFlowNET.Core/Variables/ResourceVariable.Operators.cs
@@ -22,23 +22,26 @@ namespace Tensorflow
 {
     public partial class ResourceVariable
     {
-        public static Tensor operator +(ResourceVariable x, int y) => op_helper("add", x, y);
-        public static Tensor operator +(ResourceVariable x, float y) => op_helper("add", x, y);
-        public static Tensor operator +(ResourceVariable x, double y) => op_helper("add", x, y);
-        
-        public static Tensor operator -(ResourceVariable x, int y) => op_helper("sub", x, y);
-        public static Tensor operator -(ResourceVariable x, float y) => op_helper("sub", x, y);
-        public static Tensor operator -(ResourceVariable x, double y) => op_helper("sub", x, y);
-        public static Tensor operator -(ResourceVariable x, Tensor y) => op_helper("sub", x, y);
+        public static OpDefLibrary _op_def_lib = new OpDefLibrary();
 
-        public static Tensor operator *(ResourceVariable x, ResourceVariable y) => op_helper("mul", x, y);
-        public static Tensor operator *(ResourceVariable x, NDArray y) => op_helper("mul", x, y);
+        public static ResourceVariable operator +(ResourceVariable x, int y) => op_helper("add", x, y);
+        public static ResourceVariable operator +(ResourceVariable x, float y) => op_helper("add", x, y);
+        public static ResourceVariable operator +(ResourceVariable x, double y) => op_helper("add", x, y);
+        public static ResourceVariable operator +(ResourceVariable x, ResourceVariable y) => op_helper("add", x, y);
+        public static ResourceVariable operator -(ResourceVariable x, int y) => op_helper("sub", x, y);
+        public static ResourceVariable operator -(ResourceVariable x, float y) => op_helper("sub", x, y);
+        public static ResourceVariable operator -(ResourceVariable x, double y) => op_helper("sub", x, y);
+        public static ResourceVariable operator -(ResourceVariable x, Tensor y) => op_helper("sub", x, y);
+        public static ResourceVariable operator -(ResourceVariable x, ResourceVariable y) => op_helper("sub", x, y);
 
-        public static Tensor operator <(ResourceVariable x, Tensor y) => gen_math_ops.less(x.value(), y);
+        public static ResourceVariable operator *(ResourceVariable x, ResourceVariable y) => op_helper("mul", x, y);
+        public static ResourceVariable operator *(ResourceVariable x, NDArray y) => op_helper("mul", x, y);
 
-        public static Tensor operator >(ResourceVariable x, Tensor y) => gen_math_ops.greater(x.value(), y);
+        public static ResourceVariable operator <(ResourceVariable x, Tensor y) => less(x.value(), y);
 
-        private static Tensor op_helper<T>(string default_name, ResourceVariable x, T y)
+        public static ResourceVariable operator >(ResourceVariable x, Tensor y) => greater(x.value(), y);
+
+        private static ResourceVariable op_helper<T>(string default_name, ResourceVariable x, T y)
             => tf_with(ops.name_scope(null, default_name, new { x, y }), scope =>
             {
                 string name = scope;
@@ -64,7 +67,33 @@ namespace Tensorflow
 
                 // x.assign(result);
                 // result.ResourceVar = x;
-                return result;
+                return tf.Variable(result);
             });
+
+        private static ResourceVariable less<Tx, Ty>(Tx x, Ty y, string name = null)
+        {
+            if (tf.context.executing_eagerly())
+            {
+                var results = EagerTensorPass.Create();
+                var inputs = EagerTensorPass.From(x, y);
+                Status status = c_api.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "Less", name,
+                    inputs.Points, inputs.Length,
+                    null, null,
+                    results.Points, results.Length);
+                status.Check(true);
+                return tf.Variable(results[0].Resolve());
+            }
+
+            var _op = _op_def_lib._apply_op_helper("Less", name: name, args: new { x, y });
+
+            return tf.Variable(_op.outputs[0]);
+        }
+        private static ResourceVariable greater<Tx, Ty>(Tx x, Ty y, string name = null)
+        {
+            var _op = _op_def_lib._apply_op_helper("Greater", name: name, args: new { x, y });
+
+            return tf.Variable(_op.outputs[0]);
+        }
     }
 }
diff --git a/test/TensorFlowNET.UnitTest/Basics/VariableTest.cs b/test/TensorFlowNET.UnitTest/Basics/VariableTest.cs
index e41edb89..a6302655 100644
--- a/test/TensorFlowNET.UnitTest/Basics/VariableTest.cs
+++ b/test/TensorFlowNET.UnitTest/Basics/VariableTest.cs
@@ -56,10 +56,10 @@ namespace TensorFlowNET.UnitTest.Basics
         public void Accumulation()
         {
             var x = tf.Variable(10, name: "x");
-            /*for (int i = 0; i < 5; i++)
+            for (int i = 0; i < 5; i++)
                 x = x + 1;
 
-            Assert.AreEqual(15, (int)x.numpy());*/
+            Assert.AreEqual(15, (int)x.numpy());
         }
 
         [TestMethod]