Xor is working without imported graph!

test/TensorFlowNET.Examples/NeuralNetXor.cs

@@ -16,13 +16,13 @@ namespace TensorFlowNET.Examples
         public int Priority => 10;
         public bool Enabled { get; set; } = true;
         public string Name => "NN XOR";
-        public bool ImportGraph { get; set; } = true;
+        public bool ImportGraph { get; set; } = false;
 
         public int num_steps = 5000;
 
         private NDArray data;
 
-        private (Operation, Tensor, RefVariable) make_graph(Tensor features,Tensor labels, int num_hidden = 8)
+        private (Operation, Tensor, Tensor) make_graph(Tensor features,Tensor labels, int num_hidden = 8)
         {
             var stddev = 1 / Math.Sqrt(2);
             var hidden_weights = tf.Variable(tf.truncated_normal(new int []{2, num_hidden}, stddev: (float) stddev ));
@@ -69,6 +69,8 @@ namespace TensorFlowNET.Examples
             Tensor features = graph.get_operation_by_name("Placeholder");
             Tensor labels = graph.get_operation_by_name("Placeholder_1");
             Tensor loss = graph.get_operation_by_name("loss");
+            Tensor train_op = graph.get_operation_by_name("train_op");
+            Tensor global_step = graph.get_operation_by_name("global_step");
 
             var init = tf.global_variables_initializer();
             float loss_value = 0;
@@ -86,7 +88,8 @@ namespace TensorFlowNET.Examples
                     //          [train_op, gs, loss],
                     //          feed_dict={features: xy, labels: y_}
                     //      )
-                    loss_value = sess.run(loss, new FeedItem(features, data), new FeedItem(labels, y_));
+                    var result = sess.run(new ITensorOrOperation[] { train_op, global_step, loss }, new FeedItem(features, data), new FeedItem(labels, y_));
+                    loss_value = result[2];
                     step++;
                     if (step % 1000 == 0)
                         Console.WriteLine($"Step {step} loss: {loss_value}");
@@ -122,7 +125,9 @@ namespace TensorFlowNET.Examples
                     //          [train_op, gs, loss],
                     //          feed_dict={features: xy, labels: y_}
                     //      )
-                    loss_value = sess.run(loss, new FeedItem(features, data), new FeedItem(labels, y_));
+                    var result = sess.run(new ITensorOrOperation[] { train_op, gs, loss }, new FeedItem(features, data), new FeedItem(labels, y_));
+                    loss_value = result[2];
+                    //step = result[1];
                     step++;
                     if (step % 1000 == 0)
                         Console.WriteLine($"Step {step} loss: {loss_value}");