From 365962f5ca087d849255b6f96792483b5315c32a Mon Sep 17 00:00:00 2001
From: Meinrad Recheis <meinrad.recheis@gmail.com>
Date: Fri, 19 Apr 2019 15:15:51 +0200
Subject: [PATCH] NN XOR port complete, but fails

---
 test/TensorFlowNET.Examples/NeuralNetXor.cs   | 49 ++++++++++++-------
 .../ExamplesTests/ExamplesTest.cs             |  2 +-
 2 files changed, 31 insertions(+), 20 deletions(-)

diff --git a/test/TensorFlowNET.Examples/NeuralNetXor.cs b/test/TensorFlowNET.Examples/NeuralNetXor.cs
index eea081e0..42911aad 100644
--- a/test/TensorFlowNET.Examples/NeuralNetXor.cs
+++ b/test/TensorFlowNET.Examples/NeuralNetXor.cs
@@ -59,29 +59,40 @@ namespace TensorFlowNET.Examples
             with(tf.Session(graph), sess =>
             {
                 init.run();
-                var step = 0;
-                var xy = np.array(new bool[,]
+                var step = 0;
+                //TODO: make the type conversion and jagged array initializer work with numpy
+                //var xy = np.array(new bool[,]
+                //{
+                //    {true, false},
+                //    {true, true },
+                //    {false, false },
+                //    {false, true},
+                //}, dtype: np.float32);
+                var xy = np.array(new float[]
                 {
-                    {true, false},
-                    {true, true },
-                    {false, false },
-                    {false, true},
-                }, dtype: np.float32);
-
-                var y_ = np.array(new[] {true, false, false, true}, dtype: np.int32);
+                    1, 0,
+                    1, 1,
+                    0, 0,
+                    0, 1
+                }, np.float32).reshape(4,2);
+                
+
+                //var y_ = np.array(new[] {true, false, false, true}, dtype: np.int32);
+                var y_ = np.array(new int[] { 1, 0, 0, 1 }, dtype: np.int32);
+                NDArray loss_value=null;
                 while (step < num_steps)
-                {
-                    // original python:
-                    //_, step, loss_value = sess.run(
-                    //          [train_op, gs, loss],
-                    //          feed_dict={features: xy, labels: y_}
+                {
+                    // original python:
+                    //_, step, loss_value = sess.run(
+                    //          [train_op, gs, loss],
+                    //          feed_dict={features: xy, labels: y_}
                     //      )
-                    // TODO: how the hell to port that to c#?
-                    //  var ( _, step, loss_value) = sess.run(new object[] {train_op, gs, loss},feed_dict: new {"features": xy, "labels": y_});
+                    loss_value = sess.run(loss, new FeedItem(features, xy), new FeedItem(labels, y_));
+                    step++;
+                    if (step%1000==0)
+                        Console.WriteLine($"Step {0} loss: {loss_value[0]}");
                 }
-                //tf.logging.info('Final loss is: {}'.format(loss_value))
-                //Console.WriteLine($"Final loss is: {loss_value}");
-
+                Console.WriteLine($"Final loss: {loss_value[0]}");
             });
             return true;
         }
diff --git a/test/TensorFlowNET.UnitTest/ExamplesTests/ExamplesTest.cs b/test/TensorFlowNET.UnitTest/ExamplesTests/ExamplesTest.cs
index b0af5125..e0174c56 100644
--- a/test/TensorFlowNET.UnitTest/ExamplesTests/ExamplesTest.cs
+++ b/test/TensorFlowNET.UnitTest/ExamplesTests/ExamplesTest.cs
@@ -109,7 +109,7 @@ namespace TensorFlowNET.ExamplesTests
             new TextClassificationWithMovieReviews() { Enabled = true }.Run();
         }
 
-        [Ignore]
+        [Ignore("Attempting to use uninitialized value Variable_1")]
         [TestMethod]
         public void NeuralNetXor()
         {