fix result of session.run

src/TensorFlowNET.Core/Sessions/_ElementFetchMapper.cs

@@ -43,8 +43,23 @@ namespace Tensorflow
                     case NDArray value:
                         result = value;
                         break;
-                    case float fVal:
-                        result = fVal;
+                    case short value:
+                        result = value;
+                        break;
+                    case int value:
+                        result = value;
+                        break;
+                    case long value:
+                        result = value;
+                        break;
+                    case float value:
+                        result = value;
+                        break;
+                    case double value:
+                        result = value;
+                        break;
+                    case string value:
+                        result = value;
                         break;
                     default:
                         break;

src/TensorFlowNET.Core/Sessions/_FetchHandler.cs

@@ -58,11 +58,7 @@ namespace Tensorflow
                 {
                     var value = tensor_values[j];
                     j += 1;
-                    if (value.ndim == 2)
-                    {
-                        full_values.Add(value[0]);
-                    }
-                    else
+                    if (value.ndim == 0)
                     {
                         switch (value.dtype.Name)
                         {
@@ -75,8 +71,15 @@ namespace Tensorflow
                             case "Double":
                                 full_values.Add(value.Data<double>(0));
                                 break;
+                            case "String":
+                                full_values.Add(value.Data<string>(0));
+                                break;
                         }
                     }
+                    else
+                    {
+                        full_values.Add(value[np.arange(1)]);
+                    }
                 }
                 i += 1;
             }

test/TensorFlowNET.Examples/BasicEagerApi.cs

@@ -11,9 +11,11 @@ namespace TensorFlowNET.Examples
     /// </summary>
     public class BasicEagerApi : IExample
     {
+        public bool Enabled => false;
+
         private Tensor a, b, c, d;
 
-        public void Run()
+        public bool Run()
         {
             // Set Eager API
             Console.WriteLine("Setting Eager mode...");
@@ -34,6 +36,8 @@ namespace TensorFlowNET.Examples
             Console.WriteLine($"a * b = {d}");
 
             // Full compatibility with Numpy
+
+            return true;
         }
 
         public void PrepareData()

test/TensorFlowNET.Examples/BasicOperations.cs

@@ -10,11 +10,12 @@ namespace TensorFlowNET.Examples
     /// Basic Operations example using TensorFlow library.
     /// https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/1_Introduction/basic_operations.py
     /// </summary>
-    public class BasicOperations : IExample
+    public class BasicOperations : Python, IExample
     {
+        public bool Enabled => true;
         private Session sess;
 
-        public void Run()
+        public bool Run()
         {
             // Basic constant operations
             // The value returned by the constructor represents the output
@@ -86,15 +87,12 @@ namespace TensorFlowNET.Examples
             // graph: the two constants and matmul.
             //
             // The output of the op is returned in 'result' as a numpy `ndarray` object.
-            using (sess = tf.Session())
+            return with(tf.Session(), sess =>
             {
                 var result = sess.run(product);
                 Console.WriteLine(result.ToString()); // ==> [[ 12.]]
-                if (result.Data<int>()[0] != 12)
-                {
-                    throw new ValueError("BasicOperations");
-                }
-            }
+                return result.Data<int>()[0] == 12;
+            });
         }
 
         public void PrepareData()

test/TensorFlowNET.Examples/HelloWorld.cs

@@ -9,9 +9,10 @@ namespace TensorFlowNET.Examples
     /// Simple hello world using TensorFlow
     /// https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/1_Introduction/helloworld.py
     /// </summary>
-    public class HelloWorld : IExample
+    public class HelloWorld : Python, IExample
     {
-        public void Run()
+        public bool Enabled => true;
+        public bool Run()
         {
             /* Create a Constant op
                The op is added as a node to the default graph.
@@ -22,16 +23,13 @@ namespace TensorFlowNET.Examples
             var hello = tf.constant(str);
 
             // Start tf session
-            using (var sess = tf.Session())
+            return with(tf.Session(), sess =>
             {
                 // Run the op
                 var result = sess.run(hello);
                 Console.WriteLine(result.ToString());
-                if(!result.ToString().Equals(str))
-                {
-                    throw new ValueError("HelloWorld example acts in unexpected way.");
-                }
-            }
+                return result.ToString().Equals(str);
+            });
         }
 
         public void PrepareData()

test/TensorFlowNET.Examples/IExample.cs

@@ -10,7 +10,8 @@ namespace TensorFlowNET.Examples
     /// </summary>
     public interface IExample
     {
-        void Run();
+        bool Enabled { get; }
+        bool Run();
         void PrepareData();
     }
 }

test/TensorFlowNET.Examples/ImageRecognition.cs

@@ -12,12 +12,14 @@ namespace TensorFlowNET.Examples
 {
     public class ImageRecognition : Python, IExample
     {
+        public bool Enabled => true;
+
         string dir = "ImageRecognition";
         string pbFile = "tensorflow_inception_graph.pb";
         string labelFile = "imagenet_comp_graph_label_strings.txt";
         string picFile = "grace_hopper.jpg";
 
-        public void Run()
+        public bool Run()
         {
             PrepareData();
 
@@ -54,7 +56,10 @@ namespace TensorFlowNET.Examples
                 });
 
                 Console.WriteLine($"{picFile}: {labels[idx]} {propability}");
+                return labels[idx].Equals("military uniform");
             }
+
+            return false;
         }
 
         private NDArray ReadTensorFromImageFile(string file_name,

test/TensorFlowNET.Examples/InceptionArchGoogLeNet.cs

@@ -19,6 +19,7 @@ namespace TensorFlowNET.Examples
     /// </summary>
     public class InceptionArchGoogLeNet : Python, IExample
     {
+        public bool Enabled => false;
         string dir = "label_image_data";
         string pbFile = "inception_v3_2016_08_28_frozen.pb";
         string labelFile = "imagenet_slim_labels.txt";
@@ -30,7 +31,7 @@ namespace TensorFlowNET.Examples
         string input_name = "import/input";
         string output_name = "import/InceptionV3/Predictions/Reshape_1";
 
-        public void Run()
+        public bool Run()
         {
             PrepareData();
 
@@ -60,6 +61,8 @@ namespace TensorFlowNET.Examples
 
             foreach (float idx in top_k)
                 Console.WriteLine($"{picFile}: {idx} {labels[(int)idx]}, {results[(int)idx]}");
+
+            return true;
         }
 
         private NDArray ReadTensorFromImageFile(string file_name,

test/TensorFlowNET.Examples/LinearRegression.cs

@@ -12,6 +12,8 @@ namespace TensorFlowNET.Examples
     /// </summary>
     public class LinearRegression : Python, IExample
     {
+        public bool Enabled => true;
+
         NumPyRandom rng = np.random;
 
         // Parameters
@@ -22,7 +24,7 @@ namespace TensorFlowNET.Examples
         NDArray train_X, train_Y;
         int n_samples;
 
-        public void Run()
+        public bool Run()
         {
             // Training Data
             PrepareData();
@@ -52,7 +54,7 @@ namespace TensorFlowNET.Examples
             var init = tf.global_variables_initializer();
 
             // Start training
-            with(tf.Session(), sess => 
+            return with(tf.Session(), sess => 
             {
                 // Run the initializer
                 sess.run(init);
@@ -91,7 +93,10 @@ namespace TensorFlowNET.Examples
                     new FeedItem(X, test_X), 
                     new FeedItem(Y, test_Y));
                 Console.WriteLine($"Testing cost={testing_cost}");
-                Console.WriteLine($"Absolute mean square loss difference: {Math.Abs((float)training_cost - (float)testing_cost)}");
+                var diff = Math.Abs((float)training_cost - (float)testing_cost);
+                Console.WriteLine($"Absolute mean square loss difference: {diff}");
+
+                return diff < 0.01;
             });
         }
 

test/TensorFlowNET.Examples/LogisticRegression.cs

@@ -17,6 +17,7 @@ namespace TensorFlowNET.Examples
     /// </summary>
     public class LogisticRegression : Python, IExample
     {
+        public bool Enabled => true;
         private float learning_rate = 0.01f;
         private int training_epochs = 10;
         private int batch_size = 100;
@@ -24,7 +25,7 @@ namespace TensorFlowNET.Examples
 
         Datasets mnist;
 
-        public void Run()
+        public bool Run()
         {
             PrepareData();
 
@@ -48,7 +49,7 @@ namespace TensorFlowNET.Examples
             // Initialize the variables (i.e. assign their default value)
             var init = tf.global_variables_initializer();
 
-            with(tf.Session(), sess =>
+            return with(tf.Session(), sess =>
             {
                 
                 // Run the initializer
@@ -88,7 +89,7 @@ namespace TensorFlowNET.Examples
                 float acc = accuracy.eval(new FeedItem(x, mnist.test.images), new FeedItem(y, mnist.test.labels));
                 print($"Accuracy: {acc.ToString("F4")}");
 
-                Predict();
+                return acc > 0.9;
             });
         }
 

test/TensorFlowNET.Examples/MetaGraph.cs

@@ -9,9 +9,12 @@ namespace TensorFlowNET.Examples
 {
     public class MetaGraph : Python, IExample
     {
-        public void Run()
+        public bool Enabled => false;
+
+        public bool Run()
         {
             ImportMetaGraph("my-save-dir/");
+            return false;
         }
 
         private void ImportMetaGraph(string dir)

test/TensorFlowNET.Examples/NaiveBayesClassifier.cs

@@ -11,15 +11,17 @@ namespace TensorFlowNET.Examples
     /// https://github.com/nicolov/naive_bayes_tensorflow
     /// </summary>
     public class NaiveBayesClassifier : Python, IExample
-    { 
+    {
+        public bool Enabled => false;
         public Normal dist { get; set; }
-        public void Run()
+        public bool Run()
         {
             np.array(1.0f, 1.0f);
             var X = np.array(new float[][] { new float[] { 1.0f, 1.0f }, new float[] { 2.0f, 2.0f }, new float[] { -1.0f, -1.0f }, new float[] { -2.0f, -2.0f }, new float[] { 1.0f, -1.0f }, new float[] { 2.0f, -2.0f }, });
             var y = np.array(0,0,1,1,2,2);
             fit(X, y);
             // Create a regular grid and classify each point 
+            return false;
         }
 
         public void fit(NDArray X, NDArray y)

test/TensorFlowNET.Examples/NamedEntityRecognition.cs

@@ -10,7 +10,8 @@ namespace TensorFlowNET.Examples
     /// </summary>
     public class NamedEntityRecognition : Python, IExample
     {
-        public void Run()
+        public bool Enabled => false;
+        public bool Run()
         {
             throw new NotImplementedException();
         }

test/TensorFlowNET.Examples/Program.cs

@@ -1,6 +1,9 @@
 using System;
+using System.Collections.Generic;
+using System.Drawing;
 using System.Linq;
 using System.Reflection;
+using Console = Colorful.Console;
 
 namespace TensorFlowNET.Examples
 {
@@ -9,27 +12,41 @@ namespace TensorFlowNET.Examples
         static void Main(string[] args)
         {
             var assembly = Assembly.GetEntryAssembly();
-            foreach(Type type in assembly.GetTypes().Where(x => x.GetInterfaces().Contains(typeof(IExample))))
+            var errors = new List<string>();
+            var success = new List<string>();
+            var disabled = new List<string>();
+
+            foreach (Type type in assembly.GetTypes().Where(x => x.GetInterfaces().Contains(typeof(IExample))))
             {
                 if (args.Length > 0 && !args.Contains(type.Name))
                     continue;
 
-                Console.WriteLine($"{DateTime.UtcNow} Starting {type.Name}");
+                Console.WriteLine($"{DateTime.UtcNow} Starting {type.Name}", Color.Tan);
 
                 var example = (IExample)Activator.CreateInstance(type);
 
                 try
                 {
-                    example.Run();
+                    if (example.Enabled)
+                        if (example.Run())
+                            success.Add(type.Name);
+                        else
+                            errors.Add(type.Name);
+                    else
+                        disabled.Add(type.Name);
                 }
                 catch (Exception ex)
                 {
                     Console.WriteLine(ex);
                 }
 
-                Console.WriteLine($"{DateTime.UtcNow} Completed {type.Name}");
+                Console.WriteLine($"{DateTime.UtcNow} Completed {type.Name}", Color.Tan);
             }
 
+            success.ForEach(x => Console.WriteLine($"{x} example is OK!", Color.Green));
+            disabled.ForEach(x => Console.WriteLine($"{x} example is Disabled!", Color.Tan));
+            errors.ForEach(x => Console.WriteLine($"{x} example is Failed!", Color.Red));
+
             Console.ReadLine();
         }
     }

test/TensorFlowNET.Examples/TensorFlowNET.Examples.csproj

@@ -6,6 +6,7 @@
   </PropertyGroup>
 
   <ItemGroup>
+    <PackageReference Include="Colorful.Console" Version="1.2.9" />
     <PackageReference Include="Newtonsoft.Json" Version="12.0.1" />
     <PackageReference Include="NumSharp" Version="0.8.1" />
     <PackageReference Include="SharpZipLib" Version="1.1.0" />

test/TensorFlowNET.Examples/TextClassification/TextClassificationTrain.cs

@@ -15,13 +15,14 @@ namespace TensorFlowNET.Examples.CnnTextClassification
     /// </summary>
     public class TextClassificationTrain : Python, IExample
     {
+        public bool Enabled => false;
         private string dataDir = "text_classification";
         private string dataFileName = "dbpedia_csv.tar.gz";
 
         private const int CHAR_MAX_LEN = 1014;
         private const int NUM_CLASS = 2;
 
-        public void Run()
+        public bool Run()
         {
             PrepareData();
             Console.WriteLine("Building dataset...");
@@ -29,9 +30,10 @@ namespace TensorFlowNET.Examples.CnnTextClassification
 
             var (train_x, valid_x, train_y, valid_y) = train_test_split(x, y, test_size: 0.15f);
 
-            with(tf.Session(), sess =>
+            return with(tf.Session(), sess =>
             {
                 new VdCnn(alphabet_size, CHAR_MAX_LEN, NUM_CLASS);
+                return false;
             });
         }
 

test/TensorFlowNET.Examples/TextClassification/TextClassificationWithMovieReviews.cs

@@ -11,11 +11,12 @@ namespace TensorFlowNET.Examples
 {
     public class TextClassificationWithMovieReviews : Python, IExample
     {
+        public bool Enabled => false;
         string dir = "text_classification_with_movie_reviews";
         string dataFile = "imdb.zip";
         NDArray train_data, train_labels, test_data, test_labels;
 
-        public void Run()
+        public bool Run()
         {
             PrepareData();
 
@@ -39,6 +40,8 @@ namespace TensorFlowNET.Examples
 
             var model = keras.Sequential();
             model.add(keras.layers.Embedding(vocab_size, 16));
+
+            return false;
         }
 
         public void PrepareData()