unified the incoming parameter of the _FetchMapper as NDArray.

README.md

@@ -1,5 +1,5 @@
 # TensorFlow.NET
-TensorFlow.NET provides a .NET Standard binding for [TensorFlow](https://www.tensorflow.org/). It aims to implement the complete Tensorflow API in CSharp which allows .NET developers to develop, train and deploy Machine Learning models with the cross-platform .NET Standard framework. 
+TensorFlow.NET (TF.NET) provides a .NET Standard binding for [TensorFlow](https://www.tensorflow.org/). It aims to implement the complete Tensorflow API in CSharp which allows .NET developers to develop, train and deploy Machine Learning models with the cross-platform .NET Standard framework. 
 
 [![Join the chat at https://gitter.im/publiclab/publiclab](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/sci-sharp/community)
 [![Tensorflow.NET](https://ci.appveyor.com/api/projects/status/wx4td43v2d3f2xj6?svg=true)](https://ci.appveyor.com/project/Haiping-Chen/tensorflow-net)
@@ -8,7 +8,7 @@ TensorFlow.NET provides a .NET Standard binding for [TensorFlow](https://www.ten
 [![Documentation Status](https://readthedocs.org/projects/tensorflownet/badge/?version=latest)](https://tensorflownet.readthedocs.io/en/latest/?badge=latest)
 [![Badge](https://img.shields.io/badge/link-996.icu-red.svg)](https://996.icu/#/en_US)
 
-TensorFlow.NET is a member project of [SciSharp STACK](https://github.com/SciSharp).
+TF.NET is a member project of [SciSharp STACK](https://github.com/SciSharp).
 
 ![tensors_flowing](docs/assets/tensors_flowing.gif)
 
@@ -24,14 +24,14 @@ In comparison to other projects, like for instance TensorFlowSharp which only pr
 
 ### How to use
 
-Install TensorFlow.NET through NuGet.
+Install TF.NET through NuGet.
 ```sh
 PM> Install-Package TensorFlow.NET
 ```
 
 If you are using Linux or Mac OS, please download the pre-compiled dll [here](tensorflowlib) and place it in the working folder. This is only need for Linux and Mac OS, and already packed into NuGet for Windows.
 
-Import tensorflow.net.
+Import TF.NET.
 
 ```cs
 using Tensorflow;

src/TensorFlowNET.Core/Sessions/_ElementFetchMapper.cs

@@ -10,9 +10,9 @@ namespace Tensorflow
     /// </summary>
     public class _ElementFetchMapper : _FetchMapper
     {
-        private Func<List<object>, object> _contraction_fn;
+        private Func<List<NDArray>, object> _contraction_fn;
 
-        public _ElementFetchMapper(object[] fetches, Func<List<object>, object> contraction_fn)
+        public _ElementFetchMapper(object[] fetches, Func<List<NDArray>, object> contraction_fn)
         {
             var g = ops.get_default_graph();
             ITensorOrOperation el = null;
@@ -31,7 +31,7 @@ namespace Tensorflow
         /// </summary>
         /// <param name="values"></param>
         /// <returns></returns>
-        public override NDArray build_results(List<object> values)
+        public override NDArray build_results(List<NDArray> values)
         {
             NDArray result = null;
 

src/TensorFlowNET.Core/Sessions/_FetchHandler.cs

@@ -42,7 +42,7 @@ namespace Tensorflow
 
         public NDArray build_results(BaseSession session, NDArray[] tensor_values)
         {
-            var full_values = new List<object>();
+            var full_values = new List<NDArray>();
             if (_final_fetches.Count != tensor_values.Length)
                 throw new InvalidOperationException("_final_fetches mismatch tensor_values");
 

src/TensorFlowNET.Core/Sessions/_FetchMapper.cs

@@ -17,21 +17,14 @@ namespace Tensorflow
             if (fetch.GetType().IsArray)
                 return new _ListFetchMapper(fetches);
             else
-                return new _ElementFetchMapper(fetches, (List<object> fetched_vals) => fetched_vals[0]);
+                return new _ElementFetchMapper(fetches, (List<NDArray> fetched_vals) => fetched_vals[0]);
         }
 
-        public virtual NDArray build_results(List<object> values)
+        public virtual NDArray build_results(List<NDArray> values)
         {
             var type = values[0].GetType();
             var nd = new NDArray(type, values.Count);
-
-            switch (type.Name)
-            {
-                case "Single":
-                    nd.SetData(values.Select(x => (float)x).ToArray());
-                    break;
-            }
-
+            nd.SetData(values.ToArray());
             return nd;
         }
 

test/TensorFlowNET.Examples/KMeansClustering.cs

@@ -62,10 +62,23 @@ namespace TensorFlowNET.Examples
                 sess.run(init_op, new FeedItem(X, full_data_x));
 
                 // Training
+                NDArray result = null;
                 foreach(var i in range(1, num_steps + 1))
                 {
-                    var result = sess.run(new Tensor[] { avg_distance, cluster_idx }, new FeedItem(X, full_data_x));
+                    result = sess.run(new ITensorOrOperation[] { train_op, avg_distance, cluster_idx }, new FeedItem(X, full_data_x));
+                    if (i % 2 == 0 || i == 1)
+                        print($"Step {i}, Avg Distance: {result[1]}");
                 }
+
+                var idx = result[2];
+
+                // Assign a label to each centroid
+                // Count total number of labels per centroid, using the label of each training
+                // sample to their closest centroid (given by 'idx')
+                var counts = np.zeros(k, num_classes);
+                foreach (var i in range(idx.len))
+                    counts[idx[i]] += mnist.train.labels[i];
+
             });
 
             return false;