add tf.convert_to_tensor

TensorFlow.NET.sln

@@ -9,8 +9,6 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "TensorFlowNET.Examples", "t
 EndProject
 Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "TensorFlowNET.Core", "src\TensorFlowNET.Core\TensorFlowNET.Core.csproj", "{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}"
 EndProject
-Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "NumSharp.Core", "..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj", "{DE97EAD7-B92C-4112-9690-91C40A97179E}"
-EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution
 		Debug|Any CPU = Debug|Any CPU
@@ -29,10 +27,6 @@ Global
 		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Debug|Any CPU.Build.0 = Debug|Any CPU
 		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Release|Any CPU.ActiveCfg = Release|Any CPU
 		{FD682AC0-7B2D-45D3-8B0D-C6D678B04144}.Release|Any CPU.Build.0 = Release|Any CPU
-		{DE97EAD7-B92C-4112-9690-91C40A97179E}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
-		{DE97EAD7-B92C-4112-9690-91C40A97179E}.Debug|Any CPU.Build.0 = Debug|Any CPU
-		{DE97EAD7-B92C-4112-9690-91C40A97179E}.Release|Any CPU.ActiveCfg = Release|Any CPU
-		{DE97EAD7-B92C-4112-9690-91C40A97179E}.Release|Any CPU.Build.0 = Release|Any CPU
 	EndGlobalSection
 	GlobalSection(SolutionProperties) = preSolution
 		HideSolutionNode = FALSE

src/TensorFlowNET.Core/APIs/tf.tensor.cs

@@ -0,0 +1,13 @@
+using NumSharp;
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow
+{
+    public static partial class tf
+    {
+        public static Tensor convert_to_tensor(object value,
+            string name = null) => ops.convert_to_tensor(value, name: name);
+    }
+}

src/TensorFlowNET.Core/Python.cs

@@ -29,7 +29,7 @@ namespace Tensorflow
 
         protected IEnumerable<int> range(int start, int end)
         {
-            return Enumerable.Range(start, end);
+            return Enumerable.Range(start, end - start);
         }
 
         public static T New<T>(object args) where T : IPyClass

src/TensorFlowNET.Core/TensorFlowNET.Core.csproj

@@ -4,10 +4,10 @@
     <TargetFramework>netstandard2.0</TargetFramework>
     <AssemblyName>TensorFlow.NET</AssemblyName>
     <RootNamespace>Tensorflow</RootNamespace>
-    <Version>0.6.1-alpha</Version>
+    <Version>0.6.1</Version>
     <Authors>Haiping Chen</Authors>
     <Company>SciSharp STACK</Company>
-    <GeneratePackageOnBuild>true</GeneratePackageOnBuild>
+    <GeneratePackageOnBuild>false</GeneratePackageOnBuild>
     <Copyright>Apache 2.0</Copyright>
     <RepositoryUrl>https://github.com/SciSharp/TensorFlow.NET</RepositoryUrl>
     <RepositoryType>git</RepositoryType>
@@ -44,7 +44,7 @@ More math/ linalg APIs.</PackageReleaseNotes>
 
   <ItemGroup>
     <PackageReference Include="Google.Protobuf" Version="3.7.0" />
-    <PackageReference Include="NumSharp" Version="0.9.0" />
+    <PackageReference Include="NumSharp" Version="0.10.0-alpha" />
   </ItemGroup>
 
   <ItemGroup>
@@ -57,8 +57,4 @@ More math/ linalg APIs.</PackageReleaseNotes>
     <Folder Include="Keras\Initializers\" />
   </ItemGroup>
 
-  <ItemGroup>
-    <ProjectReference Include="..\..\..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj" />
-  </ItemGroup>
-
 </Project>

test/TensorFlowNET.Examples/KMeansClustering.cs

@@ -1,6 +1,8 @@
 using NumSharp;
 using System;
 using System.Collections.Generic;
+using System.Diagnostics;
+using System.Linq;
 using System.Text;
 using Tensorflow;
 using Tensorflow.Clustering;
@@ -26,7 +28,7 @@ namespace TensorFlowNET.Examples
 
         Datasets mnist;
         NDArray full_data_x;
-        int num_steps = 50; // Total steps to train
+        int num_steps = 10; // Total steps to train
         int k = 25; // The number of clusters
         int num_classes = 10; // The 10 digits
         int num_features = 784; // Each image is 28x28 pixels
@@ -63,22 +65,43 @@ namespace TensorFlowNET.Examples
 
                 // Training
                 NDArray result = null;
-                foreach(var i in range(1, num_steps + 1))
+                var sw = new Stopwatch();
+
+                foreach (var i in range(1, num_steps + 1))
                 {
+                    sw.Start();
                     result = sess.run(new ITensorOrOperation[] { train_op, avg_distance, cluster_idx }, new FeedItem(X, full_data_x));
-                    if (i % 2 == 0 || i == 1)
-                        print($"Step {i}, Avg Distance: {result[1]}");
+                    sw.Stop();
+
+                    if (i % 5 == 0 || i == 1)
+                        print($"Step {i}, Avg Distance: {result[1]} Elapse: {sw.ElapsedMilliseconds}ms");
+
+                    sw.Reset();
                 }
 
-                var idx = result[2];
+                var idx = result[2].Data<int>();
 
                 // 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];
+                var counts = np.zeros((k, num_classes), np.float32);
+
+                sw.Start();
+                foreach (var i in range(idx.Length))
+                {
+                    var x = mnist.train.labels[i];
+                    counts[idx[i]] += x;
+                }
+                    
+                sw.Stop();
+                print($"Assign a label to each centroid took {sw.ElapsedMilliseconds}ms");
+
+                // Assign the most frequent label to the centroid
+                var labels_map_array = np.argmax(counts, 1);
+                var labels_map = tf.convert_to_tensor(labels_map_array);
 
+                // Evaluation ops
+                // Lookup: centroid_id -> label
             });
 
             return false;

test/TensorFlowNET.Examples/LogisticRegression.cs

@@ -88,7 +88,7 @@ namespace TensorFlowNET.Examples
 
                     // Display logs per epoch step
                     if ((epoch + 1) % display_step == 0)
-                        print($"Epoch: {(epoch + 1).ToString("D4")} cost= {avg_cost.ToString("G9")} elapse= {sw.ElapsedMilliseconds}ms");
+                        print($"Epoch: {(epoch + 1).ToString("D4")} Cost: {avg_cost.ToString("G9")} Elapse: {sw.ElapsedMilliseconds}ms");
 
                     sw.Reset();
                 }

test/TensorFlowNET.Examples/NearestNeighbor.cs

@@ -51,9 +51,9 @@ namespace TensorFlowNET.Examples
                     long nn_index = sess.run(pred, new FeedItem(xtr, Xtr), new FeedItem(xte, Xte[i]));
                     // Get nearest neighbor class label and compare it to its true label
                     int index = (int)nn_index;
-                    print($"Test {i} Prediction: {np.argmax(Ytr[(NDArray)index])} True Class: {np.argmax(Yte[i] as NDArray)}");
+                    print($"Test {i} Prediction: {np.argmax(Ytr[index])} True Class: {np.argmax(Yte[i])}");
                     // Calculate accuracy
-                    if (np.argmax(Ytr[(NDArray)index]) == np.argmax(Yte[i] as NDArray))
+                    if ((int)np.argmax(Ytr[index]) == (int)np.argmax(Yte[i]))
                         accuracy += 1f/ Xte.shape[0];
                 }
 

test/TensorFlowNET.Examples/TensorFlowNET.Examples.csproj

@@ -2,19 +2,18 @@
 
   <PropertyGroup>
     <OutputType>Exe</OutputType>
-    <TargetFramework>netcoreapp2.1</TargetFramework>
+    <TargetFramework>netcoreapp2.2</TargetFramework>
     <GeneratePackageOnBuild>false</GeneratePackageOnBuild>
   </PropertyGroup>
 
   <ItemGroup>
     <PackageReference Include="Colorful.Console" Version="1.2.9" />
-    <PackageReference Include="Newtonsoft.Json" Version="12.0.1" />
+    <PackageReference Include="Newtonsoft.Json" Version="12.0.2" />
     <PackageReference Include="SharpZipLib" Version="1.1.0" />
     <PackageReference Include="System.Drawing.Common" Version="4.5.1" />
   </ItemGroup>
 
   <ItemGroup>
-    <ProjectReference Include="..\..\..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj" />
     <ProjectReference Include="..\..\src\TensorFlowNET.Core\TensorFlowNET.Core.csproj" />
   </ItemGroup>
 

test/TensorFlowNET.UnitTest/TensorFlowNET.UnitTest.csproj

@@ -1,7 +1,7 @@
-<Project Sdk="Microsoft.NET.Sdk">
+<Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <TargetFramework>netcoreapp2.1</TargetFramework>
+    <TargetFramework>netcoreapp2.2</TargetFramework>
 
     <IsPackable>false</IsPackable>
   </PropertyGroup>
@@ -22,7 +22,6 @@
   </ItemGroup>
 
   <ItemGroup>
-    <ProjectReference Include="..\..\..\NumSharp\src\NumSharp.Core\NumSharp.Core.csproj" />
     <ProjectReference Include="..\..\src\TensorFlowNET.Core\TensorFlowNET.Core.csproj" />
     <ProjectReference Include="..\TensorFlowNET.Examples\TensorFlowNET.Examples.csproj" />
   </ItemGroup>