upgrade NumSharp to v0.10.4.

src/TensorFlowNET.Core/Keras/BackendBase.cs

@@ -37,7 +37,7 @@ namespace Tensorflow.Keras
 
         public void set_floatx(TF_DataType floatx) => _FLOATX = floatx;
 
-        public NDArray cast_to_floatx(NDArray x) => np.array(x, dtype: _FLOATX.as_numpy_datatype());
+        //public NDArray cast_to_floatx(NDArray x) => np.array(x, dtype: _FLOATX.as_numpy_datatype());
 
         public ImageDataFormat image_data_format() => _IMAGE_DATA_FORMAT;
 

src/TensorFlowNET.Core/Sessions/_FetchMapper.cs

@@ -42,7 +42,7 @@ namespace Tensorflow
         {
             var type = values[0].GetType();
             var nd = new NDArray(type, values.Count);
-            nd.SetData(values.ToArray());
+            nd.ReplaceData(values.ToArray());
             return nd;
         }
 

src/TensorFlowNET.Core/TensorFlowNET.Core.csproj

@@ -5,7 +5,7 @@
     <AssemblyName>TensorFlow.NET</AssemblyName>
     <RootNamespace>Tensorflow</RootNamespace>
     <TargetTensorFlow>1.14.0</TargetTensorFlow>
-    <Version>0.10.0-alpha</Version>
+    <Version>0.10.0-beta</Version>
     <Authors>Haiping Chen, Meinrad Recheis</Authors>
     <Company>SciSharp STACK</Company>
     <GeneratePackageOnBuild>true</GeneratePackageOnBuild>
@@ -29,6 +29,8 @@ Learn more about .NET AI: https://medium.com/scisharp</Description>
     <FileVersion>0.10.0.0</FileVersion>
     <PackageLicenseFile>LICENSE</PackageLicenseFile>
     <PackageRequireLicenseAcceptance>false</PackageRequireLicenseAcceptance>
+    <SignAssembly>true</SignAssembly>
+    <AssemblyOriginatorKeyFile>Open.snk</AssemblyOriginatorKeyFile>
   </PropertyGroup>
 
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|AnyCPU'">
@@ -60,7 +62,7 @@ Learn more about .NET AI: https://medium.com/scisharp</Description>
 
   <ItemGroup>
     <PackageReference Include="Google.Protobuf" Version="3.9.0" />
-    <PackageReference Include="NumSharp" Version="0.10.3" />
+    <PackageReference Include="NumSharp" Version="0.10.4" />
     <PackageReference Include="SciSharp.TensorFlow.Redist" Version="1.14.0" />
   </ItemGroup>
 
@@ -68,11 +70,4 @@ Learn more about .NET AI: https://medium.com/scisharp</Description>
     <Folder Include="Distribute\" />
     <Folder Include="Keras\Initializers\" />
   </ItemGroup>
-
-  <ItemGroup>
-    <Reference Include="NumSharp.Core">
-      <HintPath>..\..\..\..\NumSharp\src\NumSharp.Core\bin\Debug\netstandard2.0\NumSharp.Core.dll</HintPath>
-    </Reference>
-  </ItemGroup>
-
 </Project>

src/TensorFlowNET.Core/Tensors/TensorShape.cs

@@ -16,7 +16,7 @@ namespace Tensorflow
         {
             if (proto.UnknownRank) return;
 
-            ReShape(proto.Dim.Select(x => (int)x.Size).ToArray());
+            Reshape(proto.Dim.Select(x => (int)x.Size).ToArray());
         }
 
         public TensorShape(params int[] dims) : base(dims)

test/TensorFlowNET.Examples/ImageProcessing/DigitRecognitionRNN.cs

@@ -30,7 +30,7 @@ namespace TensorFlowNET.Examples.ImageProcess
     /// </summary>
     public class DigitRecognitionRNN : IExample
     {
-        public bool Enabled { get; set; } = true;
+        public bool Enabled { get; set; } = false;
         public bool IsImportingGraph { get; set; } = false;
 
         public string Name => "MNIST RNN";

test/TensorFlowNET.UnitTest/PythonTest.cs

@@ -42,7 +42,7 @@ namespace TensorFlowNET.UnitTest
             for (int i = 0; i < e.Length; i++)
             {
                 if (g[i] is NDArray && e[i] is NDArray)
-                    assertItemsEqual((g[i] as NDArray).Array, (e[i] as NDArray).Array);
+                    assertItemsEqual((g[i] as NDArray).GetData<object>(), (e[i] as NDArray).GetData<object>());
                 else if (e[i] is ICollection && g[i] is ICollection)
                     assertEqual(g[i], e[i]);
                 else
@@ -60,7 +60,7 @@ namespace TensorFlowNET.UnitTest
         {
             if (given is NDArray && expected is NDArray)
             {
-                assertItemsEqual((given as NDArray).Array, (expected as NDArray).Array);
+                assertItemsEqual((given as NDArray).GetData<object>(), (expected as NDArray).GetData<object>());
                 return;
             }
             if (given is Hashtable && expected is Hashtable)