Change to NumSharp compact version.

src/TensorFlowNET.Core/Operations/random_ops.cs

@@ -80,7 +80,7 @@ namespace Tensorflow
         }
 
         public static Tensor random_uniform(Tensor shape,
-            long minval = 0,
+            int minval = 0,
             Tensor maxval = null,
             TF_DataType dtype = TF_DataType.TF_FLOAT,
             int? seed = null,

src/TensorFlowNET.Core/Sessions/_ElementFetchMapper.cs

@@ -58,51 +58,18 @@ namespace Tensorflow
                     case NDArray value:
                         result = new[] { value };
                         break;
-#if _REGEN
-        %types=["sbyte", "bool", "byte", "short", "ushort", "int", "uint", "long", "ulong", "float", "double", "Complex"]
-        %foreach types%
-                    case #1 value:
-                        result = new[] { NDArray.Scalar(value) };
-                        break;
-         %
-#else
-                    case sbyte value:
-                        result = new[] { NDArray.Scalar(value) };
-                        break;
                     case bool value:
                         result = new[] { NDArray.Scalar(value) };
                         break;
                     case byte value:
                         result = new[] { NDArray.Scalar(value) };
                         break;
-                    case short value:
-                        result = new[] { NDArray.Scalar(value) };
-                        break;
-                    case ushort value:
-                        result = new[] { NDArray.Scalar(value) };
-                        break;
                     case int value:
                         result = new[] { NDArray.Scalar(value) };
                         break;
-                    case uint value:
-                        result = new[] { NDArray.Scalar(value) };
-                        break;
-                    case long value:
-                        result = new[] { NDArray.Scalar(value) };
-                        break;
-                    case ulong value:
-                        result = new[] { NDArray.Scalar(value) };
-                        break;
                     case float value:
                         result = new[] { NDArray.Scalar(value) };
                         break;
-                    case double value:
-                        result = new[] { NDArray.Scalar(value) };
-                        break;
-                    case Complex value:
-                        result = new[] { NDArray.Scalar(value) };
-                        break;
-#endif
                     default:
                         break;
                 }

src/TensorFlowNET.Core/TensorFlow.Binding.csproj

@@ -60,7 +60,7 @@ https://tensorflownet.readthedocs.io</Description>
 
   <ItemGroup>
     <PackageReference Include="Google.Protobuf" Version="3.11.2" />
-    <PackageReference Include="NumSharp" Version="0.20.5" />
+    <PackageReference Include="NumSharp" Version="0.30.0-alpha" />
   </ItemGroup>
 
   <ItemGroup>

src/TensorFlowNET.Hub/MnistModelLoader.cs

@@ -116,7 +116,7 @@ namespace Tensorflow.Hub
                     throw new Exception($"Invalid magic number {magic} in MNIST image file: {file}");
                 
                 var num_images =  Read32(bytestream);
-                num_images = limit == null ? num_images : Math.Min(num_images, (uint)limit);
+                num_images = limit == null ? num_images : Math.Min(num_images, (int)limit);
 
                 var rows = Read32(bytestream);
                 var cols = Read32(bytestream);
@@ -125,8 +125,8 @@ namespace Tensorflow.Hub
 
                 bytestream.Read(buf, 0, buf.Length);
 
-                var data = np.frombuffer(buf, np.uint8);
-                data = data.reshape((int)num_images, (int)rows, (int)cols, 1);
+                var data = np.frombuffer(buf, np.@byte);
+                data = data.reshape(num_images, rows, cols, 1);
 
                 return data;
             }
@@ -144,7 +144,7 @@ namespace Tensorflow.Hub
                     throw new Exception($"Invalid magic number {magic} in MNIST label file: {file}");
                 
                 var num_items = Read32(bytestream);
-                num_items = limit == null ? num_items : Math.Min(num_items, (uint)limit);
+                num_items = limit == null ? num_items : Math.Min(num_items, (int)limit);
                 
                 var buf = new byte[num_items];
 
@@ -174,11 +174,11 @@ namespace Tensorflow.Hub
             return labels_one_hot;
         }
 
-        private uint Read32(FileStream bytestream)
+        private int Read32(FileStream bytestream)
         {
             var buffer = new byte[sizeof(uint)];
             var count = bytestream.Read(buffer, 0, 4);
-            return np.frombuffer(buffer, ">u4").Data<uint>()[0];
+            return np.frombuffer(buffer, ">u4").Data<int>()[0];
         }
     }
 }

src/TensorFlowNET.Hub/Tensorflow.Hub.csproj

@@ -2,7 +2,7 @@
   <PropertyGroup>
     <RootNamespace>Tensorflow.Hub</RootNamespace>
     <TargetFramework>netstandard2.0</TargetFramework>
-    <Version>0.0.5</Version>
+    <Version>0.0.6</Version>
     <Authors>Kerry Jiang, Haiping Chen</Authors>
     <Company>SciSharp STACK</Company>
     <Copyright>Apache 2.0</Copyright>
@@ -13,7 +13,8 @@
     <Description>TensorFlow Hub is a library to foster the publication, discovery, and consumption of reusable parts of machine learning models.</Description>
     <PackageId>SciSharp.TensorFlowHub</PackageId>
     <GeneratePackageOnBuild>true</GeneratePackageOnBuild>
-    <PackageReleaseNotes>Fix GetNextBatch() bug.</PackageReleaseNotes>
+    <PackageReleaseNotes>Fix GetNextBatch() bug.
+Change to NumSharp compact version.</PackageReleaseNotes>
     <PackageIconUrl>https://avatars3.githubusercontent.com/u/44989469?s=200&amp;v=4</PackageIconUrl>
     <AssemblyName>TensorFlow.Hub</AssemblyName>
   </PropertyGroup>
@@ -21,6 +22,6 @@
     <DefineConstants>DEBUG;TRACE</DefineConstants>
   </PropertyGroup>
   <ItemGroup>
-    <PackageReference Include="NumSharp" Version="0.20.5" />
+    <PackageReference Include="NumSharp" Version="0.30.0-alpha" />
   </ItemGroup>
 </Project>