add variables.data file.

src/TensorFlowNET.Core/TensorFlowNET.Core.csproj

@@ -8,7 +8,7 @@
     <Version>0.8.0</Version>
     <Authors>Haiping Chen</Authors>
     <Company>SciSharp STACK</Company>
-    <GeneratePackageOnBuild>false</GeneratePackageOnBuild>
+    <GeneratePackageOnBuild>true</GeneratePackageOnBuild>
     <Copyright>Apache 2.0</Copyright>
     <RepositoryUrl>https://github.com/SciSharp/TensorFlow.NET</RepositoryUrl>
     <RepositoryType>git</RepositoryType>
@@ -49,7 +49,7 @@ Add Word2Vec example.</PackageReleaseNotes>
 
   <ItemGroup>
     <PackageReference Include="Google.Protobuf" Version="3.7.0" />
-    <PackageReference Include="NumSharp" Version="0.10.1" />
+    <PackageReference Include="NumSharp" Version="0.10.2" />
   </ItemGroup>
 
   <ItemGroup>

test/TensorFlowNET.Examples/ImageProcess/RetrainImageClassifier.cs

@@ -25,7 +25,7 @@ namespace TensorFlowNET.Examples.ImageProcess
     {
         public int Priority => 16;
 
-        public bool Enabled { get; set; } = false;
+        public bool Enabled { get; set; } = true;
         public bool ImportGraph { get; set; } = true;
 
         public string Name => "Retrain Image Classifier";
@@ -76,14 +76,6 @@ namespace TensorFlowNET.Examples.ImageProcess
                      wants_quantization, is_training: true);
             });
 
-            /*Tensor bottleneck_tensor = graph.OperationByName("module_apply_default/hub_output/feature_vector/SpatialSqueeze");
-            Tensor resized_image_tensor = graph.OperationByName("Placeholder");
-            Tensor final_tensor = graph.OperationByName(final_tensor_name);
-            Tensor ground_truth_input = graph.OperationByName("input/GroundTruthInput");
-            train_step = graph.OperationByName("train/GradientDescent");
-            Tensor bottleneck_input = graph.OperationByName("input/BottleneckInputPlaceholder");
-            Tensor cross_entropy = graph.OperationByName("cross_entropy/sparse_softmax_cross_entropy_loss/value");*/
-
             var sw = new Stopwatch();
 
             return with(tf.Session(graph), sess =>
@@ -485,7 +477,7 @@ namespace TensorFlowNET.Examples.ImageProcess
                             bottleneck_dir, jpeg_data_tensor, decoded_image_tensor,
                             resized_input_tensor, bottleneck_tensor, module_name);
                         how_many_bottlenecks++;
-                        if (how_many_bottlenecks % 100 == 0)
+                        if (how_many_bottlenecks % 300 == 0)
                             print($"{how_many_bottlenecks} bottleneck files created.");
                     }
                 }
@@ -609,6 +601,11 @@ namespace TensorFlowNET.Examples.ImageProcess
             url = "https://raw.githubusercontent.com/SciSharp/TensorFlow.NET/master/graph/InceptionV3.meta";
             Web.Download(url, "graph", "InceptionV3.meta");
 
+            // download variables.data checkpoint file.
+            url = "https://github.com/SciSharp/TensorFlow.NET/raw/master/data/tfhub_modules.zip";
+            Web.Download(url, data_dir, "tfhub_modules.zip");
+            Compress.UnZip(Path.Join(data_dir, "tfhub_modules.zip"), Path.Join(Path.GetTempPath(), "tfhub_modules"));
+
             // Prepare necessary directories that can be used during training
             Directory.CreateDirectory(summaries_dir);
             Directory.CreateDirectory(bottleneck_dir);