Make Graph inherits from DisposableObject.

src/TensorFlowHub/TensorFlowHub.csproj

@@ -2,7 +2,7 @@
   <PropertyGroup>
     <RootNamespace>Tensorflow.Hub</RootNamespace>
     <TargetFramework>netstandard2.0</TargetFramework>
-    <Version>0.0.1</Version>
+    <Version>0.0.2</Version>
     <Authors>Kerry Jiang</Authors>
     <Company>SciSharp STACK</Company>
     <Copyright>Apache 2.0</Copyright>
@@ -13,7 +13,7 @@
     <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>1. Add MNIST loader.</PackageReleaseNotes>
+    <PackageReleaseNotes></PackageReleaseNotes>
     <PackageIconUrl>https://avatars3.githubusercontent.com/u/44989469?s=200&amp;v=4</PackageIconUrl>
   </PropertyGroup>
   <ItemGroup>

src/TensorFlowNET.Core/Graphs/DefaultGraphStack.cs

@@ -34,10 +34,17 @@ namespace Tensorflow
 
         public Graph get_controller()
         {
-            if (stack.Count == 0)
+            if (stack.Count(x => x.IsDefault) == 0)
                 stack.Add(new StackModel { Graph = tf.Graph(), IsDefault = true });
 
-            return stack.First(x => x.IsDefault).Graph;
+            return stack.Last(x => x.IsDefault).Graph;
+        }
+
+        public bool remove(Graph g)
+        {
+            var sm = stack.FirstOrDefault(x => x.Graph == g);
+            if (sm == null) return false;
+            return stack.Remove(sm);
         }
 
         public void reset()

src/TensorFlowNET.Core/Graphs/Graph.cs

@@ -73,9 +73,8 @@ namespace Tensorflow
         all variables that are created during the construction of a graph. The caller
         may define additional collections by specifying a new name.     
      */
-    public partial class Graph : IPython, IDisposable, IEnumerable<Operation>
+    public partial class Graph : DisposableObject, IEnumerable<Operation>
     {
-        private IntPtr _handle;
         private Dictionary<int, ITensorOrOperation> _nodes_by_id;
         public Dictionary<string, ITensorOrOperation> _nodes_by_name;
         private Dictionary<string, int> _names_in_use;
@@ -121,10 +120,6 @@ namespace Tensorflow
             _graph_key = $"grap-key-{ops.uid()}/";
         }
 
-        public void __enter__()
-        {
-        }
-
         public ITensorOrOperation as_graph_element(object obj, bool allow_tensor = true, bool allow_operation = true)
         {
             return _as_graph_element_locked(obj, allow_tensor, allow_operation);
@@ -443,14 +438,15 @@ namespace Tensorflow
             _unfetchable_ops.Add(op);
         }
 
-        public void Dispose()
-        {
-            /*if (_handle != IntPtr.Zero)
-                c_api.TF_DeleteGraph(_handle);
-
-            _handle = IntPtr.Zero;
-
-            GC.SuppressFinalize(this);*/
+        protected override void DisposeManagedState()
+        {
+            ops.default_graph_stack.remove(this);
+        }
+
+        protected override void DisposeUnManagedState(IntPtr handle)
+        {
+            Console.WriteLine($"Destroy graph {handle}");
+            c_api.TF_DeleteGraph(handle);
         }
 
         /// <summary>
@@ -481,17 +477,19 @@ namespace Tensorflow
             return new TensorShape(dims.Select(x => (int)x).ToArray());
         }
 
+        string debugString = string.Empty;
         public override string ToString()
         {
-            int len = 0;
-            return c_api.TF_GraphDebugString(_handle, out len);
+            return $"{graph_key}, ({_handle})"; 
+            /*if (string.IsNullOrEmpty(debugString))
+            {
+                int len = 0;
+                debugString = c_api.TF_GraphDebugString(_handle, out len);
+            }
+
+            return debugString;*/
         }
 
-        public void __exit__()
-        {
-
-        }
-
         private IEnumerable<Operation> GetEnumerable()
             => c_api_util.tf_operations(this);
 

src/TensorFlowNET.Core/Operations/Operation.cs

@@ -84,7 +84,7 @@ namespace Tensorflow
 
             // Dict mapping op name to file and line information for op colocation
             // context managers.
-            _control_flow_context = graph._get_control_flow_context();
+            _control_flow_context = _graph._get_control_flow_context();
 
             // Note: _control_flow_post_processing() must not be called here, the caller is responsible for calling it when using this constructor.
         }

src/TensorFlowNET.Core/Sessions/BaseSession.cs

@@ -31,7 +31,6 @@ namespace Tensorflow
         protected bool _closed;
         protected int _current_version;
         protected byte[] _target;
-        protected IntPtr _session;
         public Graph graph => _graph;
 
         public BaseSession(string target = "", Graph g = null, SessionOptions opts = null)
@@ -46,7 +45,7 @@ namespace Tensorflow
 
             var status = new Status();
 
-            _session = c_api.TF_NewSession(_graph, opts ?? newOpts, status);
+            _handle = c_api.TF_NewSession(_graph, opts ?? newOpts, status);
 
             status.Check(true);
         }
@@ -212,7 +211,7 @@ namespace Tensorflow
 
             var output_values = fetch_list.Select(x => IntPtr.Zero).ToArray();
 
-            c_api.TF_SessionRun(_session,
+            c_api.TF_SessionRun(_handle,
                 run_options: null,
                 inputs: feed_dict.Select(f => f.Key).ToArray(),
                 input_values: feed_dict.Select(f => (IntPtr)f.Value).ToArray(),

src/TensorFlowNET.Core/Sessions/Session.cs

@@ -30,7 +30,7 @@ namespace Tensorflow
         public Session(IntPtr handle, Graph g = null)
             : base("", g, null)
         {
-            _session = handle;
+            _handle = handle;
         }
 
         public Session(Graph g, SessionOptions opts = null, Status s = null)
@@ -73,7 +73,7 @@ namespace Tensorflow
             return new Session(sess, g: new Graph(graph).as_default());
         }
 
-        public static implicit operator IntPtr(Session session) => session._session;
+        public static implicit operator IntPtr(Session session) => session._handle;
         public static implicit operator Session(IntPtr handle) => new Session(handle);
 
         public void __enter__()

test/TensorFlowNET.Examples/ImageProcessing/RetrainImageClassifier.cs

@@ -52,7 +52,8 @@ namespace TensorFlowNET.Examples
         // The location where variable checkpoints will be stored.
         string CHECKPOINT_NAME = Path.Join(data_dir, "_retrain_checkpoint");
         string tfhub_module = "https://tfhub.dev/google/imagenet/inception_v3/feature_vector/3";
-        string final_tensor_name = "final_result";
+        string input_tensor_name = "Placeholder";
+        string final_tensor_name = "Score";
         float testing_percentage = 0.1f;
         float validation_percentage = 0.1f;
         float learning_rate = 0.01f;
@@ -81,13 +82,13 @@ namespace TensorFlowNET.Examples
             PrepareData();
 
             #region For debug purpose
-            
+
             // predict images
             // Predict(null);
 
             // load saved pb and test new images.
             // Test(null); 
-            
+
             #endregion
 
             var graph = IsImportingGraph ? ImportGraph() : BuildGraph();
@@ -276,16 +277,13 @@ namespace TensorFlowNET.Examples
         private (Graph, Tensor, Tensor, bool) create_module_graph()
         {
             var (height, width) = (299, 299);
-
-            return tf_with(tf.Graph().as_default(), graph =>
-            {
-                tf.train.import_meta_graph("graph/InceptionV3.meta");
-                Tensor resized_input_tensor = graph.OperationByName("Placeholder"); //tf.placeholder(tf.float32, new TensorShape(-1, height, width, 3));
-                // var m = hub.Module(module_spec);
-                Tensor bottleneck_tensor = graph.OperationByName("module_apply_default/hub_output/feature_vector/SpatialSqueeze");// m(resized_input_tensor);
-                var wants_quantization = false;
-                return (graph, bottleneck_tensor, resized_input_tensor, wants_quantization);
-            });
+            var graph = tf.Graph().as_default();
+            tf.train.import_meta_graph("graph/InceptionV3.meta");
+            Tensor resized_input_tensor = graph.OperationByName(input_tensor_name); //tf.placeholder(tf.float32, new TensorShape(-1, height, width, 3));
+                                                                                // var m = hub.Module(module_spec);
+            Tensor bottleneck_tensor = graph.OperationByName("module_apply_default/hub_output/feature_vector/SpatialSqueeze");// m(resized_input_tensor);
+            var wants_quantization = false;
+            return (graph, bottleneck_tensor, resized_input_tensor, wants_quantization);
         }
 
         private (NDArray, long[], string[]) get_random_cached_bottlenecks(Session sess, Dictionary<string, Dictionary<string, string[]>> image_lists,
@@ -594,13 +592,10 @@ namespace TensorFlowNET.Examples
                 create_module_graph();
 
             // Add the new layer that we'll be training.
-            tf_with(graph.as_default(), delegate
-            {
-                (train_step, cross_entropy, bottleneck_input,
-                 ground_truth_input, final_tensor) = add_final_retrain_ops(
-                     class_count, final_tensor_name, bottleneck_tensor,
-                     wants_quantization, is_training: true);
-            });
+            (train_step, cross_entropy, bottleneck_input,
+             ground_truth_input, final_tensor) = add_final_retrain_ops(
+                 class_count, final_tensor_name, bottleneck_tensor,
+                 wants_quantization, is_training: true);
 
             return graph;
         }
@@ -734,15 +729,15 @@ namespace TensorFlowNET.Examples
             var labels = File.ReadAllLines(output_labels);
 
             // predict image
-            var img_path = Path.Join(image_dir, "roses", "12240303_80d87f77a3_n.jpg");
+            var img_path = Path.Join(image_dir, "daisy", "5547758_eea9edfd54_n.jpg");
             var fileBytes = ReadTensorFromImageFile(img_path);
 
             // import graph and variables
             var graph = new Graph();
             graph.Import(output_graph, "");
 
-            Tensor input = graph.OperationByName("Placeholder");
-            Tensor output = graph.OperationByName("final_result");
+            Tensor input = graph.OperationByName(input_tensor_name);
+            Tensor output = graph.OperationByName(final_tensor_name);
 
             using (var sess = tf.Session(graph))
             {

test/TensorFlowNET.UnitTest/NameScopeTest.cs

@@ -7,12 +7,13 @@ namespace TensorFlowNET.UnitTest
     [TestClass]
     public class NameScopeTest
     {
-        Graph g = ops.get_default_graph();
         string name = "";
 
         [TestMethod]
         public void NestedNameScope()
         {
+            Graph g = tf.Graph().as_default();
+
             tf_with(new ops.NameScope("scope1"), scope1 =>
             {
                 name = scope1;
@@ -37,6 +38,8 @@ namespace TensorFlowNET.UnitTest
                 Assert.AreEqual("scope1/Const_1:0", const3.name);
             });
 
+            g.Dispose();
+
             Assert.AreEqual("", g._name_stack);
         }
     }