fix max_pooling2d name_scope.

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

@@ -15,10 +15,12 @@ namespace Tensorflow
         public static variable_scope variable_scope(string name,
                string default_name = null,
                Tensor[] values = null,
-               bool auxiliary_name_scope = true) => new variable_scope(name, 
-                   default_name, 
+               bool? reuse = null,
+               bool auxiliary_name_scope = true) => new variable_scope(name,
+                   default_name,
                    values,
-                   auxiliary_name_scope);
+                   reuse: reuse,
+                   auxiliary_name_scope: auxiliary_name_scope);
 
         public static variable_scope variable_scope(VariableScope scope,
               string default_name = null,
@@ -27,7 +29,8 @@ namespace Tensorflow
               bool auxiliary_name_scope = true) => new variable_scope(scope,
                   default_name,
                   values,
-                  auxiliary_name_scope);
+                  reuse: reuse,
+                  auxiliary_name_scope: auxiliary_name_scope);
 
         public static IInitializer truncated_normal_initializer(float mean = 0.0f,
             float stddev = 1.0f,

src/TensorFlowNET.Core/Keras/Layers/Layer.cs

@@ -108,11 +108,11 @@ namespace Tensorflow.Keras.Layers
                     // Build layer if applicable (if the `build` method has been
                     // overridden).
                     _maybe_build(inputs[0]);
-                });
 
-               outputs = call(inputs[0], training: training);
-                _handle_activity_regularization(inputs[0], outputs);
-                _set_mask_metadata(inputs[0], outputs, null);
+                    outputs = call(inputs[0], training: training);
+                    _handle_activity_regularization(inputs[0], outputs);
+                    _set_mask_metadata(inputs[0], outputs, null);
+                });
             }
 
             return outputs;

src/TensorFlowNET.Core/Layers/Layer.cs

@@ -48,6 +48,7 @@ namespace Tensorflow.Layers
             else
             {
                 scope_context_manager = tf.variable_scope(_scope,
+                    reuse: _reuse,
                     auxiliary_name_scope: false);
             }
 
@@ -123,34 +124,33 @@ namespace Tensorflow.Layers
 
             _set_scope();
             var reuse = built || (_reuse != null && _reuse.Value);
-            return Python.with(tf.variable_scope(_scope, 
-                reuse: reuse, 
+            return with(tf.variable_scope(_scope,
+                reuse: reuse,
                 auxiliary_name_scope: false), scope =>
-            {
-                _current_scope = scope;
-                return Python.with(ops.name_scope(_name_scope()), delegate
                 {
-                    var variable = base.add_weight(name,
-                        shape,
-                        dtype: dtype,
-                        initializer: initializer,
-                        trainable: trainable,
-                        getter: (name1, shape1, dtype1, initializer1, trainable1) =>
-                        {
-                            return tf.get_variable(name1, 
-                                shape: new TensorShape(shape1),
-                                dtype: dtype1,
-                                initializer: initializer1,
-                                trainable: trainable1);
-                        });
-
-                    if(init_graph != null)
+                    _current_scope = scope;
+                    return with(ops.name_scope(_name_scope()), delegate
                     {
-                        var trainable_variables = variables.trainable_variables();
-                    }
-                    return variable;
+                        var variable = base.add_weight(name,
+                            shape,
+                            dtype: dtype,
+                            initializer: initializer,
+                            trainable: trainable,
+                            getter: (name1, shape1, dtype1, initializer1, trainable1) =>
+                            {
+                                return tf.get_variable(name1,
+                                    shape: new TensorShape(shape1),
+                                    dtype: dtype1,
+                                    initializer: initializer1,
+                                    trainable: trainable1);
+                            });
+
+                        //if (init_graph != null)
+                            //var trainable_variables = variables.trainable_variables();
+                        
+                        return variable;
+                    });
                 });
-            });
         }
 
 

src/TensorFlowNET.Core/Operations/NnOps/MaxPoolFunction.cs

@@ -5,6 +5,9 @@ using static Tensorflow.Python;
 
 namespace Tensorflow.Operations
 {
+    /// <summary>
+    /// Performs the max pooling on the input.
+    /// </summary>
     public class MaxPoolFunction : IPoolFunction
     {
         public Tensor Apply(Tensor value,
@@ -14,8 +17,9 @@ namespace Tensorflow.Operations
             string data_format = "NHWC",
             string name = null)
         {
-            return with(ops.name_scope(name, "MaxPool", new { value }), scope => {
-
+            return with(ops.name_scope(name, "MaxPool", value), scope => 
+            {
+                name = scope;
                 value = ops.convert_to_tensor(value, name: "input");
                 return gen_nn_ops.max_pool(
                     value,

src/TensorFlowNET.Core/TensorFlowNET.Core.csproj

@@ -5,7 +5,7 @@
     <AssemblyName>TensorFlow.NET</AssemblyName>
     <RootNamespace>Tensorflow</RootNamespace>
     <TargetTensorFlow>1.14.0</TargetTensorFlow>
-    <Version>0.8.0</Version>
+    <Version>0.8.1</Version>
     <Authors>Haiping Chen</Authors>
     <Company>SciSharp STACK</Company>
     <GeneratePackageOnBuild>true</GeneratePackageOnBuild>
@@ -17,15 +17,12 @@
     <PackageTags>TensorFlow, NumSharp, SciSharp, MachineLearning, TensorFlow.NET, C#</PackageTags>
     <Description>Google's TensorFlow full binding in .NET Standard.
 Docs: https://tensorflownet.readthedocs.io</Description>
-    <AssemblyVersion>0.8.0.0</AssemblyVersion>
-    <PackageReleaseNotes>Changes since v0.7:
+    <AssemblyVersion>0.8.1.0</AssemblyVersion>
+    <PackageReleaseNotes>Changes since v0.8:
 
-Add XOR example.
-Add KMeans example.
-Add Object Detection example.
-Add Word2Vec example.</PackageReleaseNotes>
+Removed global static graph instance.</PackageReleaseNotes>
     <LangVersion>7.2</LangVersion>
-    <FileVersion>0.8.0.0</FileVersion>
+    <FileVersion>0.8.1.0</FileVersion>
   </PropertyGroup>
 
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|AnyCPU'">

src/TensorFlowNET.Core/Variables/variable_scope.py.cs

@@ -107,7 +107,7 @@ namespace Tensorflow
             if (_name != null || _scope != null)
             {
                 var name_scope = _name == null ? _scope.name.Split('/').Last() : _name;
-                if (name_scope != null || current_name_scope != null)
+                if (current_name_scope == null)
                     current_name_scope = ops.name_scope(name_scope);
                 current_name_scope.__enter__();
                 var current_name_scope_name = current_name_scope;

test/TensorFlowNET.Examples/TextProcess/CnnTextClassification.cs

@@ -174,7 +174,8 @@ namespace TensorFlowNET.Examples
                 x_emb = tf.expand_dims(x_emb, -1);
             });
 
-            for(int len = 0; len < filter_sizes.Rank; len++)
+            var pooled_outputs = new List<Tensor>();
+            for (int len = 0; len < filter_sizes.Rank; len++)
             {
                 int filter_size = filter_sizes.GetLength(len);
                 var conv = tf.layers.conv2d(
@@ -190,8 +191,11 @@ namespace TensorFlowNET.Examples
                     pool_size: new[] { document_max_len - filter_size + 1, 1 },
                     strides: new[] { 1, 1 },
                     padding: "VALID");
+
+                pooled_outputs.Add(pool);
             }
 
+            // var h_pool = tf.concat(pooled_outputs, 3);
             return graph;
         }