fix create_slot_with_initializer, upgrade to v1.14.0.

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

@@ -23,6 +23,8 @@ namespace Tensorflow
             TF_DataType dtype = TF_DataType.DtInvalid,
             object initializer = null, // IInitializer or Tensor
             bool? trainable = null,
+            bool? use_resource = null,
+            bool validate_shape = true,
             VariableSynchronization synchronization = VariableSynchronization.Auto,
             VariableAggregation aggregation = VariableAggregation.None)
         {
@@ -32,6 +34,8 @@ namespace Tensorflow
                 name, 
                 shape: shape, 
                 dtype: dtype,
+                use_resource: use_resource,
+                validate_shape: validate_shape,
                 initializer: initializer,
                 trainable: trainable);
         }

src/TensorFlowNET.Core/Train/AdamOptimizer.cs

@@ -73,7 +73,8 @@ namespace Tensorflow.Train
             // Create slots for the first and second moments.
             foreach(var v in var_list)
             {
-                _zero_slot(v, "m", Name);
+                _zeros_slot(v, "m", Name);
+                _zeros_slot(v, "v", Name);
             }
         }
 

src/TensorFlowNET.Core/Train/Optimizer.cs

@@ -21,7 +21,8 @@ namespace Tensorflow
         public static int GATE_OP = 1;
         public static int GATE_GRAPH = 2;
 
-        public string Name { get; set; }
+        string _name;
+        public string Name => _name;
         public float LearningRate { get; set; }
         public Tensor LearningRateTensor { get; set; }
         public bool _use_locking;
@@ -35,7 +36,7 @@ namespace Tensorflow
             if (String.IsNullOrEmpty(name))
                 throw new NotImplementedException("Must specify the optimizer name");
 
-            Name = name;
+            _name = name;
             _use_locking = use_locking;
             LearningRate = learning_rate;
             // Dictionary of slots.
@@ -391,22 +392,34 @@ namespace Tensorflow
         /// <param name="slot_name"></param>
         /// <param name="op_name"></param>
         /// <returns></returns>
-        protected RefVariable _zero_slot(RefVariable var, string slot_name, string op_name)
+        protected RefVariable _zeros_slot(RefVariable var, string slot_name, string op_name)
         {
             var named_slots = _slot_dict(slot_name);
             if (!named_slots.ContainsKey(_var_key(var)))
             {
                 var new_slot_variable = slot_creator.create_zeros_slot(var, op_name);
+                _restore_slot_variable(slot_name: slot_name, variable: var, slot_variable: new_slot_variable);
+                named_slots[_var_key(var)] = new_slot_variable;
             }
             return named_slots[_var_key(var)];
         }
 
+        /// <summary>
+        /// Restore a newly created slot variable's value.
+        /// </summary>
+        protected void _restore_slot_variable(string slot_name, RefVariable variable, RefVariable slot_variable)
+        {
+            var variable_key = _var_key(variable);
+            // TODO
+        }
+
         protected Dictionary<string, RefVariable> _slot_dict(string slot_name)
         {
             var named_slots = _slots.ContainsKey(slot_name) ? _slots[slot_name] : null;
             if(named_slots == null)
             {
-                _slots[slot_name] = new Dictionary<string, RefVariable>();
+                named_slots = new Dictionary<string, RefVariable>();
+                _slots[slot_name] = named_slots;
             }
 
             return named_slots;

src/TensorFlowNET.Core/Train/SlotCreator.cs

@@ -43,7 +43,7 @@ namespace Tensorflow.Train
         {
             var validate_shape = shape.is_fully_defined();
             var prefix = primary.op.name;
-            return with(new variable_scope(prefix + "/" + name), delegate
+            return with(new variable_scope(string.Empty, prefix + "/" + name), delegate
             {
                 return _create_slot_var(primary, initializer, "", validate_shape, shape, dtype);
             });
@@ -62,11 +62,11 @@ namespace Tensorflow.Train
         private RefVariable _create_slot_var(VariableV1 primary, IInitializer val, string scope, bool validate_shape, 
             TensorShape shape, TF_DataType dtype)
         {
-            bool use_resource = primary is RefVariable;
+            bool use_resource = primary is ResourceVariable;
             if (resource_variable_ops.is_resource_variable(primary))
                 use_resource = true;
 
-            var slot = variable_scope.get_variable(
+            var slot = tf.get_variable(
               scope,
               initializer: val,
               trainable: false,

src/TensorFlowNET.Core/Variables/VariableScope.cs

@@ -37,6 +37,8 @@ namespace Tensorflow
             TF_DataType dtype = TF_DataType.DtInvalid,
             object initializer = null, // IInitializer or Tensor
             bool? trainable = null,
+            bool? use_resource = null,
+            bool validate_shape = true,
             VariableSynchronization synchronization = VariableSynchronization.Auto,
             VariableAggregation aggregation= VariableAggregation.None)
         {

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

@@ -104,7 +104,7 @@ namespace Tensorflow
                 current_name_scope = ops.name_scope(name_scope);
             }
 
-            if (_name != null || _scope != null)
+            if (!string.IsNullOrEmpty(_name) || _scope != null)
             {
                 var name_scope = _scope.name.Split('/').Last();
                 if (current_name_scope == null)

tensorflowlib/README.md

@@ -3,12 +3,12 @@ TensorFlow.NET pack all required libraries in architecture-specific assemblies f
 Here are some pre-built TensorFlow binaries you can use for each platform:
 
 - Linux
-  - CPU-only: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.13.1.tar.gz
-  - GPU-enabled: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-1.13.1.tar.gz
-- Mac: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-1.13.1.tar.gz
+  - CPU-only: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.14.0.tar.gz
+  - GPU-enabled: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-1.14.0.tar.gz
+- Mac: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-1.14.0.tar.gz
 - Windows
-  - CPU-only: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-windows-x86_64-1.13.1.zip
-  - GPU-enabled: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-windows-x86_64-1.13.1.zip
+  - CPU-only: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-windows-x86_64-1.14.0.zip
+  - GPU-enabled: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-windows-x86_64-1.14.0.zip
 
 ### Run in Linux
 
@@ -41,7 +41,7 @@ pacman -S git patch unzip
 
 4. Install from local wheel file.
 
-`pip install C:/tmp/tensorflow_pkg/tensorflow-1.13.0-cp36-cp36m-win_amd64.whl`
+`pip install C:/tmp/tensorflow_pkg/tensorflow-1.14.0-cp36-cp36m-win_amd64.whl`
 
 ### Export more APIs
 

test/TensorFlowNET.Examples/TensorFlowNET.Examples.csproj

@@ -17,7 +17,7 @@
     <PackageReference Include="Newtonsoft.Json" Version="12.0.2" />
     <PackageReference Include="SharpZipLib" Version="1.1.0" />
     <PackageReference Include="System.Drawing.Common" Version="4.5.1" />
-    <PackageReference Include="TensorFlow.NET" Version="0.8.0" />
+    <PackageReference Include="TensorFlow.NET" Version="0.8.2" />
   </ItemGroup>
 
   <ItemGroup>