reousrce variable.

src/TensorFlowNET.Core/Eager/Context.cs

@@ -9,6 +9,7 @@ namespace Tensorflow.Eager
 
         public int default_execution_mode;
         public string device_name = "";
+        public string scope_name = "";
         bool _initialized = false;
 
         public Context(ContextOptions opts, Status status)
@@ -33,6 +34,11 @@ namespace Tensorflow.Eager
 
         public bool executing_eagerly() => true;
 
+        public string shared_name(string name = null)
+            => !string.IsNullOrEmpty(name) || !executing_eagerly() ? 
+                name : 
+                "cd2c89b7-88b7-44c8-ad83-06c2a9158347";
+
         public static implicit operator IntPtr(Context ctx) 
             => ctx._handle;
 

src/TensorFlowNET.Core/Eager/TFE_Op.cs

@@ -18,6 +18,6 @@ namespace Tensorflow.Eager
             => tensor._handle;
 
         public override string ToString()
-            => $"TFE_Op {_handle}";
+            => $"TFE_Op 0x{_handle.ToString("x16")}";
     }
 }

src/TensorFlowNET.Core/Eager/TFE_TensorHandle.cs

@@ -18,6 +18,6 @@ namespace Tensorflow.Eager
             => tensor._handle;
 
         public override string ToString()
-            => $"TFE_TensorHandle {_handle}";
+            => $"TFE_TensorHandle 0x{_handle.ToString("x16")}";
     }
 }

src/TensorFlowNET.Core/Eager/c_api.eager.cs

@@ -89,7 +89,7 @@ namespace Tensorflow
         /// <param name="num_retvals">int*</param>
         /// <param name="status">TF_Status*</param>
         [DllImport(TensorFlowLibName)]
-        public static extern void TFE_Execute(TFE_Op op, IntPtr[] retvals, ref int num_retvals, IntPtr status);
+        public static extern void TFE_Execute(IntPtr op, IntPtr[] retvals, ref int num_retvals, IntPtr status);
 
         /// <summary>
         /// 

src/TensorFlowNET.Core/Eager/wrap_tfe_src.TFE_FastPathExecute.cs

@@ -147,6 +147,7 @@ namespace Tensorflow.Eager
 
             c_api.TFE_OpAddInput(op, input_handle, status);
             status.Check(true);
+
             return true;
         }
 
@@ -236,8 +237,13 @@ namespace Tensorflow.Eager
                 case TF_AttrType.TF_ATTR_INT:
                     c_api.TFE_OpSetAttrInt(op, key, Convert.ToInt64(value));
                     break;
+                case TF_AttrType.TF_ATTR_SHAPE:
+                    var dims = (value as int[]).Select(x => (long)x).ToArray();
+                    c_api.TFE_OpSetAttrShape(op, key, dims, dims.Length, status);
+                    status.Check(true);
+                    break;
                 default:
-                    throw new NotImplementedException("");
+                    throw new NotImplementedException($"SetOpAttrScalar for {type}");
             }
 
             return true;

src/TensorFlowNET.Core/Operations/gen_resource_variable_ops.cs

@@ -14,6 +14,9 @@
    limitations under the License.
 ******************************************************************************/
 
+using Tensorflow.Eager;
+using static Tensorflow.Binding;
+
 namespace Tensorflow
 {
     public static class gen_resource_variable_ops
@@ -29,6 +32,14 @@ namespace Tensorflow
 
         public static Tensor var_is_initialized_op(Tensor resource, string name = null)
         {
+            if (tf.context.executing_eagerly())
+            {
+                var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "VarIsInitializedOp", name, null,
+                    resource);
+                return _result;
+            }
+
             var _op = _op_def_lib._apply_op_helper("VarIsInitializedOp", name, new { resource });
 
             return _op.output;
@@ -46,6 +57,14 @@ namespace Tensorflow
         public static Tensor var_handle_op(TF_DataType dtype, TensorShape shape, 
             string container ="", string shared_name = "", string name = null)
         {
+            if (tf.context.executing_eagerly())
+            {
+                var _result = wrap_tfe_src.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                    "VarHandleOp", name, null,
+                    "container", container, "shared_name", shared_name, "dtype", dtype, "shape", shape.dims);
+                return _result;
+            }
+
             var _op = _op_def_lib._apply_op_helper("VarHandleOp", name, new {
                 dtype,
                 shape,

src/TensorFlowNET.Core/Operations/resource_variable_ops.cs

@@ -100,10 +100,10 @@ namespace Tensorflow
         /// <param name="shared_name"></param>
         /// <param name="name"></param>
         /// <param name="graph_mode"></param>
-        /// <param name="extra_handle_data"></param>
+        /// <param name="initial_value"></param>
         /// <returns></returns>
         public static Tensor variable_handle_from_shape_and_dtype(TensorShape shape, TF_DataType dtype, 
-            string shared_name, string name, bool graph_mode, Tensor extra_handle_data = null)
+            string shared_name, string name, bool graph_mode, Tensor initial_value = null)
         {
             var container = "";// ops.get_default_graph().container;
             var handle = gen_resource_variable_ops.var_handle_op(shape: shape,
@@ -112,17 +112,22 @@ namespace Tensorflow
                 name: name,
                 container: container);
 
-            if (extra_handle_data == null)
-                extra_handle_data = handle;
+            if (initial_value == null)
+                initial_value = handle;
 
             if (graph_mode)
             {
-                var full_handle_data = _combine_handle_data(handle, extra_handle_data);
+                var full_handle_data = _combine_handle_data(handle, initial_value);
                 _set_handle_shapes_and_types(handle, full_handle_data, graph_mode);
                 return handle;
             }
             else
             {
+                // We do not want two distinct ResourceVariable objects for the same
+                // underlying resource in the runtime.
+                // When in eager mode, explicitly ensure so here. When in graph mode, it's
+                // ensured by always generating different variable names.
+                var exists = gen_resource_variable_ops.var_is_initialized_op(handle);
                 throw new NotImplementedException("");
             }
         }

src/TensorFlowNET.Core/Status/Status.cs

@@ -71,5 +71,8 @@ namespace Tensorflow
 
         protected override void DisposeUnmanagedResources(IntPtr handle)
             => TF_DeleteStatus(handle);
+
+        public override string ToString()
+            => $"{Code} 0x{_handle.ToString("x16")}";
     }
 }

src/TensorFlowNET.Core/Summaries/Summary.cs

@@ -90,13 +90,13 @@ namespace Tensorflow.Summaries
             string scope_base_name = string.IsNullOrEmpty(family) ? name : $"{family}/{name}";
             return tf_with(ops.name_scope(scope_base_name, default_name: default_name, values), scope =>
             {
-                var tag = scope._name_scope;
+                var tag = scope.scope_name;
                 if (string.IsNullOrEmpty(family))
                     tag = tag.Remove(tag.Length - 1);
                 else
                     tag = $"{family}/{tag.Remove(tag.Length - 1)}";
 
-                return (tag, scope._name_scope);
+                return (tag, scope.scope_name);
             });
         }
     }

src/TensorFlowNET.Core/Tensors/Tensor.Value.cs

@@ -181,6 +181,8 @@ namespace Tensorflow
                     return (NDArray)StringData()[0];
                 case TF_DataType.TF_INT32:
                     return *(int*)buffer;
+                case TF_DataType.TF_FLOAT:
+                    return *(float*)buffer;
                 case TF_DataType.TF_DOUBLE:
                     return *(double*)buffer;
                 default:

src/TensorFlowNET.Core/Tensors/TensorShape.cs

@@ -253,7 +253,7 @@ namespace Tensorflow
         public static implicit operator Shape(TensorShape shape) => new Shape((int[]) shape.dims.Clone());
         
         public static implicit operator int[](TensorShape shape) => shape == null ? null : (int[])shape.dims.Clone(); //we clone to avoid any changes
-        public static implicit operator TensorShape(int[] dims) => new TensorShape(dims);
+        public static implicit operator TensorShape(int[] dims) => dims == null ? new TensorShape(new int[0]) : new TensorShape(dims);
 
         public static explicit operator int(TensorShape shape) => shape.size;
         public static implicit operator TensorShape(int dim) => new TensorShape(dim);

src/TensorFlowNET.Core/Tensors/constant_op.cs

@@ -91,6 +91,10 @@ namespace Tensorflow
                     return new EagerTensor(str, ctx.device_name);
                 case int int32:
                     return new EagerTensor(int32, ctx.device_name);
+                case float float32:
+                    return new EagerTensor(float32, ctx.device_name);
+                case double double64:
+                    return new EagerTensor(double64, ctx.device_name);
                 case float[] float32s:
                     return new EagerTensor(float32s, ctx.device_name);
                 case double[] double64s:

src/TensorFlowNET.Core/Variables/ResourceVariable.cs

@@ -94,20 +94,28 @@ namespace Tensorflow
             if(collections == null)
                 collections = new List<string>() { tf.GraphKeys.GLOBAL_VARIABLES };
             _trainable = trainable;
-            _graph_key = ops.get_default_graph().graph_key;
+
+            if (trainable && !collections.Contains(tf.GraphKeys.TRAINABLE_VARIABLES))
+                collections.Add(tf.GraphKeys.TRAINABLE_VARIABLES);
 
             ops.init_scope();
-            _in_graph_mode = true;
+            _in_graph_mode = !tf.context.executing_eagerly();
             tf_with(ops.name_scope(name, "Variable"), scope =>
             {
                 name = scope;
                 var handle_name = ops.name_from_scope_name(name);
-                var shared_name = handle_name;
-                var unique_id = shared_name;
+                var unique_id = $"{handle_name}_{ops.uid()}";
+                var shared_name = tf.context.shared_name();
+
+                if (_in_graph_mode)
+                {
+                    shared_name = handle_name;
+                    unique_id = shared_name;
+                }
 
                 var attr = new AttrValue();
                 attr.List = new AttrValue.Types.ListValue();
-                attr.List.S.Add(ByteString.CopyFromUtf8($"loc:{handle_name}"));
+                attr.List.S.Add(ByteString.CopyFromUtf8($"loc:@{handle_name}"));
                 tf_with(ops.name_scope("Initializer"), delegate
                 {
                     initial_value = ops.convert_to_tensor(init_from_fn ? (initial_value as Func<Tensor>)() : initial_value,

src/TensorFlowNET.Core/ops.cs

@@ -241,6 +241,9 @@ namespace Tensorflow
         /// <returns></returns>
         public static void init_scope()
         {
+            if (tf.context.executing_eagerly())
+                return;
+
             // Retrieve the active name scope: entering an `init_scope` preserves
             // the name scope of the current context.
             var default_graph = get_default_graph();

src/TensorFlowNET.Core/ops.name_scope.cs

@@ -15,6 +15,8 @@
 ******************************************************************************/
 
 using System.Collections.Generic;
+using Tensorflow.Eager;
+using static Tensorflow.Binding;
 
 namespace Tensorflow
 {
@@ -32,8 +34,8 @@ namespace Tensorflow
             public string _name;
             public string _default_name;
             public object _values;
-            public string _name_scope;
-            public string old_stack = "";
+            public string scope_name;
+            public string old_scope_name = "";
             
             public NameScope(string name, string default_name = "", object values = null)
             {
@@ -44,29 +46,54 @@ namespace Tensorflow
 
             public void __enter__()
             {
-                _name = _name ?? _default_name;
-                if (_name.EndsWith("basic_r_n_n_cell"))
+                if (tf.context.executing_eagerly())
                 {
+                    (scope_name, old_scope_name) = enter_eager_name_scope(tf.context, _name);
+                }
+                else
+                {
+                    _name = _name ?? _default_name;
+                    Graph g = null;
+
+                    if (_values is List<Tensor> vList)
+                        g = _get_graph_from_inputs(vList.ToArray());
+                    else if (_values is Tensor[] vArray)
+                        g = _get_graph_from_inputs(vArray);
+
+                    if (g == null)
+                        g = get_default_graph();
 
+                    old_scope_name = g._name_stack;
+                    scope_name = g.name_scope(_name);
                 }
-                Graph g = null;
+            }
 
-                if (_values is List<Tensor> vList)
-                    g = _get_graph_from_inputs(vList.ToArray());
-                else if (_values is Tensor[] vArray)
-                    g = _get_graph_from_inputs(vArray);
+            private (string, string) enter_eager_name_scope(Context ctx, string name)
+            {
+                if (name == null)
+                    name = "";
 
-                if (g == null)
-                    g = get_default_graph();
+                var scope_name = name;
+                var old_name = ctx.scope_name;
+                // A trailing slash breaks out of nested name scopes, indicating a
+                // fully specified scope name, for compatibility with Graph.name_scope.
+                if (!name.EndsWith("/"))
+                {
+                    scope_name = name + "/";
+                    if (!string.IsNullOrEmpty(old_name))
+                        scope_name = old_name + scope_name;
+                }
 
-                old_stack = g._name_stack;
-                _name_scope = g.name_scope(_name);
+                ctx.scope_name = scope_name;
+                return (scope_name, old_name);
             }
 
             public void Dispose()
             {
-                var g = get_default_graph();
-                g._name_stack = old_stack;
+                if (tf.context.executing_eagerly())
+                    tf.context.scope_name = old_scope_name;
+                else
+                    get_default_graph()._name_stack = old_scope_name;
             }
             
             public void __exit__()
@@ -89,7 +116,7 @@ namespace Tensorflow
             /// <param name="ns"></param>
             public static implicit operator string(NameScope ns)
             {
-                return ns._name_scope;
+                return ns.scope_name;
             }
         }
     }