change ops.name_scope interface.

src/TensorFlowNET.Core/Framework/importer.py.cs

@@ -26,7 +26,7 @@ namespace Tensorflow
 
             string prefix = "";
             var graph = ops.get_default_graph();
-            with(new ops.name_scope(name, "import", input_map.Values), scope =>
+            with(ops.name_scope(name, "import", input_map.Values), scope =>
             {
                 prefix = scope;
                 /*if (!string.IsNullOrEmpty(prefix))

src/TensorFlowNET.Core/Framework/tf.ops.cs

@@ -16,8 +16,8 @@ namespace Tensorflow
         /// <param name="default_name">The default name to use if the name argument is None.</param>
         /// <param name="values">The list of Tensor arguments that are passed to the op function.</param>
         /// <returns>The scope name.</returns>
-        public static ops.name_scope name_scope(string name, 
+        public static ops.NameScope name_scope(string name, 
             string default_name = "", 
-            object values = null) => new ops.name_scope(name, default_name, values);
+            object values = null) => new ops.NameScope(name, default_name, values);
     }
 }

src/TensorFlowNET.Core/Gradients/gradients_impl.py.cs

@@ -58,7 +58,7 @@ namespace Tensorflow
              **/
             var grads = new Dictionary<string, Tensor[][]>();
 
-            with(new ops.name_scope(name, "gradients", values: all), scope =>
+            with(ops.name_scope(name, "gradients", values: all), scope =>
             {
                 string grad_scope = scope;
                 // Get a uid for this call to gradients that can be used to help
@@ -131,7 +131,7 @@ namespace Tensorflow
                             // for ops that do not have gradients.
                             var grad_fn = ops.get_gradient_function(op);
 
-                            with(new ops.name_scope(op.name + "_grad"), scope1 =>
+                            with(ops.name_scope(op.name + "_grad"), scope1 =>
                             {
                                 string name1 = scope1;
                                 if (grad_fn != null)

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

@@ -31,7 +31,7 @@ namespace Tensorflow.Keras.Engine
             bool build_graph = tf_utils.are_all_symbolic_tensors(input_list);
 
             // Handle Keras mask propagation from previous layer to current layer.
-            Python.with(new ops.name_scope(_name_scope()), delegate
+            Python.with(ops.name_scope(_name_scope()), delegate
             {
                 if (!built)
                 {

src/TensorFlowNET.Core/Layers/Layer.cs

@@ -92,7 +92,7 @@ namespace Tensorflow.Layers
                 auxiliary_name_scope: false), scope =>
             {
                 _current_scope = scope;
-                Python.with(new ops.name_scope(_name_scope()), delegate
+                Python.with(ops.name_scope(_name_scope()), delegate
                 {
 
 

src/TensorFlowNET.Core/Operations/Distributions/normal.py.cs

@@ -33,7 +33,7 @@ namespace Tensorflow
             parameters.Add("validate_args", validate_args);
             parameters.Add("allow_nan_stats", allow_nan_stats);
 
-            with(new ops.name_scope(name, "", new { loc, scale }), scope => 
+            with(ops.name_scope(name, "", new { loc, scale }), scope => 
             {
                 with(ops.control_dependencies(validate_args ? new Operation[] { scale.op} : new Operation[] { }), cd =>
                 {

src/TensorFlowNET.Core/Operations/Losses/losses_impl.py.cs

@@ -12,7 +12,7 @@ namespace Tensorflow
             string scope = "",
             string loss_collection= "losses")
         {
-            with(new ops.name_scope(scope,
+            with(ops.name_scope(scope,
                 "sparse_softmax_cross_entropy_loss",
                 (logits, labels, weights)),
                 namescope =>

src/TensorFlowNET.Core/Operations/OpDefLibrary.cs

@@ -44,7 +44,7 @@ namespace Tensorflow
             var input_types = new List<TF_DataType>();
             dynamic values = null;
 
-            return with(new ops.name_scope(name), scope =>
+            return with(ops.name_scope(name), scope =>
             {
                 var inferred_from = new Dictionary<string, object>();
                 var base_types = new List<TF_DataType>();

src/TensorFlowNET.Core/Operations/array_ops.py.cs

@@ -12,7 +12,7 @@ namespace Tensorflow
         public static Tensor zeros(Shape shape, TF_DataType dtype = TF_DataType.TF_FLOAT, string name = null)
         {
             dtype = dtype.as_base_dtype();
-            return with(new ops.name_scope(name, "zeros", shape), scope =>
+            return with(ops.name_scope(name, "zeros", shape), scope =>
             {
                 name = scope;
                 switch (dtype)
@@ -68,7 +68,7 @@ namespace Tensorflow
 
         private static Tensor ones_like_impl<T>(T tensor, TF_DataType dtype, string name, bool optimize = true)
         {
-            return with(new ops.name_scope(name, "ones_like", new { tensor }), scope =>
+            return with(ops.name_scope(name, "ones_like", new { tensor }), scope =>
             {
                 name = scope;
                 var tensor1 = ops.convert_to_tensor(tensor, name: "tensor");
@@ -84,7 +84,7 @@ namespace Tensorflow
         public static Tensor ones(Tensor shape, TF_DataType dtype = TF_DataType.TF_FLOAT, string name = null)
         {
             dtype = dtype.as_base_dtype();
-            return with(new ops.name_scope(name, "ones", new { shape }), scope =>
+            return with(ops.name_scope(name, "ones", new { shape }), scope =>
             {
                 name = scope;
                 var output = gen_array_ops.fill(shape, constant_op.constant(1.0f, dtype: dtype), name: name);
@@ -130,7 +130,7 @@ namespace Tensorflow
 
         private static Tensor shape_internal(Tensor input, string name = null, bool optimize = true, TF_DataType out_type = TF_DataType.TF_INT32)
         {
-            return with(new ops.name_scope(name, "Shape", new { input }), scope =>
+            return with(ops.name_scope(name, "Shape", new { input }), scope =>
             {
                 name = scope;
 
@@ -151,7 +151,7 @@ namespace Tensorflow
 
         private static Tensor size_internal(Tensor input, string name = null, bool optimize = true, TF_DataType out_type = TF_DataType.TF_INT32)
         {
-            return with(new ops.name_scope(name, "Size", new Tensor[] { input }), scope =>
+            return with(ops.name_scope(name, "Size", new Tensor[] { input }), scope =>
             {
                 name = scope;
 
@@ -182,7 +182,7 @@ namespace Tensorflow
 
         public static Tensor zeros_like(Tensor tensor, TF_DataType dtype = TF_DataType.DtInvalid, string name = null, bool optimize = true)
         {
-            return with(new ops.name_scope(name, "zeros_like", new Tensor[] { tensor }), scope =>
+            return with(ops.name_scope(name, "zeros_like", new Tensor[] { tensor }), scope =>
             {
                 name = scope;
                 tensor = ops.convert_to_tensor(tensor, name: "tensor");

src/TensorFlowNET.Core/Operations/control_flow_ops.py.cs

@@ -9,7 +9,7 @@ namespace Tensorflow
     {
         public static Operation group<T>(T[] inputs, string name = null) where T : ITensorOrOperation
         {
-            return with(new ops.name_scope(name, "group_deps", inputs), scope =>
+            return with(ops.name_scope(name, "group_deps", inputs), scope =>
             {
                 name = scope;
 
@@ -83,7 +83,7 @@ namespace Tensorflow
 
         public static Tensor[] tuple(Tensor[] tensors, string name = null, Operation[] control_inputs = null)
         {
-            return with(new ops.name_scope(name, "tuple", tensors), scope =>
+            return with(ops.name_scope(name, "tuple", tensors), scope =>
             {
                 name = scope;
                 var gating_ops = tensors.Select(x => x.op).ToList();
@@ -115,7 +115,7 @@ namespace Tensorflow
             values.AddRange(dependencies);
             values.Add(output_tensor);
 
-            return with(new ops.name_scope(name, "control_dependency", values), scope =>
+            return with(ops.name_scope(name, "control_dependency", values), scope =>
             {
                 name = scope;
 

src/TensorFlowNET.Core/Operations/embedding_ops.cs

@@ -20,7 +20,7 @@ namespace Tensorflow
                 string name = null,
                 string max_norm = null)
         {
-            return with(new ops.name_scope(name, "embedding_lookup", new { @params, ids }), scope =>
+            return with(ops.name_scope(name, "embedding_lookup", new { @params, ids }), scope =>
             {
                 name = scope;
                 int np = 1;

src/TensorFlowNET.Core/Operations/math_ops.py.cs

@@ -15,7 +15,7 @@ namespace Tensorflow
             if(base_type == x.dtype)
                 return x;
 
-            return with(new ops.name_scope(name, "Cast", new { x }), scope =>
+            return with(ops.name_scope(name, "Cast", new { x }), scope =>
             {
                 x = ops.convert_to_tensor(x, name: "x");
                 if (x.dtype.as_base_dtype() != base_type)
@@ -166,7 +166,7 @@ namespace Tensorflow
             if (delta == null)
                 delta = 1;
 
-            return with(new ops.name_scope(name, "Range", new object[] { start, limit, delta }), scope =>
+            return with(ops.name_scope(name, "Range", new object[] { start, limit, delta }), scope =>
             {
                 name = scope;
                 var start1 = ops.convert_to_tensor(start, name: "start");
@@ -179,7 +179,7 @@ namespace Tensorflow
 
         public static Tensor floordiv(Tensor x, Tensor y, string name = null)
         {
-            return with(new ops.name_scope(name, "floordiv", new { x, y }), scope =>
+            return with(ops.name_scope(name, "floordiv", new { x, y }), scope =>
             {
                 return gen_math_ops.floor_div(x, y, scope);
             });
@@ -187,7 +187,7 @@ namespace Tensorflow
 
         public static Tensor rank_internal(Tensor input, string name = null, bool optimize = true)
         {
-            return with(new ops.name_scope(name, "Rank", new List<Tensor> { input }), scope =>
+            return with(ops.name_scope(name, "Rank", new List<Tensor> { input }), scope =>
             {
                 name = scope;
                 var input_tensor = ops.convert_to_tensor(input);
@@ -207,7 +207,7 @@ namespace Tensorflow
         {
             Tensor result = null;
 
-            with(new ops.name_scope(name, "MatMul", new Tensor[] { a, b }), scope =>
+            with(ops.name_scope(name, "MatMul", new Tensor[] { a, b }), scope =>
             {
                 name = scope;
 
@@ -237,7 +237,7 @@ namespace Tensorflow
             if (dt.is_floating() || dt.is_integer())
                 return x;
 
-            return with(new ops.name_scope(name, "Conj", new List<Tensor> { x }), scope =>
+            return with(ops.name_scope(name, "Conj", new List<Tensor> { x }), scope =>
             {
 
                 return x;

src/TensorFlowNET.Core/Operations/nn_impl.py.cs

@@ -19,7 +19,7 @@ namespace Tensorflow
             string name = null,
             bool keep_dims = false)
         {
-            return with<ops.name_scope, (Tensor, Tensor)>(new ops.name_scope(name, "moments", new { x, axes }), scope =>
+            return with(ops.name_scope(name, "moments", new { x, axes }), scope =>
             {
                 // The dynamic range of fp16 is too limited to support the collection of
                 // sufficient statistics. As a workaround we simply perform the operations

src/TensorFlowNET.Core/Operations/random_ops.py.cs

@@ -23,7 +23,7 @@ namespace Tensorflow
             int? seed = null, 
             string name = null)
         {
-            return with(new ops.name_scope(name, "random_normal", new { shape, mean, stddev }), scope =>
+            return with(ops.name_scope(name, "random_normal", new { shape, mean, stddev }), scope =>
             {
                 var shape_tensor = _ShapeTensor(shape);
                 var mean_tensor = ops.convert_to_tensor(mean, dtype: dtype, name: "mean");
@@ -53,7 +53,7 @@ namespace Tensorflow
             int? seed = null, 
             string name = null)
         {
-            return with(new ops.name_scope(name, "random_uniform", new { shape, minval, maxval }), scope =>
+            return with(ops.name_scope(name, "random_uniform", new { shape, minval, maxval }), scope =>
             {
                 name = scope;
                 var tensorShape = _ShapeTensor(shape);

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

@@ -41,7 +41,7 @@ namespace Tensorflow
             if( y is Tensor tr)
                 dtype = tr.dtype.as_base_dtype();
             
-            var namescope = new ops.name_scope(null, name, new { x, y });
+            var namescope = ops.name_scope(null, name, new { x, y });
             return with(namescope, scope =>
             {
                 Tensor result = null;

src/TensorFlowNET.Core/Train/Optimizer.cs

@@ -87,7 +87,7 @@ namespace Tensorflow
             _create_slots(var_list);
 
             var update_ops = new List<Operation>();
-            return with(new ops.name_scope(name, Name), scope =>
+            return with(ops.name_scope(name, Name), scope =>
             {
                 name = scope;
                 _prepare();
@@ -98,7 +98,7 @@ namespace Tensorflow
                         continue;
 
                     var scope_name = var.op.name;
-                    with(new ops.name_scope("update_" + scope_name), scope2 =>
+                    with(ops.name_scope("update_" + scope_name), scope2 =>
                     {
                         update_ops.Add(processor.update_op(this, grad));
                     });

src/TensorFlowNET.Core/Train/Saving/BaseSaverBuilder.cs

@@ -79,7 +79,7 @@ namespace Tensorflow
             Tensor save_tensor = null;
             Operation restore_op = null;
 
-            return with(new ops.name_scope(name, "save", saveables.Select(x => x.op).ToArray()), scope =>
+            return with(ops.name_scope(name, "save", saveables.Select(x => x.op).ToArray()), scope =>
             {
                 name = scope;
 

src/TensorFlowNET.Core/Variables/RefVariable.Operators.cs

@@ -17,7 +17,7 @@ namespace Tensorflow
         private static Tensor op_helper<T>(string default_name, RefVariable x, T y)
         {
             var tensor1 = x.value();
-            return with(new ops.name_scope(null, default_name, new { tensor1, y }), scope => {
+            return with(ops.name_scope(null, default_name, new { tensor1, y }), scope => {
                 var tensor2 = ops.convert_to_tensor(y, tensor1.dtype.as_base_dtype(), "y");
                 return gen_math_ops.add(tensor1, tensor2, scope);
             });

src/TensorFlowNET.Core/Variables/RefVariable.cs

@@ -118,7 +118,7 @@ namespace Tensorflow
 
             ops.init_scope();
             var values = init_from_fn ? new object[0] : new object[] { initial_value };
-            with(new ops.name_scope(name, "Variable", values), scope =>
+            with(ops.name_scope(name, "Variable", values), scope =>
             {
                 name = scope;
                 if (init_from_fn)
@@ -132,7 +132,7 @@ namespace Tensorflow
                         List = new AttrValue.Types.ListValue()
                     };
                     attr.List.S.Add(ByteString.CopyFromUtf8($"loc:{true_name}"));
-                    with(new ops.name_scope("Initializer"), scope2 =>
+                    with(ops.name_scope("Initializer"), scope2 =>
                     {
                         _initial_value = (initial_value as Func<Tensor>)();
                         _initial_value = ops.convert_to_tensor(_initial_value, name: "initial_value", dtype: dtype);

src/TensorFlowNET.Core/Variables/VariableScope.cs

@@ -39,7 +39,7 @@ namespace Tensorflow
             VariableAggregation aggregation= VariableAggregation.NONE)
         {
             string full_name = !string.IsNullOrEmpty(this._name) ? this._name + "/" + name : name;
-            return with(new ops.name_scope(null), scope =>
+            return with(ops.name_scope(null), scope =>
             {
                 if (dtype == TF_DataType.DtInvalid)
                     dtype = _dtype;

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

@@ -20,7 +20,7 @@ namespace Tensorflow
         private VariableScope _scope;
         private string _default_name;
         private object _values;
-        private ops.name_scope _current_name_scope;
+        private ops.NameScope _current_name_scope;
         private bool _auxiliary_name_scope;
         private PureVariableScope _cached_pure_variable_scope;
         private bool? _reuse;
@@ -68,7 +68,7 @@ namespace Tensorflow
 
         private VariableScope _enter_scope_uncached()
         {
-            ops.name_scope current_name_scope;
+            ops.NameScope current_name_scope;
             PureVariableScope pure_variable_scope = null;
             VariableScope entered_pure_variable_scope;
 
@@ -82,14 +82,14 @@ namespace Tensorflow
                 if(!string.IsNullOrEmpty(name_scope))
                     // Hack to reenter
                     name_scope += "/";
-                current_name_scope = new ops.name_scope(name_scope);
+                current_name_scope = ops.name_scope(name_scope);
             }
 
             if (_name != null || _scope != null)
             {
                 var name_scope = _name == null ? _scope._name.Split('/').Last() : _name;
                 if (name_scope != null || current_name_scope != null)
-                    current_name_scope = new ops.name_scope(name_scope);
+                    current_name_scope = ops.name_scope(name_scope);
                 current_name_scope.__enter__();
                 var current_name_scope_name = current_name_scope;
                 _current_name_scope = current_name_scope;
@@ -106,7 +106,7 @@ namespace Tensorflow
             }
             else
             {
-                current_name_scope = new ops.name_scope(_default_name);
+                current_name_scope = ops.name_scope(_default_name);
                 current_name_scope.__enter__();
                 string current_name_scope_name = current_name_scope;
                 _current_name_scope = current_name_scope;

src/TensorFlowNET.Core/ops.name_scope.cs

@@ -7,10 +7,14 @@ namespace Tensorflow
 {
     public partial class ops
     {
+        public static NameScope name_scope(string name,
+            string default_name = "",
+            object values = null) => new NameScope(name, default_name, values);
+
         /// <summary>
         /// Returns a context manager that creates hierarchical names for operations.
         /// </summary>
-        public class name_scope : IPython
+        public class NameScope : IPython
         {
             public string _name;
             public string _default_name;
@@ -20,7 +24,7 @@ namespace Tensorflow
             public string old_stack = "";
             private object _g_manager;
 
-            public name_scope(string name, string default_name = "", object values = null)
+            public NameScope(string name, string default_name = "", object values = null)
             {
                 _name = name;
                 _default_name = default_name;
@@ -58,7 +62,7 @@ namespace Tensorflow
             /// __enter__()
             /// </summary>
             /// <param name="ns"></param>
-            public static implicit operator string(name_scope ns)
+            public static implicit operator string(NameScope ns)
             {
                 return ns._name_scope;
             }

test/TensorFlowNET.UnitTest/NameScopeTest.cs

@@ -15,7 +15,7 @@ namespace TensorFlowNET.UnitTest
         [TestMethod]
         public void NestedNameScope()
         {
-            with(new ops.name_scope("scope1"), scope1 =>
+            with(new ops.NameScope("scope1"), scope1 =>
             {
                 name = scope1;
                 Assert.AreEqual("scope1", g._name_stack);
@@ -24,7 +24,7 @@ namespace TensorFlowNET.UnitTest
                 var const1 = tf.constant(1.0);
                 Assert.AreEqual("scope1/Const:0", const1.name);
 
-                with(new ops.name_scope("scope2"), scope2 =>
+                with(new ops.NameScope("scope2"), scope2 =>
                 {
                     name = scope2;
                     Assert.AreEqual("scope1/scope2", g._name_stack);