Remove _layers in Layer.

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

@@ -13,10 +13,10 @@ namespace Tensorflow.Keras
         List<INode> InboundNodes { get; }
         List<INode> OutboundNodes { get; }
         Tensors Apply(Tensors inputs, Tensor state = null, bool is_training = false);
-        List<IVariableV1> trainable_variables { get; }
-        List<IVariableV1> trainable_weights { get; }
-        List<IVariableV1> non_trainable_weights { get; }
-        Shape output_shape { get; }
+        List<IVariableV1> TrainableVariables { get; }
+        List<IVariableV1> TrainableWeights { get; }
+        List<IVariableV1> NonTrainableWeights { get; }
+        Shape OutputShape { get; }
         Shape BatchInputShape { get; }
         TF_DataType DType { get; }
         int count_params();

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

@@ -67,11 +67,11 @@ namespace Tensorflow
 
         public bool Trainable => throw new NotImplementedException();
 
-        public List<IVariableV1> trainable_variables => throw new NotImplementedException();
-        public List<IVariableV1> trainable_weights => throw new NotImplementedException();
-        public List<IVariableV1> non_trainable_weights => throw new NotImplementedException();
+        public List<IVariableV1> TrainableVariables => throw new NotImplementedException();
+        public List<IVariableV1> TrainableWeights => throw new NotImplementedException();
+        public List<IVariableV1> NonTrainableWeights => throw new NotImplementedException();
 
-        public Shape output_shape => throw new NotImplementedException();
+        public Shape OutputShape => throw new NotImplementedException();
 
         public Shape BatchInputShape => throw new NotImplementedException();
 

src/TensorFlowNET.Keras/Engine/Functional.GetConfig.cs

@@ -27,7 +27,7 @@ namespace Tensorflow.Keras.Engine
             };
 
             var node_conversion_map = new Dictionary<string, int>();
-            foreach (var layer in _layers)
+            foreach (var layer in _self_tracked_trackables)
             {
                 var kept_nodes = _should_skip_first_node(layer) ? 1 : 0;
                 foreach (var (original_node_index, node) in enumerate(layer.InboundNodes))
@@ -42,7 +42,7 @@ namespace Tensorflow.Keras.Engine
             }
 
             var layer_configs = new List<LayerConfig>();
-            foreach (var layer in _layers)
+            foreach (var layer in _self_tracked_trackables)
             {
                 var filtered_inbound_nodes = new List<NodeConfig>();
                 foreach (var (original_node_index, node) in enumerate(layer.InboundNodes))

src/TensorFlowNET.Keras/Engine/Functional.cs

@@ -65,13 +65,8 @@ namespace Tensorflow.Keras.Engine
             }
 
             // Keep track of the network's nodes and layers.
-            var (nodes, nodes_by_depth, layers, _) = MapGraphNetwork(inputs, outputs);
+            (NetworkNodes, NodesByDepth, _self_tracked_trackables, _) = MapGraphNetwork(inputs, outputs);
 
-            NetworkNodes = nodes;
-            NodesByDepth = nodes_by_depth;
-            if (_layers.Count == 0)
-                _layers = layers;
-            _self_tracked_trackables = layers;
             // Build self.input_names and self.output_names.
             _set_output_names();
 

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

@@ -5,8 +5,7 @@ namespace Tensorflow.Keras.Engine
 {
     public partial class Layer
     {
-        protected List<ILayer> _layers = new List<ILayer>();
-        public virtual List<ILayer> Layers => _layers;
+        public virtual List<ILayer> Layers => _self_tracked_trackables;
 
         protected void StackLayers(params ILayer[] layers)
         {

src/TensorFlowNET.Keras/Engine/Layer.cs

@@ -63,7 +63,7 @@ namespace Tensorflow.Keras.Engine
         public bool SupportsMasking { get; set; }
         protected List<IVariableV1> _trainable_weights;
 
-        public virtual List<IVariableV1> trainable_variables => _trainable_weights;
+        public virtual List<IVariableV1> TrainableVariables => _trainable_weights;
 
         protected List<IVariableV1> _non_trainable_weights;
         public List<IVariableV1> non_trainable_variables => _non_trainable_weights;
@@ -88,7 +88,7 @@ namespace Tensorflow.Keras.Engine
         public CallContext CallContext => callContext.Value;
         public Tensor[] input => inboundNodes[0].input_tensors;
         public Dictionary<int, List<INode>> NodesByDepth { get; set; }
-        public Shape output_shape => inboundNodes[0].Outputs.shape;
+        public Shape OutputShape => inboundNodes[0].Outputs.shape;
         protected List<ILayer> _self_tracked_trackables;
 
         public Layer(LayerArgs args)
@@ -250,7 +250,7 @@ namespace Tensorflow.Keras.Engine
                 return layer_utils.count_params(this, weights);
             return 0;
         }
-        List<IVariableV1> ILayer.trainable_weights
+        List<IVariableV1> ILayer.TrainableWeights
         {
             get
             {
@@ -258,7 +258,7 @@ namespace Tensorflow.Keras.Engine
             }
         }
 
-        List<IVariableV1> ILayer.non_trainable_weights
+        List<IVariableV1> ILayer.NonTrainableWeights
         {
             get
             {

src/TensorFlowNET.Keras/Engine/Model.Train.cs

@@ -34,7 +34,7 @@ namespace Tensorflow.Keras.Engine
             // self.optimizer.apply_gradients(zip(gradients, trainable_variables))
             // The _minimize call does a few extra steps unnecessary in most cases,
             // such as loss scaling and gradient clipping.
-            _minimize(tape, optimizer, loss, trainable_variables);
+            _minimize(tape, optimizer, loss, TrainableVariables);
             compiled_metrics.update_state(y, y_pred);
 
             return metrics.Select(x => (x.Name, x.result())).ToList();

src/TensorFlowNET.Keras/Engine/Model.cs

@@ -74,7 +74,7 @@ namespace Tensorflow.Keras.Engine
         public override List<ILayer> Layers
             => _flatten_layers(recursive: false, include_self: false).ToList();
 
-        public override List<IVariableV1> trainable_variables
+        public override List<IVariableV1> TrainableVariables
         {
             get
             {
@@ -88,13 +88,13 @@ namespace Tensorflow.Keras.Engine
                 foreach (var trackable_obj in _self_tracked_trackables)
                 {
                     if (trackable_obj.Trainable)
-                        variables.AddRange(trackable_obj.trainable_variables);
+                        variables.AddRange(trackable_obj.TrainableVariables);
                 }
 
-                foreach (var layer in _layers)
+                foreach (var layer in _self_tracked_trackables)
                 {
                     if (layer.Trainable)
-                        variables.AddRange(layer.trainable_variables);
+                        variables.AddRange(layer.TrainableVariables);
                 }
 
                 // variables.AddRange(_trainable_weights);

src/TensorFlowNET.Keras/Engine/Sequential.cs

@@ -75,7 +75,7 @@ namespace Tensorflow.Keras.Engine
         {
             built = false;
             var set_inputs = false;
-            if (_layers.Count == 0)
+            if (_self_tracked_trackables.Count == 0)
             {
                 if (layer is InputLayer)
                 {
@@ -128,7 +128,7 @@ namespace Tensorflow.Keras.Engine
 
         void _handle_deferred_layer_dependencies(params ILayer[] layers)
         {
-            _layers.AddRange(layers);
+            _self_tracked_trackables.AddRange(layers);
         }
 
         protected override Tensors Call(Tensors inputs, Tensor state = null, bool? training = null)
@@ -156,12 +156,12 @@ namespace Tensorflow.Keras.Engine
             ops.init_scope();
             var inputs = keras.Input(batch_input_shape: input_shape,
                 dtype: input_dtype,
-                name: $"{_layers[0].Name}_input");
+                name: $"{_self_tracked_trackables[0].Name}_input");
             Tensors layer_input = inputs;
             Tensors layer_output = null;
             Tensors outputs = null;
             List<INode> created_nodes = new List<INode>();
-            foreach (var layer in _layers)
+            foreach (var layer in _self_tracked_trackables)
             {
                 clear_previously_created_nodes(layer, _created_nodes);
                 layer_output = layer.Apply(layer_input);

src/TensorFlowNET.Keras/Saving/hdf5_format.cs

@@ -338,8 +338,8 @@ namespace Tensorflow.Keras.Saving
 
         public static List<IVariableV1> _legacy_weights(ILayer layer)
         {
-            var weights = layer.trainable_weights.Select(x => x).ToList();
-            weights.AddRange(layer.non_trainable_weights);
+            var weights = layer.TrainableWeights.Select(x => x).ToList();
+            weights.AddRange(layer.NonTrainableWeights);
             return weights;
         }
     }

src/TensorFlowNET.Keras/Utils/layer_utils.cs

@@ -103,7 +103,7 @@ namespace Tensorflow.Keras.Utils
                     print(string.Join("", range(line_length).Select(x => "_")));
             }
 
-            var trainable_count = count_params(model, model.trainable_variables);
+            var trainable_count = count_params(model, model.TrainableVariables);
             var non_trainable_count = count_params(model, model.non_trainable_variables);
 
             print($"Total params: {trainable_count + non_trainable_count}");
@@ -137,7 +137,7 @@ namespace Tensorflow.Keras.Utils
             var fields = new string[]
             {
                 $"{name} ({layer.GetType().Name})",
-                $"{layer.output_shape}",
+                $"{layer.OutputShape}",
                 $"{layer.count_params()}"
             };
 
@@ -164,7 +164,7 @@ namespace Tensorflow.Keras.Utils
             var fields = new string[]
             {
                 $"{name}({layer.GetType().Name})",
-                $"{layer.output_shape}",
+                $"{layer.OutputShape}",
                 $"{layer.count_params()}",
                 first_connection
             };