Base Layer class sketonizing

src/TensorFlowNET.Keras/Constraints/ConstraintBase.cs

@@ -4,7 +4,7 @@ using System.Text;
 
 namespace Tensorflow.Keras.Constraints
 {
-    class ConstraintBase
+    public abstract class ConstraintBase
     {
     }
 }

src/TensorFlowNET.Keras/Engine/BaseLayer.cs

@@ -4,7 +4,7 @@ using System.Text;
 
 namespace Tensorflow.Keras.Engine
 {
-    class BaseLayer
+    public class Layer
     {
     }
 }

src/TensorFlowNET.Keras/Engine/BaseLayerUtils.cs

@@ -1,10 +1,24 @@
 using System;
 using System.Collections.Generic;
 using System.Text;
+using Tensorflow.Keras.Initializers;
+using Tensorflow.Keras.Metrics;
 
 namespace Tensorflow.Keras.Engine
 {
-    class BaseLayerUtils
+    public class BaseLayerUtils
     {
+        public static (Metric, Metric) create_mean_metric(Tensor value, string name = null) => throw new NotImplementedException();
+
+        public static VariableV1 make_variable(string name, TensorShape shape= null, TF_DataType dtype= TF_DataType.TF_FLOAT, Initializer initializer= null,
+                            bool trainable= true, string caching_device= null, bool validate_shape= true, Constraints.ConstraintBase constraint= null,
+                            bool use_resource= false, Graph[] collections= null, VariableSynchronization synchronization= VariableSynchronization.Auto,
+                            VariableAggregation aggregation= VariableAggregation.None) => throw new NotImplementedException();
+
+        public static Tensor[] collect_previous_mask(TensorArray input_tensors) => throw new NotImplementedException();
+
+        public bool have_all_keras_metadata(Tensor[] tensors) => throw new NotImplementedException();
+
+        public static dynamic generate_placeholders_from_shape(TensorShape shape) => throw new NotImplementedException();
     }
 }

src/TensorFlowNET.Keras/Initializer/BaseInitializer.cs

@@ -1,7 +0,0 @@
-namespace Keras.Initializer
-{
-    class BaseInitializer : IInitializer
-    {
-        public int seed;
-    }
-}

src/TensorFlowNET.Keras/Initializers/Initializer.cs

@@ -4,7 +4,7 @@ using System.Text;
 
 namespace Tensorflow.Keras.Initializers
 {
-    class Initializer
+    public abstract class Initializer
     {
     }
 }

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

@@ -23,7 +23,7 @@ using static Tensorflow.Binding;
 
 namespace Keras.Layers
 {
-    public class Dense : ILayer
+    public class Dense : Layer
     {
         RefVariable W;
         int units;
@@ -37,7 +37,7 @@ namespace Keras.Layers
             this.units = units;
             this.name = (string.IsNullOrEmpty(name) || string.IsNullOrWhiteSpace(name))?this.GetType().Name + "_" + this.GetType().GUID:name;
         }
-        public ILayer __build__(TensorShape input_shape, int seed = 1, float stddev = -1f)
+        public Layer __build__(TensorShape input_shape, int seed = 1, float stddev = -1f)
         {
             Console.WriteLine("Building Layer \"" + name + "\" ...");
             if (stddev == -1)

src/TensorFlowNET.Keras/Layers/ILayer.cs

@@ -1,12 +0,0 @@
-using Tensorflow;
-
-namespace Keras.Layers
-{
-    public interface ILayer
-    {
-        TensorShape __shape__();
-        ILayer __build__(TensorShape input_shape, int seed = 1, float stddev = -1f);
-        Tensor __call__(Tensor x);
-        TensorShape output_shape(TensorShape input_shape);
-    }
-}

src/TensorFlowNET.Keras/Layers/Layer.cs

@@ -0,0 +1,36 @@
+using System;
+using System.Collections.Generic;
+using Tensorflow;
+using Tensorflow.Keras.Constraints;
+using Tensorflow.Keras.Initializers;
+using Tensorflow.Keras.Regularizers;
+
+namespace Keras.Layers
+{
+    public abstract class Layer
+    {
+        public Layer(bool trainable = true, string name = null, string dtype = null, bool @dynamic = false, Dictionary<string, object> kwargs = null)
+        {
+
+        }
+
+        public void build(TensorShape shape) => throw new NotImplementedException();
+
+        public void call(Tensor[] inputs) => throw new NotImplementedException();
+
+        public void _add_trackable(dynamic trackable_object, bool trainable) => throw new NotImplementedException();
+
+        public void add_weight(string name= null, TensorShape shape= null, string dtype= null, Initializer initializer = null,
+                               Regularizer regularizer = null, bool? trainable = null, ConstraintBase constraint = null,
+                                dynamic partitioner= null, bool? use_resource= null, VariableSynchronization synchronization= VariableSynchronization.Auto,
+                                VariableAggregation aggregation= VariableAggregation.None, Dictionary<string, object> kwargs = null) => throw new NotImplementedException();
+
+        public Dictionary<string, object> get_config() => throw new NotImplementedException();
+
+        public Layer from_config(Dictionary<string, object> config) => throw new NotImplementedException();
+
+        public TensorShape compute_output_shape(TensorShape input_shape) => throw new NotImplementedException();
+
+        public dynamic compute_output_signature(dynamic input_signature) => throw new NotImplementedException();
+    }
+}

src/TensorFlowNET.Keras/Metrics/Metric.cs

@@ -4,7 +4,7 @@ using System.Text;
 
 namespace Tensorflow.Keras.Metrics
 {
-    class Metric
+    public abstract class Metric
     {
     }
 }

src/TensorFlowNET.Keras/Model.cs

@@ -26,20 +26,20 @@ namespace Tensorflow.Keras
     public class Model
     {
         public Tensor Flow;
-        List<ILayer> layer_stack;
+        List<Layer> layer_stack;
 
         public TensorShape InputShape;
 
         public Model()
         {
-            layer_stack = new List<ILayer>();
+            layer_stack = new List<Layer>();
         }
-        public Model Add(ILayer layer)
+        public Model Add(Layer layer)
         {
             layer_stack.Add(layer);
             return this;
         }
-        public Model Add(IEnumerable<ILayer> layers)
+        public Model Add(IEnumerable<Layer> layers)
         {
             layer_stack.AddRange(layers);
             return this;
@@ -83,9 +83,9 @@ namespace Tensorflow.Keras
             Flow = features;
             for (int i = 0; i < layer_stack.Count; i++)
             {
-                layer_stack[i].__build__(flow_shape);
-                flow_shape = layer_stack[i].output_shape(flow_shape);
-                Flow = layer_stack[i].__call__(Flow);
+                //layer_stack[i].build(flow_shape);
+                //flow_shape = layer_stack[i].output_shape(flow_shape);
+                //Flow = layer_stack[i].__call__(Flow);
             }
             var predictions = tf.sigmoid(tf.squeeze(Flow));
             

src/TensorFlowNET.Keras/Regularizers/Regularizer.cs

@@ -4,7 +4,7 @@ using System.Text;
 
 namespace Tensorflow.Keras.Regularizers
 {
-    class Regularizer
+    public class Regularizer
     {
     }
 }