ICallback

src/TensorFlowNET.Console/Tensorflow.Console.csproj

@@ -20,7 +20,7 @@
   </PropertyGroup>
 
   <ItemGroup>
-    <PackageReference Include="SciSharp.TensorFlow.Redist" Version="2.10.0" />
+    <PackageReference Include="SciSharp.TensorFlow.Redist" Version="2.11.0" />
   </ItemGroup>
 
   <ItemGroup>

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

@@ -0,0 +1,15 @@
+namespace Tensorflow.Keras.Engine;
+
+public interface ICallback
+{
+    Dictionary<string, List<float>> history { get; set; }
+    void on_train_begin();
+    void on_epoch_begin(int epoch);
+    void on_train_batch_begin(long step);
+    void on_train_batch_end(long end_step, Dictionary<string, float> logs);
+    void on_epoch_end(int epoch, Dictionary<string, float> epoch_logs);
+    void on_predict_begin();
+    void on_predict_batch_begin(long step);
+    void on_predict_batch_end(long end_step, Dictionary<string, Tensors> logs);
+    void on_predict_end();
+}

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

@@ -1,6 +1,65 @@
-namespace Tensorflow.Keras.Engine
+using Tensorflow.Functions;
+using Tensorflow.Keras.Losses;
+using Tensorflow.Keras.Saving;
+using Tensorflow.NumPy;
+
+namespace Tensorflow.Keras.Engine;
+
+public interface IModel : ILayer
 {
-    public interface IModel
-    {
-    }
+    void compile(IOptimizer optimizer = null,
+            ILossFunc loss = null,
+            string[] metrics = null);
+
+    void compile(string optimizer, string loss, string[] metrics);
+
+    ICallback fit(NDArray x, NDArray y,
+            int batch_size = -1,
+            int epochs = 1,
+            int verbose = 1,
+            float validation_split = 0f,
+            bool shuffle = true,
+            int initial_epoch = 0,
+            int max_queue_size = 10,
+            int workers = 1,
+            bool use_multiprocessing = false);
+
+    void save(string filepath,
+            bool overwrite = true,
+            bool include_optimizer = true,
+            string save_format = "tf",
+            SaveOptions? options = null,
+            ConcreteFunction? signatures = null,
+            bool save_traces = true);
+
+    void save_weights(string filepath, 
+        bool overwrite = true, 
+        string save_format = null, 
+        object options = null);
+
+    void load_weights(string filepath, 
+        bool by_name = false, 
+        bool skip_mismatch = false, 
+        object options = null);
+
+    void evaluate(NDArray x, NDArray y,
+            int batch_size = -1,
+            int verbose = 1,
+            int steps = -1,
+            int max_queue_size = 10,
+            int workers = 1,
+            bool use_multiprocessing = false,
+            bool return_dict = false);
+
+    Tensors predict(Tensor x,
+            int batch_size = -1,
+            int verbose = 0,
+            int steps = -1,
+            int max_queue_size = 10,
+            int workers = 1,
+            bool use_multiprocessing = false);
+
+    void summary(int line_length = -1, float[] positions = null);
+
+    IKerasConfig get_config();
 }

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

@@ -0,0 +1,13 @@
+namespace Tensorflow.Keras.Engine;
+
+public interface IOptimizer
+{
+    Tensor[] aggregate_gradients(IEnumerable<(Tensor, IVariableV1)> grads_and_vars);
+    Tensor[] clip_gradients(Tensor[] grads);
+    void apply_gradients((Tensor, ResourceVariable) grads_and_vars,
+            string name = null,
+            bool experimental_aggregate_gradients = true);
+    void apply_gradients(IEnumerable<(Tensor, ResourceVariable)> grads_and_vars,
+            string name = null,
+            bool experimental_aggregate_gradients = true);
+}

src/TensorFlowNET.Core/Keras/IKerasApi.cs

@@ -1,6 +1,7 @@
 using System;
 using System.Collections.Generic;
 using System.Text;
+using Tensorflow.Keras.Engine;
 using Tensorflow.Keras.Layers;
 using Tensorflow.Keras.Losses;
 using Tensorflow.Keras.Metrics;
@@ -13,5 +14,13 @@ public interface IKerasApi
         public ILossesApi losses { get; }
         public IMetricsApi metrics { get; }
         public IInitializersApi initializers { get; }
+
+        /// <summary>
+        /// `Model` groups layers into an object with training and inference features.
+        /// </summary>
+        /// <param name="input"></param>
+        /// <param name="output"></param>
+        /// <returns></returns>
+        public IModel Model(Tensors inputs, Tensors outputs, string name = null);
     }
 }

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

@@ -1,6 +1,4 @@
-using System.Collections.Generic;
-using Tensorflow.Keras.ArgsDefinition;
-using Tensorflow.Keras.Engine;
+using Tensorflow.Keras.Engine;
 using Tensorflow.Keras.Saving;
 using Tensorflow.Training;
 
@@ -15,7 +13,7 @@ public interface ILayer: IWithTrackable, IKerasConfigable
         List<ILayer> Layers { get; }
         List<INode> InboundNodes { get; }
         List<INode> OutboundNodes { get; }
-        Tensors Apply(Tensors inputs, Tensor state = null, bool is_training = false);
+        Tensors Apply(Tensors inputs, Tensor state = null, bool training = false);
         List<IVariableV1> TrainableVariables { get; }
         List<IVariableV1> TrainableWeights { get; }
         List<IVariableV1> NonTrainableWeights { get; }

src/TensorFlowNET.Core/Tensorflow.Binding.csproj

@@ -5,7 +5,7 @@
     <AssemblyName>Tensorflow.Binding</AssemblyName>
     <RootNamespace>Tensorflow</RootNamespace>
     <TargetTensorFlow>2.10.0</TargetTensorFlow>
-    <Version>0.100.4</Version>
+    <Version>1.0.0</Version>
     <LangVersion>10.0</LangVersion>
     <Nullable>enable</Nullable>
     <Authors>Haiping Chen, Meinrad Recheis, Eli Belash</Authors>
@@ -20,7 +20,7 @@
     <Description>Google's TensorFlow full binding in .NET Standard.
 Building, training and infering deep learning models.
 https://tensorflownet.readthedocs.io</Description>
-    <AssemblyVersion>0.100.4.0</AssemblyVersion>
+    <AssemblyVersion>1.0.0.0</AssemblyVersion>
     <PackageReleaseNotes>
 		tf.net 0.100.x and above are based on tensorflow native 2.10.0
 
@@ -38,7 +38,7 @@ https://tensorflownet.readthedocs.io</Description>
 		tf.net 0.7x.x aligns with TensorFlow v2.7.x native library.
 		tf.net 0.10x.x aligns with TensorFlow v2.10.x native library.
 	</PackageReleaseNotes>
-    <FileVersion>0.100.4.0</FileVersion>
+    <FileVersion>1.0.0.0</FileVersion>
     <PackageLicenseFile>LICENSE</PackageLicenseFile>
     <PackageRequireLicenseAcceptance>true</PackageRequireLicenseAcceptance>
     <SignAssembly>true</SignAssembly>

src/TensorFlowNET.Keras/Callbacks/CallbackList.cs

@@ -1,63 +1,63 @@
 using System;
 using System.Collections.Generic;
 using System.Text;
+using Tensorflow.Keras.Engine;
 
-namespace Tensorflow.Keras.Callbacks
+namespace Tensorflow.Keras.Callbacks;
+
+public class CallbackList
 {
-    public class CallbackList
-    {
-        List<ICallback> callbacks = new List<ICallback>();
-        public History History => callbacks[0] as History;
-
-        public CallbackList(CallbackParams parameters)
-        {
-            callbacks.Add(new History(parameters));
-            callbacks.Add(new ProgbarLogger(parameters));
-        }
-
-        public void on_train_begin()
-        {
-            callbacks.ForEach(x => x.on_train_begin());
-        }
-
-        public void on_epoch_begin(int epoch)
-        {
-            callbacks.ForEach(x => x.on_epoch_begin(epoch));
-        }
-
-        public void on_train_batch_begin(long step)
-        {
-            callbacks.ForEach(x => x.on_train_batch_begin(step));
-        }
-
-        public void on_train_batch_end(long end_step, Dictionary<string, float> logs)
-        {
-            callbacks.ForEach(x => x.on_train_batch_end(end_step, logs));
-        }
-
-        public void on_epoch_end(int epoch, Dictionary<string, float> epoch_logs)
-        {
-            callbacks.ForEach(x => x.on_epoch_end(epoch, epoch_logs));
-        }
-
-        public void on_predict_begin()
-        {
-            callbacks.ForEach(x => x.on_predict_begin());
-        }
-
-        public void on_predict_batch_begin(long step)
-        {
-            callbacks.ForEach(x => x.on_predict_batch_begin(step));
-        }
-
-        public void on_predict_batch_end(long end_step, Dictionary<string, Tensors> logs)
-        {
-            callbacks.ForEach(x => x.on_predict_batch_end(end_step, logs));
-        }
-
-        public void on_predict_end()
-        {
-            callbacks.ForEach(x => x.on_predict_end());
-        }
+    List<ICallback> callbacks = new List<ICallback>();
+    public History History => callbacks[0] as History;
+
+    public CallbackList(CallbackParams parameters)
+    {
+        callbacks.Add(new History(parameters));
+        callbacks.Add(new ProgbarLogger(parameters));
+    }
+
+    public void on_train_begin()
+    {
+        callbacks.ForEach(x => x.on_train_begin());
+    }
+
+    public void on_epoch_begin(int epoch)
+    {
+        callbacks.ForEach(x => x.on_epoch_begin(epoch));
+    }
+
+    public void on_train_batch_begin(long step)
+    {
+        callbacks.ForEach(x => x.on_train_batch_begin(step));
+    }
+
+    public void on_train_batch_end(long end_step, Dictionary<string, float> logs)
+    {
+        callbacks.ForEach(x => x.on_train_batch_end(end_step, logs));
+    }
+
+    public void on_epoch_end(int epoch, Dictionary<string, float> epoch_logs)
+    {
+        callbacks.ForEach(x => x.on_epoch_end(epoch, epoch_logs));
+    }
+
+    public void on_predict_begin()
+    {
+        callbacks.ForEach(x => x.on_predict_begin());
+    }
+
+    public void on_predict_batch_begin(long step)
+    {
+        callbacks.ForEach(x => x.on_predict_batch_begin(step));
+    }
+
+    public void on_predict_batch_end(long end_step, Dictionary<string, Tensors> logs)
+    {
+        callbacks.ForEach(x => x.on_predict_batch_end(end_step, logs));
+    }
+
+    public void on_predict_end()
+    {
+        callbacks.ForEach(x => x.on_predict_end());
     }
 }