feat: add Bidirectional layer

Author: “Wanglongzhi2001”

src/TensorFlowNET.Core/Keras/ArgsDefinition/Rnn/BidirectionalArgs.cs

@@ -0,0 +1,20 @@
+using Newtonsoft.Json;
+using System;
+using System.Collections.Generic;
+using System.Text;
+using Tensorflow.NumPy;
+
+namespace Tensorflow.Keras.ArgsDefinition
+{
+    public class BidirectionalArgs : AutoSerializeLayerArgs
+    {
+        [JsonProperty("layer")]
+        public ILayer Layer { get; set; }
+        [JsonProperty("merge_mode")]
+        public string? MergeMode { get; set; }
+        [JsonProperty("backward_layer")]
+        public ILayer BackwardLayer { get; set; }
+        public NDArray Weights { get; set; }
+    }
+
+}

src/TensorFlowNET.Core/Keras/ArgsDefinition/Rnn/LSTMArgs.cs

@@ -5,5 +5,10 @@ public class LSTMArgs : RNNArgs
         // TODO: maybe change the `RNNArgs` and implement this class.
         public bool UnitForgetBias { get; set; }
         public int Implementation { get; set; }
+
+        public LSTMArgs Clone()
+        {
+            return (LSTMArgs)MemberwiseClone();
+        }
     }
 }

src/TensorFlowNET.Core/Keras/ArgsDefinition/Rnn/RNNArgs.cs

@@ -40,5 +40,10 @@ public class RNNArgs : AutoSerializeLayerArgs
         public bool ZeroOutputForMask { get; set; } = false;
         [JsonProperty("recurrent_dropout")]
         public float RecurrentDropout { get; set; } = .0f;
+
+        public RNNArgs Clone()
+        {
+            return (RNNArgs)MemberwiseClone();
+        }
     }
 }

src/TensorFlowNET.Core/Keras/ArgsDefinition/Rnn/WrapperArgs.cs

@@ -0,0 +1,24 @@
+using Newtonsoft.Json;
+using System;
+using System.Collections.Generic;
+using System.Runtime.CompilerServices;
+using System.Text;
+
+
+namespace Tensorflow.Keras.ArgsDefinition
+{
+    public class WrapperArgs : AutoSerializeLayerArgs
+    {
+        [JsonProperty("layer")]
+        public ILayer Layer { get; set; }
+
+        public WrapperArgs(ILayer layer) 
+        { 
+            Layer = layer;
+        }
+
+        public static implicit operator WrapperArgs(BidirectionalArgs args)
+            => new WrapperArgs(args.Layer);
+    }
+
+}

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

@@ -258,7 +258,19 @@ public IRnnCell GRUCell(
             float dropout = 0f,
             float recurrent_dropout = 0f, 
             bool reset_after = true);
-            
+
+        /// <summary>
+        /// Bidirectional wrapper for RNNs.
+        /// </summary>
+        /// <param name="layer">`keras.layers.RNN` instance, such as `keras.layers.LSTM` or `keras.layers.GRU`</param>
+        /// automatically.</param>
+        /// <returns></returns>
+        public ILayer Bidirectional(
+                ILayer layer,
+                string merge_mode = "concat",
+                NDArray weights = null,
+                ILayer backward_layer = null);
+
         public ILayer Subtract();
     }
 }

src/TensorFlowNET.Keras/Layers/LayersApi.cs

@@ -908,6 +908,20 @@ public IRnnCell GRUCell(
                 ResetAfter = reset_after
             });
 
+        public ILayer Bidirectional(
+        ILayer layer,
+        string merge_mode = "concat",
+        NDArray weights = null,
+        ILayer backward_layer = null)
+        => new Bidirectional(new BidirectionalArgs
+        {
+            Layer = layer,
+            MergeMode = merge_mode,
+            Weights = weights,
+            BackwardLayer = backward_layer
+        });
+
+
         /// <summary>
         /// 
         /// </summary>

src/TensorFlowNET.Keras/Layers/Rnn/BaseWrapper.cs

@@ -0,0 +1,33 @@
+using System;
+using System.Collections.Generic;
+using System.Diagnostics;
+using System.Text;
+using Tensorflow.Keras.ArgsDefinition;
+using Tensorflow.Keras.Saving;
+
+namespace Tensorflow.Keras.Layers
+{
+    /// <summary>
+    /// Abstract wrapper base class. Wrappers take another layer and augment it in various ways.
+    /// Do not use this class as a layer, it is only an abstract base class.
+    /// Two usable wrappers are the `TimeDistributed` and `Bidirectional` wrappers.
+    /// </summary>
+    public abstract class Wrapper: Layer
+    {
+        public ILayer _layer;
+        public Wrapper(WrapperArgs args):base(args)
+        {
+            _layer = args.Layer;
+        }
+
+        public virtual void Build(KerasShapesWrapper input_shape)
+        {
+            if (!_layer.Built)
+            {
+                _layer.build(input_shape);
+            }
+            built = true;
+        }
+
+    }
+}