Add LeakyReLU layer.

Author: Oceania2018

src/TensorFlowNET.Core/Keras/ArgsDefinition/LeakyReLUArgs.cs

@@ -0,0 +1,14 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Keras.ArgsDefinition
+{
+    public class LeakyReLUArgs : LayerArgs
+    {
+        /// <summary>
+        /// Negative slope coefficient.
+        /// </summary>
+        public float Alpha { get; set; } = 0.3f;
+    }
+}

src/TensorFlowNET.Keras/Layers/LayersApi.cs

@@ -315,6 +315,17 @@ public Tensor max_pooling2d(Tensor inputs,
             return layer.Apply(inputs);
         }
 
+        /// <summary>
+        /// Leaky version of a Rectified Linear Unit.
+        /// </summary>
+        /// <param name="alpha">Negative slope coefficient.</param>
+        /// <returns></returns>
+        public Layer LeakyReLU(float alpha = 0.3f)
+            => new LeakyReLU(new LeakyReLUArgs
+            {
+                Alpha = alpha
+            });
+
         public Layer LSTM(int units,
             Activation activation = null,
             Activation recurrent_activation = null,

src/TensorFlowNET.Keras/Layers/LeakyReLU.cs

@@ -0,0 +1,27 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+using Tensorflow.Keras.ArgsDefinition;
+using Tensorflow.Keras.Engine;
+using static Tensorflow.Binding;
+
+namespace Tensorflow.Keras.Layers
+{
+    /// <summary>
+    /// Leaky version of a Rectified Linear Unit.
+    /// </summary>
+    public class LeakyReLU : Layer
+    {
+        LeakyReLUArgs args;
+        float alpha => args.Alpha;
+        public LeakyReLU(LeakyReLUArgs args) : base(args)
+        {
+            this.args = args;
+        }
+
+        protected override Tensors Call(Tensors inputs, Tensor state = null, bool is_training = false)
+        {
+            return tf.nn.leaky_relu(inputs, alpha: alpha);
+        }
+    }
+}

test/TensorFlowNET.UnitTest/Keras/ActivationTest.cs

@@ -0,0 +1,26 @@
+using Microsoft.VisualStudio.TestTools.UnitTesting;
+using System;
+using System.Collections.Generic;
+using System.Text;
+using NumSharp;
+using static Tensorflow.KerasApi;
+using Tensorflow;
+
+namespace TensorFlowNET.UnitTest.Keras
+{
+    [TestClass]
+    public class ActivationTest : EagerModeTestBase
+    {
+        [TestMethod]
+        public void LeakyReLU()
+        {
+            var layer = keras.layers.LeakyReLU();
+            Tensor output = layer.Apply(np.array(-3.0f, -1.0f, 0.0f, 2.0f));
+            var outputArray = output.ToArray<float>();
+            assertFloat32Equal(-0.9f, outputArray[0], "Not equal");
+            assertFloat32Equal(-0.3f, outputArray[1], "Not equal");
+            assertFloat32Equal(0.0f, outputArray[2], "Not equal");
+            assertFloat32Equal(2.0f, outputArray[3], "Not equal");
+        }
+    }
+}