Merge pull request cbovar#133 from cbovar/Fix_Dropout

Fix Dropout exception

Author: cbovar

src/ConvNetSharp.Core.Tests/ConvNetSharp.Core.Tests.csproj

@@ -46,6 +46,7 @@
   </ItemGroup>
   <ItemGroup>
     <Compile Include="ConvLayerTests.cs" />
+    <Compile Include="DropoutLayerTests.cs" />
     <Compile Include="FullyConnLayerTests.cs" />
     <Compile Include="GradientCheckTools.cs" />
     <Compile Include="PoolLayerTests.cs" />

src/ConvNetSharp.Core.Tests/DropoutLayerTests.cs

@@ -0,0 +1,47 @@
+using System.Linq;
+using ConvNetSharp.Core.Layers;
+using ConvNetSharp.Volume;
+using ConvNetSharp.Volume.Double;
+using Microsoft.VisualStudio.TestTools.UnitTesting;
+
+namespace ConvNetSharp.Core.Tests
+{
+    [TestClass]
+    public class DropoutLayerTests
+    {
+        [TestMethod]
+        public void Learning()
+        {
+            var n = 1000000;
+            var dropProbability = 0.2;
+            var layer = new DropoutLayer<double>(dropProbability);
+            layer.Init(1, 1, n);
+
+            var input = BuilderInstance.Volume.From(new double[n].Populate(1.0), new Shape(1, 1, n, 1));
+            var result = layer.DoForward(input, true);
+
+            var val = result.ToArray().First(o => o != 0.0);
+            var scalingFactor = 1.0 / (1.0 - dropProbability);
+            Assert.AreEqual(scalingFactor, val); // Make sure output is scaled during learning
+
+            var average = result.ToArray().Average();
+            var measuredProba = average * dropProbability;
+            Assert.AreEqual(dropProbability, measuredProba, 0.001); // Make sure dropout really happened
+        }
+
+        [TestMethod]
+        public void NotLearning()
+        {
+            var n = 1000000;
+            var dropProbability = 0.2;
+            var layer = new DropoutLayer<double>(dropProbability);
+            layer.Init(1, 1, n);
+
+            var input = BuilderInstance.Volume.From(new double[n].Populate(1.0), new Shape(1, 1, n, 1));
+            var result = layer.DoForward(input, false);
+
+            var average = result.ToArray().Average();
+            Assert.AreEqual(1.0, average); // Let everything go through
+        }
+    }
+}

src/ConvNetSharp.Core/Layers/DropoutLayer.cs

@@ -24,7 +24,7 @@ public override void Backward(Volume<T> outputGradient)
 
             this.InputActivationGradients.Clear();
 
-            this.OutputActivation.DropoutGradient(this.InputActivation, this.OutputActivationGradients, this.InputActivationGradients, this.DropProbability);
+            this.OutputActivation.DropoutGradient(this.InputActivation, this.OutputActivationGradients, this.DropProbability, this.InputActivationGradients);
         }
 
         protected override Volume<T> Forward(Volume<T> input, bool isTraining = false)