bug fix

Author: yusugomori

.gitignore

@@ -11,4 +11,7 @@
 
 java/.idea/*
 java/java.iml
-java/out/*
+java/out/*
+
+data/*
+!data/.gitkeep

data/.gitkeep

@@ -103,14 +103,14 @@ public void train(int epochs, double[][] train_X, int[][] train_Y, boolean dropo
                         prev_W = hiddenLayers[i+1].W;
                     }
 
-                    dy = new double[hidden_layer_sizes[i]];
-                    hiddenLayers[i].backward(layer_inputs.get(i), dy, layer_inputs.get(i+1), prev_dy, prev_W, lr);
-
                     if(dropout) {
-                        for(int j=0; j<dy.length; j++) {
-                            dy[j] *= dropout_masks.get(i)[j];
+                        for(int j=0; j<prev_dy.length; j++) {
+                            prev_dy[j] *= dropout_masks.get(i)[j];
                         }
                     }
+
+                    dy = new double[hidden_layer_sizes[i]];
+                    hiddenLayers[i].backward(layer_inputs.get(i), dy, layer_inputs.get(i+1), prev_dy, prev_W, lr);
                 }
 
             }

java/src/DeepLearning/Dropout.java

@@ -61,7 +61,7 @@ def contrastive_divergence(self, lr=0.1, k=1, input=None):
         self.W += lr * (numpy.dot(self.input.T, ph_mean)
                         - numpy.dot(nv_samples.T, nh_means))
         self.vbias += lr * numpy.mean(self.input - nv_samples, axis=0)
-        self.hbias += lr * numpy.mean(ph_sample - nh_means, axis=0)
+        self.hbias += lr * numpy.mean(ph_mean - nh_means, axis=0)
 
         # cost = self.get_reconstruction_cross_entropy()
         # return cost