use dropout in CNNs

mlair/model_modules/convolutional_networks.py

@@ -104,11 +104,15 @@ class CNN(AbstractModelClass):
                                    kernel_initializer=self.kernel_initializer,
                                    kernel_regularizer=self.kernel_regularizer)(x_in)
         x_in = self.activation()(x_in)
+        if self.dropout is not None:
+            x_in = self.dropout(self.dropout_rate)(x_in)
         x_in = keras.layers.MaxPooling2D((25, 1), strides=(1, 1), padding='valid')(x_in)
         x_in = keras.layers.Conv2D(filters=64, kernel_size=(13, 1),
                                    kernel_initializer=self.kernel_initializer,
                                    kernel_regularizer=self.kernel_regularizer)(x_in)
         x_in = self.activation()(x_in)
+        if self.dropout is not None:
+            x_in = self.dropout(self.dropout_rate)(x_in)
         x_in = keras.layers.Flatten()(x_in)
         x_in = keras.layers.Dense(128, kernel_initializer=self.kernel_initializer,
                                   kernel_regularizer=self.kernel_regularizer)(x_in)