import tensorflow as tf

            # a. Create convolution/pooling layers = conv + drop + pool + conv + drop + pool + conv + pool + conv + drop  
            self.conv1 = tf.layers.conv2d(self.X, 
                                          self.config.cifar10_cnn["num_filters"], 
                                          self.config.cifar10_cnn["filter_size"], 
                                          padding='same', activation=tf.nn.relu)
            self.drop1 = tf.layers.dropout(self.conv1, self.config.cifar10_cnn["keep_prob"], training=self.train)
            self.pool1 = tf.layers.max_pooling2d(self.drop1, 2, 2)

            self.conv2 = tf.layers.conv2d(self.pool1, 
                                          self.config.cifar10_cnn["num_filters"], 
                                          self.config.cifar10_cnn["filter_size"],
                                          padding='same', activation=tf.nn.relu)
