import tensorflow as tf

            o_d4 = self.general_deconv2d(o_me3, self.base_number_of_features, 3, stride = 2, padding = 'SAME', activation_function = 'relu', do_norm = False, name = name + '_deconv2d_4')
            o_me4 = tf.concat([o_d4, o_c1], 3) # Skip connection
            logits = tf.layers.conv2d(o_me4, self.args.num_classes, 1, 1, 'SAME', activation = None)
            prediction = tf.nn.softmax(logits, name = name + '_softmax')
            
            return logits, prediction
