import tensorflow as tf

                biases = tf.get_variable('biases', [output_node],
                                         initializer=tf.constant_initializer(0.0))

                layer_out = tf.matmul(prev_x, weights) + biases
            # Output of Network
            y = layer_out
            # Global step
            with tf.variable_scope('training_step', reuse=tf.AUTO_REUSE):
                global_step = tf.get_variable("global_step", [], 
                                              dtype=tf.int32,
                                              initializer=tf.constant_initializer(0), 
                                              trainable=False)
            # Loss value
            reg_item = tf.contrib.layers.l1_l2_regularizer(L1_reg,
