import tensorflow as tf

                    output_sizes = [
                        int((list_size+1)/2) + 1, 
                        int((list_size+1)/4) + 1,
                        1
                    ]
                    for i in range(len(output_sizes)):
                        expand_W = tf.get_variable("W_%d" % i, [current_size, output_sizes[i]])
                        expand_b = tf.get_variable("b_%d" % i, [output_sizes[i]])
                        output_data = tf.nn.bias_add(tf.matmul(output_data, expand_W), expand_b)
                        output_data = tf.nn.elu(output_data)
                        current_size = output_sizes[i]
                    #expand_W = tf.get_variable("final_W", [current_size, 1])
