import tensorflow as tf

        val_losses = np.array(val_losses)
        
    return (training_losses,val_losses, int(parameter_num))





"""
Test RNN graph 0 step
"""
def test_rnn(test_data_x,test_data_y, g, checkpoint, input_prob, output_prob, state_prob, num_test):
    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())

        test_data_yp = np.insert(test_data_y,0,0,axis=0)[:-1]

        "read the trained graph"
        g['saver'].restore(sess, checkpoint)

        
        "run the test points"
        #run the whole sequence, one class one total run       
        for index,(X, Y, YP) in enumerate(gen_batch(test_data_x, test_data_y,test_data_yp, 1, num_test, None)):
