text: import tensorflow as tf
  import numpy as np
  import sys,os
  
  modelName = sys.argv[1]
  sess = tf.Session()
  saver = tf.train.import_meta_graph(modelName + '.meta')
  saver.restore(sess, tf.train.latest_checkpoint('./', modelName + '.chk'))
  
  saved_vars = tf.get_collection('vars');
  var_x = saved_vars[0]
  y = saved_vars[1]
  keep_prob=saved_vars[2]
  h = saved_vars[3]
  
  test_data = np.genfromtxt('inData.csv', delimiter='|', dtype=np.float32)
  output = sess.run(h, feed_dict={var_x:test_data, keep_prob:1.0})
  N = np.shape(test_data)[0]
  np.savetxt("outData.csv", output, delimiter='|', fmt='%.5f')
  