def manual_eval(num_eval): with tf.Session(config=tf.ConfigProto(allow_soft_placement=True, log_device_placement=FLAGS.log_device_placement)) as sess: # Create model and load parameters. _, model_sig = graph_utils.get_model_signature(FLAGS) _, rev_nl_vocab, _, rev_cm_vocab = data_utils.load_vocab(FLAGS) _, dev_set, _ = load_data(use_buckets=False) eval_tools.manual_eval(model_sig, dev_set, rev_nl_vocab, FLAGS, FLAGS.model_dir, num_eval)
def manual_eval(): # Load vocabularies. nl_vocab_path = os.path.join(FLAGS.data_dir, "vocab%d.nl" % FLAGS.nl_vocab_size) cm_vocab_path = os.path.join(FLAGS.data_dir, "vocab%d.cm.ast" % FLAGS.cm_vocab_size) nl_vocab, rev_nl_vocab = data_utils.initialize_vocabulary(nl_vocab_path) cm_vocab, rev_cm_vocab = data_utils.initialize_vocabulary(cm_vocab_path) train_set, dev_set, _ = load_data() model = knn.KNNModel() model.train(train_set) eval_tools.manual_eval(model_name, dev_set, rev_nl_vocab, FLAGS, FLAGS.model_dir, num_eval=500)