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)
