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 eval(data_set, model_sig=None, verbose=True):
with tf.Session(config=tf.ConfigProto(allow_soft_placement=True,
log_device_placement=FLAGS.log_device_placement)) as sess:
if model_sig is None:
_, model_sig = graph_utils.get_model_signature(FLAGS)
print("evaluate " + model_sig + "...")
_, rev_nl_vocab, _, rev_cm_vocab = data_utils.load_vocab(FLAGS)
return eval_tools.eval_set(model_sig, data_set, rev_nl_vocab, FLAGS,
verbose=verbose)