diff --git a/examples/deep_learning_keras.py b/examples/deep_learning_keras.py
index fc672da75..eb247561e 100644
--- a/examples/deep_learning_keras.py
+++ b/examples/deep_learning_keras.py
@@ -4,9 +4,8 @@ import random
 
 import cytoolz
 import numpy
-from keras.layers import Sequential, LSTM, Dense, Embedding, Dropout
-from keras.wrappers import Bidirectional
-from keras import model_from_json
+from keras.models import Sequential, model_from_json
+from keras.layers import LSTM, Dense, Embedding, Dropout, Bidirectional
 import cPickle as pickle
 
 import spacy
@@ -127,17 +126,16 @@ def read_data(data_dir, limit=0):
 
 
 @plac.annotations(
-    language=("The language to train", "positional", None, str, ['en','de', 'zh']),
-    train_loc=("Location of training file or directory"),
-    dev_loc=("Location of development file or directory"),
+    train_dir=("Location of training file or directory"),
+    dev_dir=("Location of development file or directory"),
     model_dir=("Location of output model directory",),
     is_runtime=("Demonstrate run-time usage", "flag", "r", bool),
-    nr_hidden=("Number of hidden units", "flag", "H", int),
-    max_length=("Maximum sentence length", "flag", "L", int),
-    dropout=("Dropout", "flag", "d", float),
-    nr_epoch=("Number of training epochs", "flag", "i", int),
-    batch_size=("Size of minibatches for training LSTM", "flag", "b", int),
-    nr_examples=("Limit to N examples", "flag", "n", int)
+    nr_hidden=("Number of hidden units", "option", "H", int),
+    max_length=("Maximum sentence length", "option", "L", int),
+    dropout=("Dropout", "option", "d", float),
+    nb_epoch=("Number of training epochs", "option", "i", int),
+    batch_size=("Size of minibatches for training LSTM", "option", "b", int),
+    nr_examples=("Limit to N examples", "option", "n", int)
 )
 def main(model_dir, train_dir, dev_dir,
          is_runtime=False,