Optimisation on ngram embedding

train_geocoder.py

@@ -130,7 +130,7 @@ if os.path.exists(EMBEDDING_FN):
   logging.info("Embedding loaded ! ")
 else:
   logging.info("Generating N-GRAM Embedding...")
-  embedding_weights = index.get_embedding_layer([index.encode(p) for p in np.concatenate((pairs_of_toponym.toponym.unique(),pairs_of_toponym.toponym_context.unique()))],dim= EMBEDDING_DIM,iter=WORDVEC_ITER)
+  embedding_weights = index.get_embedding_layer(np.concatenate((pairs_of_toponym.toponym.unique(),pairs_of_toponym.toponym_context.unique())),dim= EMBEDDING_DIM,iter=WORDVEC_ITER)
   np.save(EMBEDDING_FN,embedding_weights)
   logging.info("Embedding generated !")