add default value in args

examples/train_nces.py

@@ -45,7 +45,6 @@ def start(args):
         synthesizer = ROCES(knowledge_base_path=args.kb, auto_train=False, k=5, max_length=48, proj_dim=128,
          drop_prob=0.1, num_heads=4, num_seeds=1, m=32, load_pretrained=args.load_pretrained, verbose=True)
     synthesizer.train(training_data, epochs=args.epochs, max_num_lps=args.max_num_lps, refinement_expressivity=args.refinement_expressivity)
-    print(synthesizer)
 
 if __name__ == '__main__':
     set_seed(42)
@@ -55,7 +54,7 @@ def start(args):
     parser.add_argument('--refinement_expressivity', type=float, default=0.9, help='The expressivity of the refinement operator during training data generation')
     parser.add_argument('--max_num_lps', type=int, default=20000, help='Maximum number of learning problems to generate if no training data is provided')
     parser.add_argument('--path_of_embeddings', type=str, default=None, help='Path to a csv file containing embeddings for the KB.')
-    parser.add_argument('--path_train_data', type=str, help='Path to training data')
+    parser.add_argument('--path_train_data', type=str, default=None, help='Path to training data')
     parser.add_argument('--epochs', type=int, default=50, help='Number of training epochs')
     parser.add_argument('--load_pretrained', type=str2bool, default=False, help='Whether to load the pretrained model')
     start(parser.parse_args())