fix #1585 (#1586)

* Fix Python3.

fluid/PaddleCV/deeplabv3+/train.py

@@ -34,7 +34,10 @@ def add_arguments():
     add_argument('parallel', bool, False, "using ParallelExecutor.")
     add_argument('use_gpu', bool, True, "Whether use GPU or CPU.")
     add_argument('num_classes', int, 19, "Number of classes.")
-    parser.add_argument('--enable_ce', action='store_true', help='If set, run the task with continuous evaluation logs.')
+    parser.add_argument(
+        '--enable_ce',
+        action='store_true',
+        help='If set, run the task with continuous evaluation logs.')
 
 
 def load_model():
@@ -52,7 +55,10 @@ def load_model():
     else:
         if args.num_classes == 19:
             fluid.io.load_params(
-                exe, dirname=args.init_weights_path, main_program=tp)
+                exe,
+                dirname="",
+                filename=args.init_weights_path,
+                main_program=tp)
         else:
             fluid.io.load_vars(
                 exe, dirname="", filename=args.init_weights_path, vars=myvars)
@@ -93,6 +99,7 @@ def get_cards(args):
     else:
         return args.num_devices
 
+
 CityscapeDataset = reader.CityscapeDataset
 parser = argparse.ArgumentParser()
 
@@ -203,8 +210,7 @@ if args.enable_ce:
     gpu_num = get_cards(args)
     print("kpis\teach_pass_duration_card%s\t%s" %
           (gpu_num, total_time / epoch_idx))
-    print("kpis\ttrain_loss_card%s\t%s" %
-            (gpu_num, train_loss))
+    print("kpis\ttrain_loss_card%s\t%s" % (gpu_num, train_loss))
 
 print("Training done. Model is saved to", args.save_weights_path)
 save_model()