diff --git a/dygraph/cycle_gan/infer.py b/dygraph/cycle_gan/infer.py
index b0e2d45d3ed5c05ed82e67d724acd2cbe2f5fd0d..de70585f621ae51f1a88da3a1581d1f4266aecd8 100644
--- a/dygraph/cycle_gan/infer.py
+++ b/dygraph/cycle_gan/infer.py
@@ -52,8 +52,8 @@ def infer():
             os.makedirs(out_path)
         cycle_gan = Cycle_Gan("cycle_gan")
         save_dir = args.init_model 
-        restore, _ = fluid.dygraph.load_persistables(save_dir)
-        cycle_gan.load_dict(restore)
+        restore, _ = fluid.load_dygraph(save_dir)
+        cycle_gan.set_dict(restore)
         cycle_gan.eval()
         for file in glob.glob(args.input):
             print ("read %s" % file)
diff --git a/dygraph/cycle_gan/test.py b/dygraph/cycle_gan/test.py
index 19a2c7fb465659cb459d04c8967e3b205b19bb15..ba0b03ba2045102c8acab88a33eb16932db0e9fe 100644
--- a/dygraph/cycle_gan/test.py
+++ b/dygraph/cycle_gan/test.py
@@ -52,8 +52,8 @@ def test():
             os.makedirs(out_path)
         cycle_gan = Cycle_Gan("cycle_gan")
         save_dir = args.init_model + str(epoch)
-        restore, _ = fluid.dygraph.load_persistables(save_dir)
-        cycle_gan.load_dict(restore)
+        restore, _ = fluid.load_dygraph(save_dir)
+        cycle_gan.set_dict(restore)
         cycle_gan.eval()
         for data_A , data_B in zip(A_test_reader(), B_test_reader()): 
             A_name = data_A[1]
diff --git a/dygraph/cycle_gan/train.py b/dygraph/cycle_gan/train.py
index 59dc5c0c17d1b420cd933994bade47360ba33438..147b08dbf60b982b6f3e5d447a2a5af5bd526cb6 100644
--- a/dygraph/cycle_gan/train.py
+++ b/dygraph/cycle_gan/train.py
@@ -204,7 +204,7 @@ def train(args):
                     break
 
             if args.save_checkpoints:
-                fluid.dygraph.save_persistables(
+                fluid.save_dygraph(
                     cycle_gan.state_dict(),
                     args.output + "/checkpoints/{}".format(epoch))
 
diff --git a/dygraph/mnist/train.py b/dygraph/mnist/train.py
index 5bd5e0d8d46990133903847ba57f3ac54083d4eb..b067c94c9e61b40cce2bf2c378a222203fc4e004 100644
--- a/dygraph/mnist/train.py
+++ b/dygraph/mnist/train.py
@@ -150,8 +150,8 @@ def inference_mnist():
     with fluid.dygraph.guard(place):
         mnist_infer = MNIST("mnist")
         # load checkpoint
-        model_dict, _ = fluid.dygraph.load_persistables("save_dir")
-        mnist_infer.load_dict(model_dict)
+        model_dict, _ = fluid.load_dygraph("save_temp")
+        mnist_infer.set_dict(model_dict)
         print("checkpoint loaded")
 
         # start evaluate mode
@@ -245,7 +245,7 @@ def train_mnist(args):
             args.use_data_parallel and
             fluid.dygraph.parallel.Env().local_rank == 0)
         if save_parameters:
-            fluid.dygraph.save_persistables(mnist.state_dict(), "save_dir")
+            fluid.save_dygraph(mnist.state_dict(), "save_temp")
             print("checkpoint saved")
 
         inference_mnist()
diff --git a/dygraph/reinforcement_learning/actor_critic.py b/dygraph/reinforcement_learning/actor_critic.py
index c94b0a7432ea4d633a1aa8931f8954e63c08769f..f68a53f85dbc2e6b9e0743413c359eee76ee9e5f 100644
--- a/dygraph/reinforcement_learning/actor_critic.py
+++ b/dygraph/reinforcement_learning/actor_critic.py
@@ -200,5 +200,5 @@ with fluid.dygraph.guard():
             print("Solved! Running reward is now {} and "
                   "the last episode runs to {} time steps!".format(
                       running_reward, t))
-            fluid.dygraph.save_persistables(policy.state_dict(), args.save_dir)
+            fluid.save_dygraph(policy.state_dict(), args.save_dir)
             break
diff --git a/dygraph/reinforcement_learning/reinforce.py b/dygraph/reinforcement_learning/reinforce.py
index 84f9ac0246f31b4018b48d43fd9c90ad68a738f0..2a23b3450b65f8f213dc90f6c8ea22049a1c32f4 100644
--- a/dygraph/reinforcement_learning/reinforce.py
+++ b/dygraph/reinforcement_learning/reinforce.py
@@ -186,5 +186,5 @@ with fluid.dygraph.guard():
             print("Solved! Running reward is now {} and "
                   "the last episode runs to {} time steps!".format(
                       running_reward, t))
-            fluid.dygraph.save_persistables(policy.state_dict(), args.save_dir)
+            fluid.save_dygraph(policy.state_dict(), args.save_dir)
             break
diff --git a/dygraph/reinforcement_learning/test_actor_critic_load.py b/dygraph/reinforcement_learning/test_actor_critic_load.py
index 3f157aa9825cbc516aaa688456ff3683bcca1301..2ddbfd8ce017f02aa3f839eaca5ac805c27c24b0 100644
--- a/dygraph/reinforcement_learning/test_actor_critic_load.py
+++ b/dygraph/reinforcement_learning/test_actor_critic_load.py
@@ -174,8 +174,8 @@ with fluid.dygraph.guard():
         return returns
 
     running_reward = 10
-    model_dict, _ = fluid.dygraph.load_persistables(args.save_dir)
-    policy.load_dict(model_dict)
+    model_dict, _ = fluid.load_dygraph(args.save_dir)
+    policy.set_dict(model_dict)
 
     state, ep_reward = env.reset(), 0
     for t in range(1, 10000):  # Don't infinite loop while learning
diff --git a/dygraph/reinforcement_learning/test_reinforce_load.py b/dygraph/reinforcement_learning/test_reinforce_load.py
index fa468e9b950c6f9ec78bf5fc6866daf4343fd22a..db7245d1ee44b49950ae46660a67937e333318b4 100644
--- a/dygraph/reinforcement_learning/test_reinforce_load.py
+++ b/dygraph/reinforcement_learning/test_reinforce_load.py
@@ -161,8 +161,8 @@ with fluid.dygraph.guard():
 
     running_reward = 10
     state, ep_reward = env.reset(), 0
-    model_dict, _ = fluid.dygraph.load_persistables(args.save_dir)
-    policy.load_dict(model_dict)
+    model_dict, _ = fluid.load_dygraph(args.save_dir)
+    policy.set_dict(model_dict)
 
     for t in range(1, 10000):  # Don't infinite loop while learning
         state = np.array(state).astype("float32")
diff --git a/dygraph/resnet/train.py b/dygraph/resnet/train.py
index 19cda2ae64d8b68ee4451ef946b5a7fb657a6b16..5ce1d2466fac6c829001aee884c6b14c5a846ac2 100644
--- a/dygraph/resnet/train.py
+++ b/dygraph/resnet/train.py
@@ -380,7 +380,7 @@ def train_resnet():
                 args.use_data_parallel and
                 fluid.dygraph.parallel.Env().local_rank == 0)
             if save_parameters:
-                fluid.dygraph.save_persistables(resnet.state_dict(),
+                fluid.save_dygraph(resnet.state_dict(),
                                                 'resnet_params')
 
 
diff --git a/dygraph/sentiment/main.py b/dygraph/sentiment/main.py
index 279b34775648de4f6ae5481ca42313f909a261ed..b22f7ee7e71922db978332eedaba48145a79f28d 100644
--- a/dygraph/sentiment/main.py
+++ b/dygraph/sentiment/main.py
@@ -232,7 +232,7 @@ def train():
                     if steps % args.save_steps == 0:
                         save_path = "save_dir_" + str(steps)
                         print('save model to: ' + save_path)
-                        fluid.dygraph.save_persistables(cnn_net.state_dict(),
+                        fluid.save_dygraph(cnn_net.state_dict(),
                                                         save_path)
                 if enable_profile:
                         print('save profile result into /tmp/profile_file')
@@ -258,8 +258,8 @@ def infer():
         print('Do inferring ...... ')
         total_acc, total_num_seqs = [], []
 
-        restore, _ = fluid.dygraph.load_persistables(args.checkpoints)
-        cnn_net_infer.load_dict(restore)
+        restore, _ = fluid.load_dygraph(args.checkpoints)
+        cnn_net_infer.set_dict(restore)
         cnn_net_infer.eval()
 
         steps = 0