fix compatibility issue

paddle_fl/dataset/femnist.py

@@ -39,10 +39,10 @@ def train(trainer_id,inner_step,batch_size,count_by_step):
                 train_images = json_train["user_data"][cur_user]['x']
                 train_labels = json_train["user_data"][cur_user]['y']
                 if count_by_step:
-                        for i in xrange(inner_step*batch_size):
+                        for i in range(inner_step*batch_size):
                                 yield train_images[i%(len(train_images))], train_labels[i%(len(train_images))]
                 else:
-                        for i in xrange(len(train_images)):
+                        for i in range(len(train_images)):
                                 yield train_images[i], train_labels[i]
 
                 train_file.close()
@@ -67,7 +67,7 @@ def test(trainer_id,inner_step,batch_size,count_by_step):
                 for user in users:
                         test_images = json_test['user_data'][user]['x']
                         test_labels = json_test['user_data'][user]['y']
-                        for i in xrange(len(test_images)):
+                        for i in range(len(test_images)):
                                 yield test_images[i], test_labels[i]
 
                 test_file.close()

paddle_fl/examples/femnist_demo/fl_trainer.py

@@ -40,7 +40,7 @@ def train_test(train_test_program, train_test_feed, train_test_reader):
 epoch_id = 0
 step = 0
 epoch = 3000
-count_by_step = False
+count_by_step = True
 if count_by_step:
 	output_folder = "model_node%d" % trainer_id
 else: 
@@ -66,7 +66,7 @@ while not trainer.stop():
             acc = trainer.run(feeder.feed(data), fetch=["accuracy_0.tmp_0"])
             step += 1
             count += 1
-	    print(count)
+            print(count)
             if count % trainer._step == 0: 
                 break
     # print("acc:%.3f" % (acc[0]))
@@ -81,5 +81,5 @@ while not trainer.stop():
 
     print("Test with epoch %d, accuracy: %s" % (epoch_id, acc_val))
     if trainer_id == 0:  
-    	save_dir = (output_folder + "/epoch_%d") % epoch_id
+        save_dir = (output_folder + "/epoch_%d") % epoch_id
         trainer.save_inference_program(output_folder)