fix dataset conflict issue in single machine simulation

paddle_fl/dataset/femnist.py

@@ -24,18 +24,18 @@ def train(trainer_id,inner_step,batch_size,count_by_step):
         tar_path = data_path + ".tar.gz"
         if not os.path.exists(target_path):
             os.system("mkdir trainer%d_data" % trainer_id)
-	if not os.path.exists(data_path):
-		print("Preparing data...")
-		if not os.path.exists(tar_path):
-			download("https://paddlefl.bj.bcebos.com/leaf/femnist_data.tar.gz",tar_path)
-		extract(tar_path,target_path)
-	def train_data():
-		train_file = open("./trainer%d_data/femnist_data/train/all_data_%d_niid_0_keep_0_train_9.json" % (trainer_id,trainer_id),'r')
-		json_train = json.load(train_file)
-		users = json_train["users"]
-		rand = random.randrange(0,len(users)) # random choose a user from each trainer
-		cur_user = users[rand]
-		print('training using '+cur_user)
+        if not os.path.exists(data_path):
+            print("Preparing data...")
+            if not os.path.exists(tar_path):
+               download("https://paddlefl.bj.bcebos.com/leaf/femnist_data.tar.gz",tar_path)
+               extract(tar_path,target_path)
+        def train_data():
+                train_file = open("./trainer%d_data/femnist_data/train/all_data_%d_niid_0_keep_0_train_9.json" % (trainer_id,trainer_id),'r')
+                json_train = json.load(train_file)
+                users = json_train["users"]
+                rand = random.randrange(0,len(users)) # random choose a user from each trainer
+                cur_user = users[rand]
+                print('training using '+cur_user)
                 train_images = json_train["user_data"][cur_user]['x']
                 train_labels = json_train["user_data"][cur_user]['y']
                 if count_by_step:
@@ -45,9 +45,9 @@ def train(trainer_id,inner_step,batch_size,count_by_step):
                         for i in xrange(len(train_images)):
                                 yield train_images[i], train_labels[i]
 
-		train_file.close()
+                train_file.close()
 
-	return train_data
+        return train_data
 
 def test(trainer_id,inner_step,batch_size,count_by_step):
         target_path = "trainer%d_data" % trainer_id
@@ -60,18 +60,18 @@ def test(trainer_id,inner_step,batch_size,count_by_step):
                 if not os.path.exists(tar_path):
                         download("https://paddlefl.bj.bcebos.com/leaf/femnist_data.tar.gz",tar_path)
                 extract(tar_path,target_path)
-	def test_data():
-		test_file = open("./trainer%d_data/femnist_data/test/all_data_%d_niid_0_keep_0_test_9.json" % (trainer_id,trainer_id), 'r')
-		json_test = json.load(test_file)
-		users = json_test["users"]
-		for user in users:
+        def test_data():
+                test_file = open("./trainer%d_data/femnist_data/test/all_data_%d_niid_0_keep_0_test_9.json" % (trainer_id,trainer_id), 'r')
+                json_test = json.load(test_file)
+                users = json_test["users"]
+                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)):
                                 yield test_images[i], test_labels[i]
 
-		test_file.close()
+                test_file.close()
 
-	return test_data
+        return test_data