fix bugs in pfednlp trainer

federatedscope/core/trainers/context.py

@@ -189,9 +189,9 @@ def setup_optimizer_and_scheduler(self, mode):
         setattr(
             self, f'{mode}_scheduler',
             get_scheduler(self.train_optimizer,
+                          **self.cfg.train.scheduler,
                           total_steps=total_steps,
-                          warmup_steps=warmup_steps,
-                          **self.cfg.train.scheduler))
+                          warmup_steps=warmup_steps))
 
     def track_mode(self, mode):
         self.mode_stack.append(mode)

federatedscope/nlp/aggregator/hfl_aggregator.py

@@ -63,7 +63,7 @@ def save_model(self, path, cur_round=-1):
 
         path = os.path.join(path, 'global')
         os.makedirs(path, exist_ok=True)
-        neighbor_ids = list(self.neighbors.keys())
+        neighbor_ids = sorted(list(self.neighbors.keys()))
         for i, model in enumerate(self.models):
             ckpt = {'cur_round': cur_round, 'model': model.state_dict()}
             torch.save(

federatedscope/nlp/dataset/preprocess/get_hfl_data.py

@@ -16,7 +16,6 @@ class HFLDataProcessor(object):
     def __init__(self, config, train_frac=0.9):
         self.data_dir = config.data.root
         self.datasets = config.data.datasets
-        self.total_client_num = config.federate.client_num
         self.num_grouped_clients = config.data.num_grouped_clients
         self.train_frac = train_frac
         self.all_train_data = []