diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_lora.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_lora.py.swp
index 914514cac..3b7f923d9 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_lora.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_lora.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_lora.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_lora.py
index d83874c08..2260aff8a 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_lora.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_lora.py
@@ -1591,17 +1591,18 @@ def run_adapter(rank, world_size, args, wb=None):
         logging.info("Using DDP")
         model = DDP(model, device_ids=[rank], find_unused_parameters=True)
     
-    lora_module = []
-    for i, module in enumerate(model.modules()):
+    lora_modules = []
+    for modules in model.modules():
         if isinstance(module, fairseq.modules.multihead_attention.MultiheadAttention):
-            for m in module.modules():
-                lora_module.append(LoRAHook(m))
+            for module in modules.modules():
+                lora_modules.append(LoRAHook(m))
     
     adapter_names = []
     adapter_param = []
+    for lora in lora_module
+    '''
     for n, p  in model.named_parameters():
         print(n)
-        '''
         if 'adapters' in n:# or 'joiner' in n or 'simple' in n or 'ctc' in n:
             adapter_names.append(n)
             adapter_param.append(p)
@@ -1609,7 +1610,7 @@ def run_adapter(rank, world_size, args, wb=None):
             p.requires_grad = True
         else:
             p.requires_grad = False
-        '''
+    '''
     optimizer_adapter = ScaledAdam(
             adapter_param,
             lr=params.adapter_lr,