diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.prompt_tuning.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.prompt_tuning.py.swp
index 30bc235e8..2dc1681ed 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.prompt_tuning.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.prompt_tuning.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/prompt_tuning.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/prompt_tuning.py
index 173404859..7d52e4240 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/prompt_tuning.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/prompt_tuning.py
@@ -1575,6 +1575,7 @@ def run_adapter(rank, world_size, args, wb=None):
         logging.info("Using DDP")
         model = DDP(model, device_ids=[rank], find_unused_parameters=True)
     
+    '''
     adapter_names = []
     adapter_param = []
     for n, p  in model.named_parameters():
@@ -1585,6 +1586,12 @@ def run_adapter(rank, world_size, args, wb=None):
             p.requires_grad = True
         else:
             p.requires_grad = False
+    '''
+    
+    for n, p in model.named_parameters():
+        p.requires_grad = False
+    
+    prompt = torch.nn.Parameter(torch.randn(50, 512))
     
     optimizer_adapter = ScaledAdam(
             adapter_param,