diff --git a/egs/librispeech/ASR/.prompt_tuning.sh.swp b/egs/librispeech/ASR/.prompt_tuning.sh.swp
index 5fee9c2d2..21b0ee6f9 100644
Binary files a/egs/librispeech/ASR/.prompt_tuning.sh.swp and b/egs/librispeech/ASR/.prompt_tuning.sh.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.data2vec_audio.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.data2vec_audio.py.swp
index d815409bc..0f674ee6d 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.data2vec_audio.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.data2vec_audio.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py
index ac6dda4ae..646335cb9 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py
@@ -490,7 +490,7 @@ class Data2VecAudioModel(BaseFairseqModel):
         
         ## for prompt tuning
         if prompt is not None:
-            if 0:
+            if 1:
                 conv_feat_all = torch.tensor([]).to(features.device)
                 length = 0
                 for i in range(padding_mask.size()[0]):