diff --git a/egs/librispeech/ASR/.run_adapter.sh.swp b/egs/librispeech/ASR/.run_adapter.sh.swp
index da3bbf8ed..c40213102 100644
Binary files a/egs/librispeech/ASR/.run_adapter.sh.swp and b/egs/librispeech/ASR/.run_adapter.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 45364a317..7c49f0092 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 3a09386a6..fd77b7fbc 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
@@ -41,6 +41,7 @@ class TransformerEncoderAdapter(TransformerEncoder):
         for p in self.adapters.parameters():
             #p.data = nn.Parameter(torch.zeros(p.size()).to('cuda'))
             p.data = nn.Parameter(torch.randn(p.size()).to('cuda')/10000.)
+            print(p)
 
     def forward(self, x, padding_mask=None, layer=None, tgt_layer=None):
         x, layer_results = self.extract_features_with_adapter(