diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_adapter.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_adapter.py.swp
index eee1565b6..15e53574e 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_adapter.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_adapter.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_adapter.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_adapter.py
index 0e17a6c10..9c5bd69a6 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_adapter.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_adapter.py
@@ -835,7 +835,7 @@ def compute_loss(
 
     #texts = batch["supervisions"]["text"]
     texts = []
-    for utt_id in
+    for utt_id in 
     
     token_ids = sp.encode(texts, out_type=int)
     y = k2.RaggedTensor(token_ids).to(device)
@@ -1595,6 +1595,7 @@ def run_adapter(rank, world_size, args, wb=None):
             pl[text[0]] = ' '.join(text[1:])
     
     pl_texts = pl
+
     def remove_short_and_long_utt(c: Cut):
         return 1.0 <= c.duration <= 20.0