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 e1e94f4e6..047d94a8f 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 bd9eaa656..acc0a5e82 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
@@ -792,6 +792,7 @@ def compute_loss(
     batch: dict,
     is_training: bool,
     decode: bool = False,
+    pl_texts: dict = None,
 ) -> Tuple[Tensor, MetricsTracker]:
     """
     Compute transducer loss given the model and its inputs.
@@ -832,11 +833,10 @@ def compute_loss(
     batch_idx_train = params.batch_idx_train
     warm_step = params.warm_step
 
-    texts = batch["supervisions"]["text"]
-    print(texts)
-    exit()
+    #texts = batch["supervisions"]["text"]
+    texts = []
+    for utt_id in
     
-    #texts = batch["greedy pseudo text"]
     token_ids = sp.encode(texts, out_type=int)
     y = k2.RaggedTensor(token_ids).to(device)