diff --git a/egs/librispeech/ASR/conformer_ctc2/.decode.py.swp b/egs/librispeech/ASR/conformer_ctc2/.decode.py.swp
index 120bac8a0..be51e9266 100644
Binary files a/egs/librispeech/ASR/conformer_ctc2/.decode.py.swp and b/egs/librispeech/ASR/conformer_ctc2/.decode.py.swp differ
diff --git a/egs/librispeech/ASR/conformer_ctc2/.train.py.swp b/egs/librispeech/ASR/conformer_ctc2/.train.py.swp
index 9e88101b7..bbe7892af 100644
Binary files a/egs/librispeech/ASR/conformer_ctc2/.train.py.swp and b/egs/librispeech/ASR/conformer_ctc2/.train.py.swp differ
diff --git a/egs/librispeech/ASR/conformer_ctc2/decode.py b/egs/librispeech/ASR/conformer_ctc2/decode.py
index f1a56fb05..72ae1fb10 100755
--- a/egs/librispeech/ASR/conformer_ctc2/decode.py
+++ b/egs/librispeech/ASR/conformer_ctc2/decode.py
@@ -321,6 +321,8 @@ def decode_one_batch(
     nnet_output, memory, memory_key_padding_mask = model(feature, supervisions)
     if type(nnet_output) == tuple:
         nnet_output = nnet_output[0]
+    print(type(nnet_output))
+    exit()
     # nnet_output is (N, T, C)
 
     supervision_segments = torch.stack(