diff --git a/egs/aishell/ASR/conformer_ctc/.transformer.py.swp b/egs/aishell/ASR/conformer_ctc/.transformer.py.swp
index 34ffe002d..a0a71f3c9 100644
Binary files a/egs/aishell/ASR/conformer_ctc/.transformer.py.swp and b/egs/aishell/ASR/conformer_ctc/.transformer.py.swp differ
diff --git a/egs/aishell/ASR/conformer_ctc/transformer.py b/egs/aishell/ASR/conformer_ctc/transformer.py
index 982abc6c0..90aca750d 100644
--- a/egs/aishell/ASR/conformer_ctc/transformer.py
+++ b/egs/aishell/ASR/conformer_ctc/transformer.py
@@ -113,6 +113,7 @@ class Transformer(nn.Module):
         #    num_layers=num_encoder_layers,
         #    norm=encoder_norm,
         #)
+        print(encoder_norm)
         self.encoder = TransfEncoder(
             encoder_layer=encoder_layer,
             num_layers=num_encoder_layers,
@@ -491,10 +492,10 @@ class TransfEncoder(nn.TransformerEncoder):
                 output = torch._nested_tensor_from_mask(output, src_key_padding_mask.logical_not(), mask_check=False)
                 src_key_padding_mask_for_layers = None
         
-        outputs = []
+        layer_outputs = []
         for mod in self.layers:
             output = mod(output, src_mask=mask, src_key_padding_mask=src_key_padding_mask_for_layers)
-            outputs.append(output)
+            layer_outputs.append(output)
 
         if convert_to_nested:
             output = output.to_padded_tensor(0.)