diff --git a/egs/librispeech/ASR/pruned_transducer_stateless5/.conformer.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless5/.conformer.py.swp
new file mode 100644
index 000000000..47b4262c0
Binary files /dev/null and b/egs/librispeech/ASR/pruned_transducer_stateless5/.conformer.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless5/conformer.py b/egs/librispeech/ASR/pruned_transducer_stateless5/conformer.py
index 8d766dd37..2ef747973 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless5/conformer.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless5/conformer.py
@@ -695,8 +695,6 @@ class ConformerEncoder(nn.Module):
 
         outputs = []
         
-        layer_output = []
-
         for i, mod in enumerate(self.layers):
             output = mod(
                 output,
@@ -708,11 +706,9 @@ class ConformerEncoder(nn.Module):
             if i in self.aux_layers:
                 outputs.append(output)
 
-            layer_output.append(output)
-
         output = self.combiner(outputs)
 
-        return output, layer_output
+        return output
 
     @torch.jit.export
     def chunk_forward(
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer.py.swp
deleted file mode 100644
index 40457978b..000000000
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer.py.swp and /dev/null differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer.py b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer.py
index b54567c95..a175a24bb 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer.py
@@ -204,6 +204,7 @@ class Conformer(EncoderInterface):
         x = x.permute(1, 0, 2)  # (T, N, C) ->(N, T, C)
         
         layer_output = [x.permute(1, 0, 2) for x in layer_output]
+        
         x = self.layer_norm(1/6*(self.sigmoid(self.alpha[0])*layer_output[2] + \
                                  self.sigmoid(self.alpha[1])*layer_output[5] + \
                                  self.sigmoid(self.alpha[2])*layer_output[8] + \