diff --git a/egs/librispeech/ASR/conformer_ctc2/.conformer.py.swp b/egs/librispeech/ASR/conformer_ctc2/.conformer.py.swp
index f9f11eb4d..aa55848ac 100644
Binary files a/egs/librispeech/ASR/conformer_ctc2/.conformer.py.swp and b/egs/librispeech/ASR/conformer_ctc2/.conformer.py.swp differ
diff --git a/egs/librispeech/ASR/conformer_ctc2/conformer.py b/egs/librispeech/ASR/conformer_ctc2/conformer.py
index 6a3739841..49b45ec7f 100644
--- a/egs/librispeech/ASR/conformer_ctc2/conformer.py
+++ b/egs/librispeech/ASR/conformer_ctc2/conformer.py
@@ -64,6 +64,7 @@ class Conformer(Transformer):
         dropout: float = 0.1,
         layer_dropout: float = 0.075,
         cnn_module_kernel: int = 31,
+        group_num: int = 0,
     ) -> None:
         super(Conformer, self).__init__(
             num_features=num_features,
@@ -101,12 +102,13 @@ class Conformer(Transformer):
             cnn_module_kernel,
         )
         self.encoder = ConformerEncoder(encoder_layer, num_encoder_layers)
-
+        
         self.group_num = group_num
-        self.group_layer_num = int(self.encoder_layers // self.group_num)
-        self.alpha = nn.Parameter(torch.rand(self.group_num))
-        self.sigmoid = nn.Sigmoid()
-        self.layer_norm = nn.LayerNorm(d_model)
+        if self.group_num != 0:
+            self.group_layer_num = int(self.encoder_layers // self.group_num)
+            self.alpha = nn.Parameter(torch.rand(self.group_num))
+            self.sigmoid = nn.Sigmoid()
+            self.layer_norm = nn.LayerNorm(d_model)
 
     def run_encoder(
         self,
@@ -146,8 +148,10 @@ class Conformer(Transformer):
         x, layer_outputs = self.encoder(
             x, pos_emb, src_key_padding_mask=mask, warmup=warmup
         )  # (T, N, C)
-
+        
+        if self.group_num != 0:
         # x = x.permute(1, 0, 2)  # (T, N, C) ->(N, T, C)
+        
 
         # return x, lengths
         return x, mask