diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer.py.swp
index a6c6a19e3..f58bd1351 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer_randomcombine.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer_randomcombine.py.swp
index 81e7151f4..5ecc7d0ab 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer_randomcombine.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer_randomcombine.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer.py b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer.py
index 928610fd2..3a3a5e43c 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer.py
@@ -124,6 +124,11 @@ class Conformer(EncoderInterface):
         self.encoder = ConformerEncoder(encoder_layer, num_encoder_layers)
         self._init_state: List[torch.Tensor] = [torch.empty(0)]
 
+        self.group_size = 6
+        self.alpha = nn.Parameter(torch.rand(self.group_size))
+        self.sigmoid = nn.Sigmoid()
+        self.layer_norm = nn.LayerNorm(512)
+
     def forward(
         self, x: torch.Tensor, x_lens: torch.Tensor, warmup: float = 1.0
     ) -> Tuple[torch.Tensor, torch.Tensor]: