diff --git a/GPT_SoVITS/AR/models/t2s_model.py b/GPT_SoVITS/AR/models/t2s_model.py
index 8e3c7fc..23da380 100644
--- a/GPT_SoVITS/AR/models/t2s_model.py
+++ b/GPT_SoVITS/AR/models/t2s_model.py
@@ -166,10 +166,10 @@ class T2STransformer:
         return x, k_cache, v_cache
 
     def decode_next_token(
-        self, x, k_cache: List[torch.Tensor], v_cache: List[torch.Tensor], attn_mask : torch.Tensor
+        self, x, k_cache: List[torch.Tensor], v_cache: List[torch.Tensor]
     ):
         for i in range(self.num_blocks):
-            x, k_cache[i], v_cache[i] = self.blocks[i].decode_next_token(x, k_cache[i], v_cache[i], attn_mask)
+            x, k_cache[i], v_cache[i] = self.blocks[i].decode_next_token(x, k_cache[i], v_cache[i])
         return x, k_cache, v_cache
 
 
@@ -554,7 +554,7 @@ class Text2SemanticDecoder(nn.Module):
             if idx == 0:
                 xy_dec, k_cache, v_cache = self.t2s_transformer.process_prompt(xy_pos, xy_attn_mask)
             else:
-                xy_dec, k_cache, v_cache = self.t2s_transformer.decode_next_token(xy_pos, k_cache, v_cache, xy_attn_mask)
+                xy_dec, k_cache, v_cache = self.t2s_transformer.decode_next_token(xy_pos, k_cache, v_cache)
 
             logits = self.ar_predict_layer(
                 xy_dec[:, -1]