back to forward_static

vllm/model_executor/layers/layernorm.py

@@ -148,7 +148,7 @@ class RMSNorm(CustomOp):
 
     @staticmethod
     def forward_static(
-        self,
+        # self,
         x: torch.Tensor,
         variance_epsilon: float,
         hidden_size: int,
@@ -158,9 +158,9 @@ class RMSNorm(CustomOp):
         variance_size_override: int | None = None,
     ) -> torch.Tensor | tuple[torch.Tensor, torch.Tensor]:
         """PyTorch-native implementation equivalent to forward()."""
-        if not torch.compiler.is_compiling() and envs.VLLM_USE_OPT_OP:
-            return self.forward_cuda(x, residual)  
-        else:
+        # if not torch.compiler.is_compiling() and envs.VLLM_USE_OPT_OP:
+        #     return self.forward_cuda(x, residual)  
+        # else:
         orig_dtype = x.dtype
         x = x.to(torch.float32)
         if residual is not None: