[Perf][MoE][ROCm][Kimi-K2.5] Remove a redundant per-forward-pass dtype conversion of the routing bias parameter in DeepSeek-V2/V3 MoE

vllm/model_executor/models/deepseek_v2.py

@@ -351,6 +351,20 @@ def __init__(
             else torch.bfloat16
         )
 
+        # Align e_score_correction_bias dtype with the gate's output dtype so
+        # downstream routing kernels (e.g. aiter biased_grouped_topk) don't
+        # have to cast this constant parameter on every forward pass. We
+        # mutate `.data` in place to preserve the Parameter identity already
+        # captured by `self.experts` / the router. The weight loader uses
+        # `param.data.copy_(loaded_weight)`, which converts the loaded fp32
+        # checkpoint tensor into this dtype automatically at load time.
+        if self.gate.e_score_correction_bias is not None:
+            target_dtype = self.gate.out_dtype
+            if self.gate.e_score_correction_bias.dtype != target_dtype:
+                self.gate.e_score_correction_bias.data = (
+                    self.gate.e_score_correction_bias.data.to(target_dtype)
+                )
+
     def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
         num_tokens, hidden_dim = hidden_states.shape
         hidden_states = hidden_states.view(-1, hidden_dim)