[Bugfix] Define router_logits_dtype for remaining MoE models (#33737)

Signed-off-by: mgoin <mgoin64@gmail.com>

vllm/model_executor/models/afmoe.py

@@ -142,6 +142,7 @@ class AfmoeMoE(nn.Module):
             e_score_correction_bias=self.expert_bias,
             enable_eplb=self.enable_eplb,
             num_redundant_experts=self.n_redundant_experts,
+            router_logits_dtype=torch.float32,
         )
 
     def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:

vllm/model_executor/models/bailing_moe.py

@@ -300,6 +300,7 @@ class BailingMoE(nn.Module):
             num_expert_group=self.n_group,
             topk_group=self.topk_group,
             use_grouped_topk=self.use_grouped_topk,
+            router_logits_dtype=self.router_dtype,
         )
 
     def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:

vllm/model_executor/models/flex_olmo.py

@@ -71,7 +71,6 @@ class FlexOlmoMoE(nn.Module):
             prefix=f"{prefix}.gate",
         )
 
-        # Gate always runs at half / full precision for now.
         self.experts = FusedMoE(
             num_experts=hf_config.num_experts,
             top_k=hf_config.num_experts_per_tok,
@@ -82,6 +81,7 @@ class FlexOlmoMoE(nn.Module):
             quant_config=None,
             tp_size=tp_size,
             prefix=f"{prefix}.experts",
+            router_logits_dtype=torch.float32,
         )
 
         self.top_k = hf_config.num_experts_per_tok

vllm/model_executor/models/longcat_flash.py

@@ -236,9 +236,9 @@ class FlashMLP(nn.Module):
 class LongcatRouter(nn.Module):
     def __init__(
         self,
-        config,
-        zero_expert_num=0,
-        rounter_params_dtype=torch.bfloat16,
+        config: FlashConfig,
+        zero_expert_num: int,
+        rounter_params_dtype: torch.dtype,
         prefix: str = "",
     ):
         super().__init__()
@@ -309,6 +309,7 @@ class LongcatMoe(nn.Module):
             prefix=f"{prefix}.experts",
             enable_eplb=enable_eplb,
             routed_scaling_factor=config.routed_scaling_factor,
+            router_logits_dtype=self.rounter_params_dtype,
         )
 
     def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:

vllm/model_executor/models/mimo_v2_flash.py

@@ -174,6 +174,7 @@ class MiMoV2MoE(nn.Module):
             num_expert_group=config.n_group,
             topk_group=config.topk_group,
             scoring_func="sigmoid",
+            router_logits_dtype=self.gate_dtype,
         )
 
     def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:

vllm/model_executor/models/step3p5.py

@@ -388,6 +388,7 @@ class FusedMoEBlock(nn.Module):
             routed_scaling_factor=config.moe_router_scaling_factor,
             enable_eplb=self.enable_eplb,
             num_redundant_experts=self.n_redundant_experts,
+            router_logits_dtype=torch.float32,
         )
 
     def forward(self, hidden_states: torch.Tensor) -> torch.Tensor: