diff --git a/vllm/model_executor/layers/fused_moe/layer.py b/vllm/model_executor/layers/fused_moe/layer.py
index 4a6a3b95ec7f..ee3d041464d7 100644
--- a/vllm/model_executor/layers/fused_moe/layer.py
+++ b/vllm/model_executor/layers/fused_moe/layer.py
@@ -372,10 +372,18 @@ def apply(
         logical_replica_count: Optional[torch.Tensor] = None,
     ) -> torch.Tensor:
         if enable_eplb:
-            assert expert_load_view is not None
-            assert logical_to_physical_map is not None
-            assert logical_replica_count is not None
-            assert isinstance(layer, FusedMoE)
+            if expert_load_view is None:
+                raise ValueError(
+                    "expert_load_view must be provided when enable_eplb is True")
+            if logical_to_physical_map is None:
+                raise ValueError(
+                    "logical_to_physical_map must be provided when enable_eplb is True")
+            if logical_replica_count is None:
+                raise ValueError(
+                    "logical_replica_count must be provided when enable_eplb is True")
+            if not isinstance(layer, FusedMoE):
+                raise TypeError(
+                    f"Expected layer to be FusedMoE, but got {type(layer)}")
 
         return self.forward(
             x=x,
@@ -421,6 +429,19 @@ def forward_cuda(
         logical_to_physical_map: Optional[torch.Tensor] = None,
         logical_replica_count: Optional[torch.Tensor] = None,
     ) -> torch.Tensor:
+        if enable_eplb:
+            if expert_load_view is None:
+                raise ValueError(
+                    "expert_load_view must be provided when enable_eplb is True")
+            if logical_to_physical_map is None:
+                raise ValueError(
+                    "logical_to_physical_map must be provided when enable_eplb is True")
+            if logical_replica_count is None:
+                raise ValueError(
+                    "logical_replica_count must be provided when enable_eplb is True")
+            if not isinstance(layer, FusedMoE):
+                raise TypeError(
+                    f"Expected layer to be FusedMoE, but got {type(layer)}")
 
         topk_weights, topk_ids = FusedMoE.select_experts(
             hidden_states=x,
@@ -1411,10 +1432,10 @@ def process_chunk(chunk_start, chunk_end, skip_result_store=False):
                     >= chunk_size)
             assert (self.batched_router_logits.size(0)  # type: ignore
                     >= chunk_size)
-            staged_hidden_states = self.batched_hidden_states[:
-                                                              chunk_size, :]  # type: ignore
-            staged_router_logits = self.batched_router_logits[:
-                                                              chunk_size, :]  # type: ignore
+            staged_hidden_states = self.batched_hidden_states[
+                :chunk_size, :]  # type: ignore
+            staged_router_logits = self.batched_router_logits[
+                :chunk_size, :]  # type: ignore
             staged_hidden_states.copy_(hidden_states, non_blocking=True)
             staged_router_logits.copy_(router_logits, non_blocking=True)