add moe_type assert

internlm/model/moe.py

@@ -44,7 +44,7 @@ class MoE(torch.nn.Module):
 
         super().__init__()
 
-        moe_impl = self.get_moe(getattr(gpc.config.model, "moe_type", None))
+        moe_impl = self.get_moe_impl(gpc.config.model.moe_type)
 
         if not hasattr(gpc.config, "moe"):
             gpc.config.moe = dict()
@@ -74,9 +74,11 @@ class MoE(torch.nn.Module):
             # coefficient is used for weighted sum of the output of expert and residual mlp
             self.coefficient = torch.nn.Linear(hidden_size, 2)
 
-    def get_moe(self, moe_type):
+    def get_moe_impl(self, moe_type):
         if moe_type is None or moe_type == "GShard":
             return GShardMOELayer
+        else:
+            assert False, "unsupported moe type"
 
     def forward(self, hidden_states, used_token=None):
         """MoE forward