diff --git a/tutel/examples/helloworld_ddp.py b/tutel/examples/helloworld_ddp.py
index 3ac8ad7f..86e80488 100755
--- a/tutel/examples/helloworld_ddp.py
+++ b/tutel/examples/helloworld_ddp.py
@@ -60,7 +60,6 @@
 class ExampleModel(torch.nn.Module):
     def __init__(self):
         super().__init__()
-        self._ddp_params_and_buffers_to_ignore = list()
 
         self._moe_layer = tutel_moe.moe_layer(
             gate_type = {'type': 'top', 'k': top_value, 'fp32_gate': args.fp32_gate},
@@ -81,15 +80,20 @@ def forward(self, input):
         result = F.log_softmax(torch.sum(result, dim=2), dim=1)
         return result
 
+    # Important setting 1: skip handling expert parameters by Pytorch DDP
     def add_param_to_skip_allreduce(self, param_name):
+        if not hasattr(self, '_ddp_params_and_buffers_to_ignore'):
+          self._ddp_params_and_buffers_to_ignore = list()
         self._ddp_params_and_buffers_to_ignore.append(param_name)
 
 
 model = ExampleModel().to(device)
 
+# Important setting 2: iterate all expert paramter object and move them into the array of setting 1
 for name, param in model.named_parameters():
     if hasattr(param, 'skip_allreduce'):
         model.add_param_to_skip_allreduce(name)
+
 if torch.distributed.is_initialized():
     model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank])