update comment

megatron/model/module.py

@@ -109,9 +109,8 @@ class MegatronModule(torch.nn.Module):
                 torch.distributed.all_reduce(self.word_embeddings_weight().data,
                                              group=mpu.get_embedding_group())
 
-            # All-reduce other embeddings as well as necessary. The last stage
-            # does not have these other embeddings, so just create placeholder
-            # tensors of the right shape with all zeros.
+            # Ensure that encoder(first stage) and decoder(split stage) position 
+            # embeddings have the same initial parameter values
             # NOTE: We don't currently support T5 with the interleaved schedule.
             if mpu.is_rank_in_position_embedding_group() and \
                     args.pipeline_model_parallel_split_rank is not None: