support reduce_avg for sharding v2 (#62623)

python/paddle/distributed/fleet/meta_optimizers/dygraph_optimizer/dygraph_sharding_optimizer.py

@@ -513,6 +513,14 @@ def __init__(self, optimizer, hcg):
         self.pp_overlap = pp_config.sharding_comm_overlap
         self.pp_release_grads = pp_config.release_gradients
 
+        # Check nccl reduce_avg setting
+        self.use_reduce_avg = sharding_config.use_reduce_avg
+        if self.use_reduce_avg and (not is_avg_reduce_op_supported()):
+            self.use_reduce_avg = False
+            warnings.warn(
+                "nccl reduce_avg requires paddle compiled with cuda and nccl>=2.10.0, please check compilation setups."
+            )
+
         self._build_comm_buffers(acc_steps)
         # NOTE(shenliang03): Sort the comm_buffers by dst rank,
         # it will improve the performance in reduce communicate. Default
@@ -579,6 +587,7 @@ def _build_comm_buffers(self, acc_steps, group_size=256 * 1024 * 1024):
                 acc_steps,
                 act=HOOK_ACTION.REDUCE_SCATTER,
                 release_grads=self.pp_release_grads,
+                use_reduce_avg=self.use_reduce_avg,
             )
             self._comm_buffer_list.append(buffer)