dont wait for send op under dygraph pp (#46209)

python/paddle/distributed/fleet/meta_parallel/pp_utils/p2p_communication.py

@@ -329,23 +329,21 @@ def _p2p_helper(tensor_send_next, tensor_send_prev, recv_prev, recv_next):
             for d in tensor_send_prev:
                 if _in_legacy_dygraph():
                     paddle.distributed.wait(d, use_calc_stream=True)
-                tasks.append(
                 send_partial(d,
                              dst=0,
                              nranks=mp_degree,
                              rank_id=mp_rank,
                              group=_hcg.send_prev_group,
-                                 use_calc_stream=False))
+                             use_calc_stream=False)
         else:
             if _in_legacy_dygraph():
                 paddle.distributed.wait(tensor_send_prev, use_calc_stream=True)
-            tasks.append(
             send_partial(tensor_send_prev,
                          dst=0,
                          nranks=mp_degree,
                          rank_id=mp_rank,
                          group=_hcg.send_prev_group,
-                             use_calc_stream=False))
+                         use_calc_stream=False)
 
     if tensor_recv_prev is not None:
         if isinstance(tensor_recv_prev, tuple):
@@ -371,23 +369,21 @@ def _p2p_helper(tensor_send_next, tensor_send_prev, recv_prev, recv_next):
             for d in tensor_send_next:
                 if _in_legacy_dygraph():
                     paddle.distributed.wait(d, use_calc_stream=True)
-                tasks.append(
                 send_partial(d,
                              dst=1,
                              nranks=mp_degree,
                              rank_id=mp_rank,
                              group=_hcg.send_next_group,
-                                 use_calc_stream=False))
+                             use_calc_stream=False)
         else:
             if _in_legacy_dygraph():
                 paddle.distributed.wait(tensor_send_next, use_calc_stream=True)
-            tasks.append(
             send_partial(tensor_send_next,
                          dst=1,
                          nranks=mp_degree,
                          rank_id=mp_rank,
                          group=_hcg.send_next_group,
-                             use_calc_stream=False))
+                         use_calc_stream=False)
 
     if tensor_recv_next is not None:
         if isinstance(tensor_recv_next, tuple):
@@ -438,6 +434,7 @@ def _p2p_helper(tensor_send_next, tensor_send_prev, recv_prev, recv_next):
                               group=mp_group,
                               use_calc_stream=True))
 
+    if in_dygraph_mode():
         for task in tasks:
             # wait partial all gather tasks
             if task is not None: