[NewComm] Set new communication library as default.

paddle/phi/core/flags.cc

@@ -1338,13 +1338,13 @@ PHI_DEFINE_EXPORTED_int32(
  * Communication library related FLAG
  * Name: FLAGS_dynamic_static_unified_comm
  * Since Version: 2.5
- * Value Range: bool, default=false
+ * Value Range: bool, default=true
  * Example:
  * Note: Whether to use new communication library in auto parallel and static
  * mode. If true, it will use unified CommContextManager for communication.
  */
 PHI_DEFINE_EXPORTED_bool(dynamic_static_unified_comm,
-                         false,
+                         true,
                          "Whether to use new communication library in auto "
                          "parallel and static mode.");
 #endif  // FLAGS_dynamic_static_unified_comm

test/collective/fleet/c_comm_init_op.py

@@ -17,9 +17,6 @@
 
 import paddle
 from paddle import base
-from paddle.distributed.fleet.base.private_helper_function import (
-    wait_server_ready,
-)
 
 paddle.enable_static()
 
@@ -35,8 +32,6 @@ def setUp(self):
         self.exe = base.Executor(self.place)
         self.endpoints.remove(self.current_endpoint)
         self.other_endpoints = self.endpoints
-        if self.rank == 0:
-            wait_server_ready(self.other_endpoints)
 
     def test_specifying_devices(self):
         program = base.Program()

test/collective/fleet/test_fused_attention_pass_with_mp.sh

@@ -17,4 +17,5 @@
 set -e
 # use default values
 # FIXME: random fails on Unknown command lines -c (or -m).
+export FLAGS_dynamic_static_unified_comm=0
 CUDA_VISIBLE_DEVICES=0,1 python -m paddle.distributed.launch fused_attention_pass_with_mp.py

test/distributed_passes/auto_parallel_pass_test_base.py

@@ -37,6 +37,7 @@ class AutoPallelPassTestBase(DistPassTestBase):
     def setUp(self):
         paddle.enable_static()
         seed = int(os.environ.get('SEED', -1))
+        os.environ["FLAGS_dynamic_static_unified_comm"] = "0"
         if seed <= 0:
             seed = np.random.randint(low=1, high=1000000, size=[1])[0]
             os.environ['SEED'] = str(seed)

test/distributed_passes/dist_pass_test_base.py

@@ -64,6 +64,7 @@ def setUp(self):
         if paddle.is_compiled_with_cuda():
             paddle.set_flags({'FLAGS_cudnn_deterministic': 1})
 
+        os.environ["FLAGS_dynamic_static_unified_comm"] = "0"
         seed = int(os.environ.get('SEED', -1))
         if seed <= 0:
             seed = np.random.randint(low=1, high=1000000, size=[1])[0]

test/legacy_test/test_collective_api_base.py

@@ -359,6 +359,7 @@ def check_with_place(
             "PATH_ID": path_id,
             "DTYPE": dtype,
             "REDUCE_TYPE": str(reduce_type),
+            "FLAGS_dynamic_static_unified_comm": "0",
         }
         required_envs.update(additional_envs)
         required_envs.update(need_envs)

test/legacy_test/test_collective_base.py

@@ -266,7 +266,7 @@ def check_with_place(
             "LD_PRELOAD": os.getenv("LD_PRELOAD", ""),
             "GLOG_v": "3",
             "NCCL_P2P_DISABLE": "1",
-            "Flags_dynamic_static_unified_comm": "False",
+            "FLAGS_dynamic_static_unified_comm": "0",
             "DTYPE": "float32",
         }
         required_envs.update(need_envs)

test/legacy_test/test_dist_base.py

@@ -1692,6 +1692,7 @@ def _get_required_envs(self, check_error_log=False, need_envs={}):
             "NCCL_P2P_DISABLE": "1",
             "NCCL_SHM_DISABLE": "1",
             "FLAGS_new_executor_static_build": "1",
+            "FLAGS_dynamic_static_unified_comm": "0",
         }
 
         if check_error_log:

test/legacy_test/test_dist_hapi_model.py

@@ -75,6 +75,7 @@ def start_local_trainers(
             "PADDLE_CURRENT_ENDPOINT": "%s" % t.endpoint,
             "PADDLE_TRAINERS_NUM": "%d" % cluster.trainers_nranks(),
             "PADDLE_TRAINER_ENDPOINTS": ",".join(cluster.trainers_endpoints()),
+            "FLAGS_dynamic_static_unified_comm": "0",
         }
 
         current_env.update(proc_env)

test/legacy_test/test_distributed_fused_lamb_op_with_clip.py

@@ -68,6 +68,7 @@ def run_test(
     os.environ['MAX_GLOBAL_NORM'] = str(max_global_norm)
     os.environ['GRADIENT_MERGE_STEPS'] = str(gradient_merge_steps)
     os.environ['USE_MASTER_ACC_GRAD'] = str(1 if use_master_acc_grad else 0)
+    os.environ["FLAGS_dynamic_static_unified_comm"] = "0"
     os.environ.update(need_env)
 
     touch_file_env = 'SUCCESS_TOUCH_FILE'

test/legacy_test/test_parallel_dygraph_dataparallel.py

@@ -121,6 +121,7 @@ def start_local_trainers(
             "PADDLE_CURRENT_ENDPOINT": "%s" % t.endpoint,
             "PADDLE_TRAINERS_NUM": "%d" % cluster.trainers_nranks(),
             "PADDLE_TRAINER_ENDPOINTS": ",".join(cluster.trainers_endpoints()),
+            "FLAGS_dynamic_static_unified_comm": "0",
         }
 
         proc_env["FLAGS_allocator_strategy"] = allocator_strategy

test/legacy_test/test_run.py

@@ -207,4 +207,5 @@ def test_ps_4(self):
 
 
 if __name__ == '__main__':
+    os.environ["FLAGS_dynamic_static_unified_comm"] = "0"
     unittest.main()

tools/test_runner.py

@@ -40,6 +40,7 @@
 
 def main():
     sys.path.append(os.getcwd())
+    os.environ["FLAGS_dynamic_static_unified_comm"] = "false"
     if core.is_compiled_with_cuda() or core.is_compiled_with_rocm():
         if os.getenv('FLAGS_enable_gpu_memory_usage_log') is None:
             os.environ['FLAGS_enable_gpu_memory_usage_log'] = 'true'