resurface lost ddp info message (#8111)

Author: awaelchli

pytorch_lightning/plugins/training_type/ddp.py

@@ -35,7 +35,7 @@
     _TORCH_GREATER_EQUAL_1_8,
     rank_zero_warn,
 )
-from pytorch_lightning.utilities.distributed import rank_zero_only, ReduceOp, sync_ddp_if_available
+from pytorch_lightning.utilities.distributed import rank_zero_info, rank_zero_only, ReduceOp, sync_ddp_if_available
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.seed import reset_seed
 
@@ -197,13 +197,6 @@ def setup_distributed(self):
         # where to store ip_table
         self.init_ddp_connection()
 
-        # on world_size=0 let everyone know training is starting
-        if self.is_global_zero and not torch.distributed.is_initialized():
-            log.info("-" * 100)
-            log.info(f"distributed_backend={self.distributed_backend}")
-            log.info(f"All DDP processes registered. Starting ddp with {self.world_size} processes")
-            log.info("-" * 100)
-
         # set the ranks and devices
         self.dist.rank = self.global_rank
         self.dist.device = self.root_device
@@ -271,6 +264,14 @@ def init_ddp_connection(self, global_rank: Optional[int] = None, world_size: Opt
             log.info(f"initializing ddp: GLOBAL_RANK: {global_rank}, MEMBER: {global_rank + 1}/{world_size}")
             torch_distrib.init_process_group(self.torch_distributed_backend, rank=global_rank, world_size=world_size)
 
+            # on rank=0 let everyone know training is starting
+            rank_zero_info(
+                f"{'-' * 100}\n"
+                f"distributed_backend={self.torch_distributed_backend}\n"
+                f"All DDP processes registered. Starting ddp with {self.world_size} processes\n"
+                f"{'-' * 100}\n"
+            )
+
     def pre_dispatch(self):
         # move the model to the correct device
         self.model_to_device()

pytorch_lightning/plugins/training_type/ddp_spawn.py

@@ -31,7 +31,7 @@
 from pytorch_lightning.utilities import _TORCH_GREATER_EQUAL_1_7, _TORCH_GREATER_EQUAL_1_8, rank_zero_warn
 from pytorch_lightning.utilities.cloud_io import atomic_save
 from pytorch_lightning.utilities.cloud_io import load as pl_load
-from pytorch_lightning.utilities.distributed import rank_zero_only, ReduceOp, sync_ddp_if_available
+from pytorch_lightning.utilities.distributed import rank_zero_info, rank_zero_only, ReduceOp, sync_ddp_if_available
 from pytorch_lightning.utilities.seed import reset_seed
 
 if _TORCH_GREATER_EQUAL_1_8:
@@ -148,13 +148,6 @@ def new_process(self, process_idx, trainer, mp_queue):
         #   ... need to double check that it is the correct place
         # self.trainer.call_setup_hook(self.model)
 
-        # on world_size=0 let everyone know training is starting
-        if self.is_global_zero and not torch.distributed.is_initialized():
-            log.info("-" * 100)
-            log.info(f"distributed_backend={self.distributed_backend}")
-            log.info(f"All DDP processes registered. Starting ddp with {self.world_size} processes")
-            log.info("-" * 100)
-
         # set the ranks and devices
         self.dist.rank = self.global_rank
         self.dist.device = self.root_device
@@ -230,6 +223,14 @@ def init_ddp_connection(self, global_rank: Optional[int], world_size: Optional[i
             log.info(f"initializing ddp: GLOBAL_RANK: {global_rank}, MEMBER: {global_rank + 1}/{world_size}")
             torch_distrib.init_process_group(self.torch_distributed_backend, rank=global_rank, world_size=world_size)
 
+            # on rank=0 let everyone know training is starting
+            rank_zero_info(
+                f"{'-' * 100}\n"
+                f"distributed_backend={self.torch_distributed_backend}\n"
+                f"All DDP processes registered. Starting ddp with {self.world_size} processes\n"
+                f"{'-' * 100}\n"
+            )
+
     def determine_ddp_device_ids(self):
         if self.root_device.type == "cpu":
             return None