add dp rank for multi-dp (#6351)

Co-authored-by: Tong Li <tong.li35271158@gmail.com>

Author: 2 people

applications/ColossalChat/coati/distributed/grpo_consumer.py

@@ -136,7 +136,10 @@ def __init__(
     def setup(self):
         super().setup()
         if (not self.plugin.pp_size > 1 and self.rank == 0) or (
-            self.plugin.pp_size > 1 and self.booster.plugin.stage_manager.is_last_stage() and self.tp_rank == 0
+            self.plugin.pp_size > 1
+            and self.booster.plugin.stage_manager.is_last_stage()
+            and self.tp_rank == 0
+            and self.dp_rank == 0
         ):
             self.wandb_run = wandb.init(
                 project=self.project_name,
@@ -237,7 +240,6 @@ def step(self, step_idx: int, pbar: Any, **kwargs) -> Optional[float]:
         effective_samples = all_reduce_sum(torch.sum(loss_mask), self.plugin)
         effective_tokens_count = torch.sum(action_mask, dim=-1) * loss_mask
         total_effective_tokens_count = all_reduce_sum(torch.sum(effective_tokens_count), self.plugin)
-        total_samples = all_reduce_sum(torch.sum(torch.ones_like(loss_mask, device=loss_mask.device)), self.plugin)
         self.effective_sample_count += effective_samples.item()
         pbar.set_postfix(
             {
@@ -423,7 +425,10 @@ def _criterion(outputs, inputs):
                         mean_kl.append(kl.data)
                     mean_loss.append(loss.data)
             if not self.plugin.pp_size > 1 or (
-                self.plugin.pp_size > 1 and self.booster.plugin.stage_manager.is_last_stage() and self.tp_rank == 0
+                self.plugin.pp_size > 1
+                and self.booster.plugin.stage_manager.is_last_stage()
+                and self.tp_rank == 0
+                and self.dp_rank == 0
             ):
                 reward = all_reduce_mean(reward.mean(), self.plugin)
                 format_acc = all_reduce_mean(format_acc.mean(), self.plugin)