pipe engine _aggregate_total_loss: more efficient loss concatenation (#4327)

* _aggregate_total_loss: more efficient loss concatenation

optimize _aggregate_total_loss function in order to remove dependancy
of copying from device to host and back to device.
This reduce the runtime on the host.

* Fixing the if/else block on which the optimization should take place

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Co-authored-by: Olatunji Ruwase <olruwase@microsoft.com>

deepspeed/runtime/pipe/engine.py

@@ -549,7 +549,7 @@ class PipelineEngine(DeepSpeedEngine):
                 agg_loss /= self.dp_world_size
 
             assert self.global_rank in self.grid.pp_group
-            losses = torch.Tensor([self.dp_group_loss, agg_loss]).to(self.device)
+            losses = torch.stack([self.dp_group_loss, agg_loss])
             if self.is_pipe_parallel:
                 dist.broadcast(tensor=losses, src=self.global_rank, group=self.mpu.get_pipe_parallel_group())
         else: