[fix] remove debug info;

tests/test_pipeline/test_schedule/test_zerobubble_pp.py

@@ -760,7 +760,6 @@ def run_fwd_bwd_vschedule_with_optim(test_config):
     ],
 )
 def run_with_booster_moehybridplugin(config: Tuple[int, ...]):
-    test_config = config
     stage, ep_size, pp_size, tp_size, sp_size = config
     num_microbatches = pp_size
     dist.get_world_size()
@@ -877,7 +876,6 @@ def run_with_booster_moehybridplugin(config: Tuple[int, ...]):
                 parallel_output = sharded_output["loss"]
             else:
                 parallel_output = torch.tensor(12345.0, device="cuda")
-            print(f"rank {dist.get_rank()} parallel_output {parallel_output}")
             # broadcast along pp axis
             dist.broadcast(parallel_output, src=dist.get_process_group_ranks(plugin.pp_group)[0], group=plugin.pp_group)
 
@@ -905,7 +903,6 @@ def run_with_booster_moehybridplugin(config: Tuple[int, ...]):
         torch_optimizer.step()
         torch_optimizer.zero_grad()
         assert_loose_close(parallel_output, torch_output_sum, dtype=dtype)
-        print(f"rank {dist.get_rank()} config {test_config}  test passed")
     clear_layout_converter()
     Randomizer.reset_index()
     torch.cuda.empty_cache()
@@ -1060,10 +1057,8 @@ def run_with_booster_hybridplugin(config: Tuple[int, ...]):
                 p.grad /= dp_size
         torch_optimizer.step()
         torch_optimizer.zero_grad()
-
-        print(f"parallel_output {parallel_output}, torch_output_sum {torch_output_sum}")
         assert_loose_close(parallel_output, torch_output_sum, dtype=dtype)
-        print(f"rank {dist.get_rank()} pp_size:{pp_size}, tp_size {tp_size}, sp_size :{sp_size} test passed")
+
     clear_layout_converter()
     Randomizer.reset_index()
     torch.cuda.empty_cache()