[diffusion] chore: revise process title (#18446)

python/sglang/multimodal_gen/runtime/managers/gpu_worker.py

@@ -12,11 +12,20 @@ from setproctitle import setproctitle
 from sglang.multimodal_gen import envs
 from sglang.multimodal_gen.runtime.distributed import (
     get_sp_group,
+    get_tp_rank,
+    get_tp_world_size,
     maybe_init_distributed_environment_and_model_parallel,
+    model_parallel_is_initialized,
 )
 from sglang.multimodal_gen.runtime.distributed.parallel_state import (
     get_cfg_group,
+    get_classifier_free_guidance_rank,
+    get_classifier_free_guidance_world_size,
+    get_ring_parallel_rank,
+    get_ring_parallel_world_size,
     get_tp_group,
+    get_ulysses_parallel_rank,
+    get_ulysses_parallel_world_size,
 )
 from sglang.multimodal_gen.runtime.entrypoints.utils import save_outputs
 from sglang.multimodal_gen.runtime.pipelines_core import (
@@ -70,7 +79,6 @@ class GPUWorker:
 
     def init_device_and_model(self) -> None:
         """Initialize the device and load the model."""
-        setproctitle(f"sgl_diffusion::scheduler_TP{self.local_rank}")
         torch.get_device_module().set_device(self.local_rank)
         # Set environment variables for distributed initialization
         os.environ["MASTER_ADDR"] = "localhost"
@@ -78,7 +86,7 @@ class GPUWorker:
         os.environ["LOCAL_RANK"] = str(self.local_rank)
         os.environ["RANK"] = str(self.rank)
         os.environ["WORLD_SIZE"] = str(self.server_args.num_gpus)
-        # Initialize the distributed environment
+        # initialize the distributed environment
         maybe_init_distributed_environment_and_model_parallel(
             tp_size=self.server_args.tp_size,
             enable_cfg_parallel=self.server_args.enable_cfg_parallel,
@@ -90,6 +98,25 @@ class GPUWorker:
             dist_timeout=self.server_args.dist_timeout,
         )
 
+        # set proc title
+        if model_parallel_is_initialized():
+            suffix = ""
+            if get_tp_world_size() != 1:
+                tp_rank = get_tp_rank()
+                suffix += f"_TP{tp_rank}"
+            if get_ulysses_parallel_world_size() != 1:
+                u_rank = get_ulysses_parallel_rank()
+                suffix += f"_U{u_rank}"
+            if get_ring_parallel_world_size() != 1:
+                r_rank = get_ring_parallel_rank()
+                suffix += f"_R{r_rank}"
+            if get_classifier_free_guidance_world_size() != 1:
+                c_rank = get_classifier_free_guidance_rank()
+                suffix += f"_C{c_rank}"
+            setproctitle(f"sgl_diffusion::scheduler{suffix}")
+        else:
+            setproctitle(f"sgl_diffusion::scheduler_{self.local_rank}")
+
         self.pipeline = build_pipeline(self.server_args)
 
         # apply layerwise offload after lora is applied while building LoRAPipeline