From 0b1b07db7275f653b7224da8e724f425b7cbd0eb Mon Sep 17 00:00:00 2001
From: Qiaolin Yu <liin1211@outlook.com>
Date: Wed, 15 Apr 2026 15:08:18 -0700
Subject: [PATCH] [misc] fix ray folder lint (#22905)

---
 .../srt/ray/data_parallel_controller.py       | 16 +++------
 python/sglang/srt/ray/engine.py               | 34 +++++++------------
 2 files changed, 17 insertions(+), 33 deletions(-)

diff --git a/python/sglang/srt/ray/data_parallel_controller.py b/python/sglang/srt/ray/data_parallel_controller.py
index 751f07dbf..8f479be9f 100644
--- a/python/sglang/srt/ray/data_parallel_controller.py
+++ b/python/sglang/srt/ray/data_parallel_controller.py
@@ -93,9 +93,7 @@ class RayDataParallelController(DataParallelController):
 
         # Create actors for each DP rank sequentially
         for dp_rank in range(server_args.dp_size):
-            self._launch_ray_tp_group(
-                server_args, dp_port_args_list[dp_rank], dp_rank
-            )
+            self._launch_ray_tp_group(server_args, dp_port_args_list[dp_rank], dp_rank)
 
     def launch_dp_attention_schedulers(
         self, server_args: ServerArgs, port_args: PortArgs
@@ -168,24 +166,20 @@ class RayDataParallelController(DataParallelController):
                         rank_port_args.detokenizer_ipc_name = (
                             port_args.detokenizer_ipc_name
                         )
-                        rank_port_args.tokenizer_ipc_name = (
-                            port_args.tokenizer_ipc_name
-                        )
+                        rank_port_args.tokenizer_ipc_name = port_args.tokenizer_ipc_name
 
                     local_gpu_idx = (pp_rank % pp_per_node) * tp_per_node + (
                         tp_rank % tp_per_node
                     )
 
-                    attn_cp_rank, moe_dp_rank, moe_ep_rank = (
-                        _compute_parallelism_ranks(server_args, tp_rank)
+                    attn_cp_rank, moe_dp_rank, moe_ep_rank = _compute_parallelism_ranks(
+                        server_args, tp_rank
                     )
 
                     # Each DP group needs a unique dist_init_addr for its own
                     # torch.distributed process group. Use nccl_port which is
                     # unique per DP group (regular DP) or shared (DP attention).
-                    dist_init_addr = (
-                        f"{self.rank0_node_ip}:{rank_port_args.nccl_port}"
-                    )
+                    dist_init_addr = f"{self.rank0_node_ip}:{rank_port_args.nccl_port}"
 
                     actor = SchedulerActor.options(
                         num_cpus=0,
diff --git a/python/sglang/srt/ray/engine.py b/python/sglang/srt/ray/engine.py
index fef79cc52..b627065c0 100644
--- a/python/sglang/srt/ray/engine.py
+++ b/python/sglang/srt/ray/engine.py
@@ -124,28 +124,24 @@ class RayEngine(Engine):
                 f"Use {gpus_per_node} GPUs/node, world_size={world_size}"
             )
 
-            dist_init_addr = (
-                f"{rank0_node_ip}:{server_args.port + ZMQ_TCP_PORT_DELTA}"
-            )
+            dist_init_addr = f"{rank0_node_ip}:{server_args.port + ZMQ_TCP_PORT_DELTA}"
             logger.info(f"dist_init_addr: {dist_init_addr}")
 
             scheduler_actors = []
 
             for node_idx in range(nnodes):
                 bundle_idx = bundle_for_node[node_idx]
-                pp_range, tp_range, pp_per_node, tp_per_node = (
-                    _calculate_rank_ranges(
-                        nnodes,
-                        server_args.pp_size,
-                        server_args.tp_size,
-                        node_rank=node_idx,
-                    )
+                pp_range, tp_range, pp_per_node, tp_per_node = _calculate_rank_ranges(
+                    nnodes,
+                    server_args.pp_size,
+                    server_args.tp_size,
+                    node_rank=node_idx,
                 )
                 for pp_rank in pp_range:
                     for tp_rank in tp_range:
-                        local_gpu_idx = (
-                            pp_rank % pp_per_node
-                        ) * tp_per_node + (tp_rank % tp_per_node)
+                        local_gpu_idx = (pp_rank % pp_per_node) * tp_per_node + (
+                            tp_rank % tp_per_node
+                        )
 
                         attn_cp_rank, moe_dp_rank, moe_ep_rank = (
                             _compute_parallelism_ranks(server_args, tp_rank)
@@ -182,12 +178,8 @@ class RayEngine(Engine):
                     try:
                         ray.kill(actor)
                     except Exception:
-                        logger.error(
-                            f"Failed to kill Ray scheduler actor: {actor}"
-                        )
-                raise RuntimeError(
-                    f"Scheduler actor failed to initialize: {e}"
-                )
+                        logger.error(f"Failed to kill Ray scheduler actor: {actor}")
+                raise RuntimeError(f"Scheduler actor failed to initialize: {e}")
 
             event_loop_refs = [
                 actor.run_event_loop.remote() for actor in scheduler_actors
@@ -197,9 +189,7 @@ class RayEngine(Engine):
                 try:
                     ray.get(event_loop_refs)
                 except Exception as e:
-                    logger.error(
-                        f"Ray scheduler actor terminated with error: {e}"
-                    )
+                    logger.error(f"Ray scheduler actor terminated with error: {e}")
 
             return (
                 RaySchedulerInitResult(