From 824ad24149cd56ebb783e52f1a725cff34734142 Mon Sep 17 00:00:00 2001 From: fzyzcjy <5236035+fzyzcjy@users.noreply.github.com> Date: Sat, 16 May 2026 09:05:43 +0800 Subject: [PATCH] Convert local-only self.X attributes to locals (#25430) --- python/sglang/srt/managers/tokenizer_manager.py | 2 +- python/sglang/srt/model_executor/model_runner.py | 8 ++++---- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/python/sglang/srt/managers/tokenizer_manager.py b/python/sglang/srt/managers/tokenizer_manager.py index 6375a1d8b..23c6af312 100644 --- a/python/sglang/srt/managers/tokenizer_manager.py +++ b/python/sglang/srt/managers/tokenizer_manager.py @@ -445,7 +445,7 @@ class TokenizerManager(TokenizerControlMixin, TokenizerManagerScoreMixin): self.disaggregation_mode = DisaggregationMode( self.server_args.disaggregation_mode ) - self.bootstrap_server = start_disagg_service(self.server_args) + start_disagg_service(self.server_args) # Single-source counter for auto-assigning fake bootstrap_room. self.fake_bootstrap_room_counter = 0 diff --git a/python/sglang/srt/model_executor/model_runner.py b/python/sglang/srt/model_executor/model_runner.py index 53bb200c2..e504fbdf2 100644 --- a/python/sglang/srt/model_executor/model_runner.py +++ b/python/sglang/srt/model_executor/model_runner.py @@ -1500,8 +1500,8 @@ class ModelRunner(ModelRunnerKVCacheMixin): # Register model for layerwise NVTX profiling if enabled if self.server_args.enable_layerwise_nvtx_marker: - self.pyt_hooks = PytHooks() - self.pyt_hooks.register_hooks(self.model, module_prefix="model") + pyt_hooks = PytHooks() + pyt_hooks.register_hooks(self.model, module_prefix="model") if self.server_args.kv_cache_dtype == "fp8_e4m3": if self.server_args.quantization_param_path is not None: @@ -2080,8 +2080,8 @@ class ModelRunner(ModelRunnerKVCacheMixin): ) # We need to get device after patch otherwise the device would be wrong - self.device_module = torch.get_device_module(self.device) - infered_device = self.device_module.current_device() + device_module = torch.get_device_module(self.device) + infered_device = device_module.current_device() named_tensors = [ (name, _unwrap_tensor(tensor, tp_rank=self.tp_rank, device=infered_device))