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Move args from global_config to environ (#11332)

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This commit is contained in:
Liangsheng Yin
2025-10-12 21:29:31 +08:00
committed by GitHub
parent 01e59e8247
commit f49419061d
6 changed files with 34 additions and 46 deletions
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16
python/sglang/srt/managers/scheduler.py
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@@ -35,7 +35,6 @@ from torch.cuda import Stream as CudaStream
from torch.cuda import StreamContext as CudaStreamContext
from torch.distributed import barrier
from sglang.global_config import global_config
from sglang.srt.configs.model_config import ModelConfig
from sglang.srt.constrained.base_grammar_backend import (
INVALID_GRAMMAR_OBJ,
@@ -61,6 +60,7 @@ from sglang.srt.disaggregation.utils import (
prepare_abort,
)
from sglang.srt.distributed import get_pp_group, get_world_group
from sglang.srt.environ import envs
from sglang.srt.eplb.expert_distribution import get_global_expert_distribution_recorder
from sglang.srt.layers.dp_attention import compute_dp_attention_world_info
from sglang.srt.layers.logits_processor import LogitsProcessorOutput
@@ -556,18 +556,17 @@ class Scheduler(
server_args.schedule_conservativeness >= 0
), "Invalid schedule_conservativeness"
self.init_new_token_ratio = min(
global_config.default_init_new_token_ratio
envs.SGLANG_INIT_NEW_TOKEN_RATIO.get()
* server_args.schedule_conservativeness,
1.0,
)
self.min_new_token_ratio = min(
self.init_new_token_ratio
* global_config.default_min_new_token_ratio_factor,
self.init_new_token_ratio * envs.SGLANG_MIN_NEW_TOKEN_RATIO_FACTOR.get(),
1.0,
)
self.new_token_ratio_decay = (
self.init_new_token_ratio - self.min_new_token_ratio
) / global_config.default_new_token_ratio_decay_steps
) / envs.SGLANG_NEW_TOKEN_RATIO_DECAY_STEPS.get()
self.new_token_ratio = self.init_new_token_ratio
# Init watchdog thread
@@ -2897,12 +2896,13 @@ class IdleSleeper:
for s in sockets:
self.poller.register(s, zmq.POLLIN)
self.empty_cache_interval = envs.SGLANG_EMPTY_CACHE_INTERVAL.get()
def maybe_sleep(self):
self.poller.poll(1000)
if (
global_config.torch_empty_cache_interval > 0
and time.time() - self.last_empty_time
> global_config.torch_empty_cache_interval
self.empty_cache_interval > 0
and time.time() - self.last_empty_time > self.empty_cache_interval
):
self.last_empty_time = time.time()
torch.cuda.empty_cache()