xinyun/vllm
1
0
Fork 0
mirror of https://git.datalinker.icu/vllm-project/vllm.git synced 2026-06-01 15:27:12 +08:00
Code Issues Packages Projects Releases Wiki Activity

[Misc] Clean Up EngineArgs.create_engine_config (#13734)

Browse Source 
Signed-off-by: rshaw@neuralmagic.com <rshaw@neuralmagic.com>
This commit is contained in:
Robert Shaw 2025-02-24 13:52:21 -05:00 committed by GitHub
parent db986c19ea
commit 1f0ae3ed0a
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 30 additions and 41 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
vllm/config.py
View File

@ -1124,6 +1124,10 @@ class CacheConfig:
return {key: str(value) for key, value in self.__dict__.items()} return {key: str(value) for key, value in self.__dict__.items()}
def _verify_args(self) -> None: def _verify_args(self) -> None:
if self.cpu_offload_gb < 0:
raise ValueError("CPU offload space must be non-negative"
f", but got {self.cpu_offload_gb}")
if self.gpu_memory_utilization > 1.0: if self.gpu_memory_utilization > 1.0:
raise ValueError( raise ValueError(
"GPU memory utilization must be less than 1.0. Got " "GPU memory utilization must be less than 1.0. Got "

67
vllm/engine/arg_utils.py
View File

@ -1062,6 +1062,17 @@ class EngineArgs:
return engine_args return engine_args
def create_model_config(self) -> ModelConfig: def create_model_config(self) -> ModelConfig:
# gguf file needs a specific model loader and doesn't use hf_repo
if check_gguf_file(self.model):
self.quantization = self.load_format = "gguf"
# NOTE: This is to allow model loading from S3 in CI
if (not isinstance(self, AsyncEngineArgs) and envs.VLLM_CI_USE_S3
and self.model in MODELS_ON_S3
and self.load_format == LoadFormat.AUTO): # noqa: E501
self.model = f"{MODEL_WEIGHTS_S3_BUCKET}/{self.model}"
self.load_format = LoadFormat.RUNAI_STREAMER
return ModelConfig( return ModelConfig(
model=self.model, model=self.model,
task=self.task, task=self.task,
@ -1101,26 +1112,6 @@ class EngineArgs:
) )
def create_load_config(self) -> LoadConfig: def create_load_config(self) -> LoadConfig:
return LoadConfig(
load_format=self.load_format,
download_dir=self.download_dir,
model_loader_extra_config=self.model_loader_extra_config,
ignore_patterns=self.ignore_patterns,
)
def create_engine_config(self,
usage_context: Optional[UsageContext] = None
) -> VllmConfig:
from vllm.platforms import current_platform
current_platform.pre_register_and_update()
if envs.VLLM_USE_V1:
self._override_v1_engine_args(usage_context)
# gguf file needs a specific model loader and doesn't use hf_repo
if check_gguf_file(self.model):
self.quantization = self.load_format = "gguf"
# bitsandbytes quantization needs a specific model loader # bitsandbytes quantization needs a specific model loader
# so we make sure the quant method and the load format are consistent # so we make sure the quant method and the load format are consistent
if (self.quantization == "bitsandbytes" or if (self.quantization == "bitsandbytes" or
@ -1137,19 +1128,23 @@ class EngineArgs:
"BitsAndBytes load format and QLoRA adapter only support " "BitsAndBytes load format and QLoRA adapter only support "
f"'bitsandbytes' quantization, but got {self.quantization}") f"'bitsandbytes' quantization, but got {self.quantization}")
assert self.cpu_offload_gb >= 0, ( return LoadConfig(
"CPU offload space must be non-negative" load_format=self.load_format,
f", but got {self.cpu_offload_gb}") download_dir=self.download_dir,
model_loader_extra_config=self.model_loader_extra_config,
ignore_patterns=self.ignore_patterns,
)
def create_engine_config(self,
usage_context: Optional[UsageContext] = None
) -> VllmConfig:
from vllm.platforms import current_platform
current_platform.pre_register_and_update()
if envs.VLLM_USE_V1:
self._override_v1_engine_args(usage_context)
device_config = DeviceConfig(device=self.device) device_config = DeviceConfig(device=self.device)
# NOTE: This is to allow model loading from S3 in CI
if (not isinstance(self, AsyncEngineArgs) and envs.VLLM_CI_USE_S3
and self.model in MODELS_ON_S3
and self.load_format == LoadFormat.AUTO): # noqa: E501
self.model = f"{MODEL_WEIGHTS_S3_BUCKET}/{self.model}"
self.load_format = LoadFormat.RUNAI_STREAMER
model_config = self.create_model_config() model_config = self.create_model_config()
if (model_config.is_multimodal_model and not envs.VLLM_USE_V1 if (model_config.is_multimodal_model and not envs.VLLM_USE_V1
@ -1281,16 +1276,6 @@ class EngineArgs:
if speculative_config is None \ if speculative_config is None \
else speculative_config.num_lookahead_slots else speculative_config.num_lookahead_slots
if not self.use_v2_block_manager:
logger.warning(
"[DEPRECATED] Block manager v1 has been removed, "
"and setting --use-v2-block-manager to True or False has "
"no effect on vLLM behavior. Please remove "
"--use-v2-block-manager in your engine argument. "
"If your use case is not supported by "
"SelfAttnBlockSpaceManager (i.e. block manager v2),"
" please file an issue with detailed information.")
scheduler_config = SchedulerConfig( scheduler_config = SchedulerConfig(
runner_type=model_config.runner_type, runner_type=model_config.runner_type,
max_num_batched_tokens=self.max_num_batched_tokens, max_num_batched_tokens=self.max_num_batched_tokens,