[Platform] add pre_register_and_update function (#12432)

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan 2025-02-11 22:06:46 +08:00 committed by GitHub
parent da317197dd
commit 2e3b969ec0
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3 changed files with 41 additions and 1 deletions

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@ -3057,7 +3057,8 @@ class VllmConfig:
kv_transfer_config: KVTransferConfig = field(default=None,
init=True) # type: ignore
# some opaque config, only used to provide additional information
# for the hash computation, mainly used for testing and debugging.
# for the hash computation, mainly used for testing, debugging or out of
# tree config registration.
additional_config: SupportsHash = field(default=None,
init=True) # type: ignore
instance_id: str = ""

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@ -20,6 +20,7 @@ from vllm.config import (CacheConfig, CompilationConfig, ConfigFormat,
from vllm.executor.executor_base import ExecutorBase
from vllm.logger import init_logger
from vllm.model_executor.layers.quantization import QUANTIZATION_METHODS
from vllm.plugins import load_general_plugins
from vllm.transformers_utils.utils import check_gguf_file
from vllm.usage.usage_lib import UsageContext
from vllm.utils import FlexibleArgumentParser, StoreBoolean
@ -203,6 +204,8 @@ class EngineArgs:
calculate_kv_scales: Optional[bool] = None
additional_config: Optional[Dict[str, Any]] = None
def __post_init__(self):
if not self.tokenizer:
self.tokenizer = self.model
@ -984,6 +987,14 @@ class EngineArgs:
'be loaded from the model checkpoint if available. '
'Otherwise, the scales will default to 1.0.')
parser.add_argument(
"--additional-config",
type=json.loads,
default=None,
help="Additional config for specified platform in JSON format. "
"Different platforms may support different configs. Make sure the "
"configs are valid for the platform you are using. The input format"
" is like '{\"config_key\":\"config_value\"}'")
return parser
@classmethod
@ -1044,6 +1055,9 @@ class EngineArgs:
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)
@ -1287,6 +1301,7 @@ class EngineArgs:
prompt_adapter_config=prompt_adapter_config,
compilation_config=self.compilation_config,
kv_transfer_config=self.kv_transfer_config,
additional_config=self.additional_config,
)
if envs.VLLM_USE_V1:
@ -1347,6 +1362,12 @@ class AsyncEngineArgs(EngineArgs):
parser.add_argument('--disable-log-requests',
action='store_true',
help='Disable logging requests.')
# Initialize plugin to update the parser, for example, The plugin may
# adding a new kind of quantization method to --quantization argument or
# a new device to --device argument.
load_general_plugins()
from vllm.platforms import current_platform
current_platform.pre_register_and_update(parser)
return parser

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@ -13,8 +13,10 @@ from vllm.logger import init_logger
if TYPE_CHECKING:
from vllm.config import VllmConfig
from vllm.utils import FlexibleArgumentParser
else:
VllmConfig = None
FlexibleArgumentParser = None
logger = init_logger(__name__)
@ -223,6 +225,22 @@ class Platform:
np.random.seed(seed)
torch.manual_seed(seed)
@classmethod
def pre_register_and_update(cls,
parser: Optional[FlexibleArgumentParser] = None
) -> None:
"""
Do some pre-registeration or update action for the current platform.
This function is called before global VllmConfig is initialized or cli
arguments are parsed. It's used for out-of-tree platforms to register or
update the configuration.
For example, the out-of-tree quantization config can be imported and
registered here dynamically.
"""
pass
@classmethod
def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
"""