[1/N][CI] Add multi node test (#3359)
### What this PR does / why we need it? This pr purpose to add multi-node test, on the first step, add `deepseek-v3` dp+tp+ep test ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? - vLLM version: v0.11.0rc3 - vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0 --------- Signed-off-by: wangli <wangli858794774@gmail.com>
This commit is contained in:
Li Wang
204
tests/e2e/multi_node/config/multi_node_config.py
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204
tests/e2e/multi_node/config/multi_node_config.py
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import json
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import logging
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import os
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from dataclasses import dataclass, field, fields
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from pathlib import Path
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from typing import Any, Dict, List, Optional, Type, TypeVar, Union
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from tests.e2e.multi_node.config.utils import (get_avaliable_port,
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get_leader_ip,
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get_net_interface)
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LOG = logging.getLogger(__name__)
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logging.basicConfig(level=logging.INFO)
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CONFIG_PATH = Path("tests/e2e/multi_node/config/config.json")
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T = TypeVar("T", bound="BaseConfig")
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# =========================
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# Base Config
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# =========================
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@dataclass
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class BaseConfig:
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model: str = "vllm-ascend/DeepSeek-V3-W8A8"
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_extra_fields: Optional[Dict[str, Any]] = None
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@classmethod
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def from_config(cls: Type[T], data: dict[str, Any]) -> T:
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"""Create config instance from dict, keeping unknown fields."""
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field_names = {f.name for f in fields(cls)}
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valid_fields = {k: v for k, v in data.items() if k in field_names}
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extra_fields = {k: v for k, v in data.items() if k not in field_names}
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obj = cls(**valid_fields)
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obj._extra_fields = extra_fields or {}
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return obj
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def to_list(self) -> List[str]:
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"""Convert all fields (including _extra_fields) to CLI arguments."""
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args: List[str] = []
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all_items = {**vars(self), **(self._extra_fields or {})}
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for key, value in all_items.items():
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if key in ("model", "_extra_fields") or value in (None, "", [],
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{}):
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continue
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key = key.replace("_", "-")
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if isinstance(value, bool):
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if value:
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args.append(f"--{key}")
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elif isinstance(value, dict):
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args += [f"--{key}", json.dumps(value, ensure_ascii=False)]
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else:
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args += [f"--{key}", str(value)]
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return args
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# =========================
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# Server Config
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# =========================
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@dataclass
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class ServerConfig(BaseConfig):
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host: str = "0.0.0.0"
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port: int = 8080
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trust_remote_code: bool = True
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enable_expert_parallel: bool = True
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gpu_memory_utilization: float = 0.9
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headless: bool = False
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quantization: Optional[str] = None
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tensor_parallel_size: int = 8
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max_model_len: int = 8192
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max_num_batched_token: int = 8192
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data_parallel_size: int = 4
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data_parallel_size_local: int = 2
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data_parallel_start_rank: int = 0
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data_parallel_rpc_port: int = 13389
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data_parallel_address: Optional[str] = None
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kv_transfer_config: Optional[Dict[str, Any]] = None
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additional_config: Optional[Dict[str, Any]] = None
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def init_dp_param(
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self,
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is_leader: bool,
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is_disaggregate_prefill: bool,
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dp_size: int,
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world_size: int,
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) -> None:
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"""Initialize distributed parallel parameters."""
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iface = get_net_interface()
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if iface is None:
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raise RuntimeError("No available network interface found")
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self.data_parallel_address = iface[0]
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if is_disaggregate_prefill:
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self.data_parallel_start_rank = 0
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return
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if not is_leader:
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self.headless = True
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self.data_parallel_start_rank = dp_size // world_size
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self.data_parallel_address = get_leader_ip()
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@dataclass
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class PerfConfig(BaseConfig):
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pass
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@dataclass
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class AccuracyConfig:
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prompt: str
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expected_output: str
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# =========================
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# MultiNode Config
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# =========================
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@dataclass
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class MultiNodeConfig:
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test_name: str = "Unnamed Test"
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disaggregate_prefill: bool = False
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enable_multithread_load: bool = True
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world_size: int = 2
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server_host: str = "0.0.0.0"
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server_port: int = 8888
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server_config: ServerConfig = field(default_factory=ServerConfig)
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perf_config: Optional[PerfConfig] = None
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accuracy_config: Optional[AccuracyConfig] = None
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@classmethod
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def from_config(cls, cfg: Dict[str, Any]) -> "MultiNodeConfig":
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"""Create a MultiNodeConfig from raw dict."""
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num_nodes = cfg.get("num_nodes", 2)
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is_disaggregate_prefill = cfg.get("disaggregate_prefill", False)
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node_index = int(os.getenv("LWS_WORKER_INDEX", 0))
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is_leader = node_index == 0
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# server config
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server_cfg_data = cfg.get("server_parameters", {})
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if not server_cfg_data:
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raise ValueError("Missing required key: 'server_parameters'")
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role_key = "leader_config" if is_leader else "worker_config"
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server_cfg_dict = server_cfg_data.get(role_key, {})
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server_cfg: ServerConfig = ServerConfig.from_config(server_cfg_dict)
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if cfg.get("enable_multithread_load"):
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server_cfg.model_loader_extra_config = { # type: ignore[attr-defined]
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"enable_multithread_load": True,
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"num_threads": 8,
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}
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# distributed param init
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server_cfg.init_dp_param(
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is_leader=is_leader,
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is_disaggregate_prefill=is_disaggregate_prefill,
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dp_size=server_cfg.data_parallel_size,
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world_size=num_nodes,
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)
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perf_cfg: Optional[PerfConfig] = (PerfConfig.from_config(
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cfg.get("client_parameters", {})) if cfg.get("client_parameters")
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else None)
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# network info
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leader_cfg = server_cfg_data.get("leader_config", {})
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server_host = get_leader_ip()
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server_port = (get_avaliable_port() if is_disaggregate_prefill else
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leader_cfg.get("port", 8080))
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return cls(
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test_name=str(cfg.get("test_name", "Unnamed Test")),
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disaggregate_prefill=is_disaggregate_prefill,
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enable_multithread_load=cfg.get("enable_multithread_load", False),
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world_size=num_nodes,
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server_config=server_cfg,
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perf_config=perf_cfg,
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server_host=server_host,
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server_port=server_port,
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)
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# =========================
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# Loader
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# =========================
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def load_configs(
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path: Union[str, Path] = CONFIG_PATH) -> List[MultiNodeConfig]:
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"""Load one or multiple configs from JSON file."""
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path = Path(path)
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if not path.exists():
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raise FileNotFoundError(f"Configuration file not found: {path}")
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raw = json.loads(path.read_text())
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configs_data = raw if isinstance(raw, list) else [raw]
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configs = []
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for idx, item in enumerate(configs_data):
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try:
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configs.append(MultiNodeConfig.from_config(item))
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except Exception as e:
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LOG.exception(f"Failed to parse config #{idx}: {e}")
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raise
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return configs
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