[1/N] Refactor nightly test structure (#5479)

### What this PR does / why we need it?
This patch is a series of refactoring actions, including clarifying the
directory structure of nightly tests, refactoring the config retrieval
logic, and optimizing the workflow, etc. This is the first step:
refactoring the directory structure of nightly to make it more readable
and logical.

- vLLM version: v0.13.0
- vLLM main:
5326c89803

Signed-off-by: wangli <wangli858794774@gmail.com>
This commit is contained in:
Li Wang
2025-12-30 19:03:02 +08:00
committed by GitHub
parent c85cc045f8
commit e760aae1df
59 changed files with 475 additions and 471 deletions

View File

@@ -28,7 +28,6 @@ import sys
import time
from typing import Any, Optional, Tuple, TypeVar, Union
import httpx
import numpy as np
import openai
import pytest
@@ -52,7 +51,8 @@ from vllm.utils.network_utils import get_open_port
from tests.e2e.model_utils import (TokensTextLogprobs,
TokensTextLogprobsPromptLogprobs)
from tests.e2e.nightly.multi_node.config.multi_node_config import NodeInfo
from tests.e2e.nightly.multi_node.scripts.multi_node_config import (
DisaggregatedPrefillCfg, NodeInfo)
from vllm_ascend.ascend_config import clear_ascend_config
# TODO: remove this part after the patch merged into vllm, if
# we not explicitly patch here, some of them might be effectiveless
@@ -104,6 +104,7 @@ class RemoteOpenAIServer:
env['VLLM_WORKER_MULTIPROC_METHOD'] = 'spawn'
if env_dict is not None:
env.update(env_dict)
logger.info(f"Starting server with command: {' '.join(server_cmd)}")
self.proc: subprocess.Popen = subprocess.Popen(
server_cmd,
env=env,
@@ -111,20 +112,21 @@ class RemoteOpenAIServer:
stderr=sys.stderr,
)
def __init__(self,
model: str,
vllm_serve_args: Union[list[str], str],
*,
server_host: str = '0.0.0.0',
server_port: int = 8080,
env_dict: Optional[dict[str, str]] = None,
seed: Optional[int] = None,
auto_port: bool = True,
nodes_info: Optional[list[NodeInfo]] = None,
disaggregated_prefill: Optional[dict] = None,
proxy_port: Optional[int] = None,
max_wait_seconds: Optional[float] = None,
override_hf_configs: Optional[dict[str, Any]] = None) -> None:
def __init__(
self,
model: str,
vllm_serve_args: Union[list[str], str],
*,
server_host: str = '0.0.0.0',
server_port: int = 8080,
env_dict: Optional[dict[str, str]] = None,
seed: Optional[int] = None,
auto_port: bool = True,
nodes_info: Optional[list[NodeInfo]] = None,
disaggregated_prefill: Optional[DisaggregatedPrefillCfg] = None,
proxy_port: Optional[int] = None,
max_wait_seconds: Optional[float] = None,
override_hf_configs: Optional[dict[str, Any]] = None) -> None:
if isinstance(vllm_serve_args, str):
vllm_serve_args = shlex.split(vllm_serve_args)
else:
@@ -187,6 +189,7 @@ class RemoteOpenAIServer:
This is for headless mode, where the api server
process only exists in the leader node.
"""
logger.info("Hanging until server process terminates...")
client = requests
try:
while True:
@@ -198,8 +201,6 @@ class RemoteOpenAIServer:
except Exception:
break
finally:
if isinstance(client, httpx.Client):
client.close()
self._terminate_server()
def _wait_for_server_pd(self, timeout: float):
@@ -210,8 +211,7 @@ class RemoteOpenAIServer:
def url_health(ip: str, port: int) -> str:
return f"http://{ip}:{port}/health"
targets = [(node_info.ip,
url_health(node_info.ip, node_info.server_port))
targets = [(node_info.ip, url_health(node_info.ip, self.port))
for node_info in self.nodes_info if not node_info.headless]
# Wait for proxy ready

View File

@@ -17,7 +17,7 @@ env_common:
disaggregated_prefill:
enabled: true
prefiller_host_index: [0, 1]
decoder_host_index: [2]
decoder_host_index: [2, 3]
deployment:
-

View File

@@ -16,7 +16,7 @@ env_common:
disaggregated_prefill:
enabled: true
prefiller_host_index: [0, 1]
decoder_host_index: [2]
decoder_host_index: [2, 3]
deployment:
-

View File

@@ -1,285 +0,0 @@
import logging
import os
import subprocess
from dataclasses import dataclass
from typing import Optional
import regex as re
import yaml
from tests.e2e.nightly.multi_node.config.utils import (get_all_ipv4,
get_avaliable_port,
get_cluster_ips,
get_net_interface,
setup_logger)
setup_logger()
logger = logging.getLogger(__name__)
DISAGGEGATED_PREFILL_PORT = 5333
CONFIG_BASE_PATH = "tests/e2e/nightly/multi_node/config/models/"
@dataclass
class NodeInfo:
index: int
ip: str
server_cmd: str
headless: bool
server_port: int
def __str__(self):
return (f"NodeInfo:\n"
f" index={self.index}\n"
f" ip={self.ip}\n"
f" headless={self.headless}\n"
f" server_port={self.server_port}")
class MultiNodeConfig:
def __init__(self,
model: str,
test_name: str,
nodes_info: list[NodeInfo],
npu_per_node: int = 16,
server_port: int = 8080,
disaggregated_prefill: Optional[dict] = None,
envs: Optional[dict] = None,
perf_cmd: Optional[str] = None,
acc_cmd: Optional[str] = None):
self.test_name = test_name
self.model = model
self.nodes_info = nodes_info
# We assume the first index of nodes as the master
# NOTE: this may be different in the scenarios like disaggregated prefill
# There may be multi groups of nodes, and the master of each group may be different
self.master_ip = self.nodes_info[0].ip
self.num_nodes = len(self.nodes_info)
self.npu_per_node = npu_per_node
self.server_port = server_port
self.envs = envs if envs is not None else {}
self.proxy_port = get_avaliable_port()
self.perf_cmd = perf_cmd
self.acc_cmd = acc_cmd
self.disaggregated_prefill = disaggregated_prefill
self._init_disaggregated_prefill()
self._init_dist_env()
self.server_cmd = self._expand_env_vars(self.node_info.server_cmd,
self.envs)
@property
def cur_ip(self):
return self.nodes_info[self.cur_index].ip
@property
def nic_name(self):
return get_net_interface(self.cur_ip)
@property
def node_info(self):
return self.nodes_info[self.cur_index]
@property
def cur_index(self):
# 1. Try to read worker index from K8s environment variable
worker_index = os.environ.get("LWS_WORKER_INDEX")
if worker_index:
return int(worker_index)
# 2. Fallback: match local IP against cluster IP list
cluster_ips = [node.ip for node in self.nodes_info]
cluster_ip_set = set(cluster_ips)
cur_ips = get_all_ipv4()
for ip in cur_ips:
if ip in cluster_ip_set:
return cluster_ips.index(ip)
raise RuntimeError(
"Could not determine current node index: no matching IP.\n"
f"Local machine IPs: {cur_ips}\n"
f"Cluster IPs: {cluster_ips}\n"
"Please check your config file or network settings.")
def _init_disaggregated_prefill(self):
if self.disaggregated_prefill:
decode_host_index = self.disaggregated_prefill.get(
"decoder_host_index")
if not decode_host_index:
raise RuntimeError("got empty decode_host_index")
self.decode_start_index: int = decode_host_index[0]
self.num_prefillers = self.decode_start_index
self.num_decoders = self.num_nodes - self.num_prefillers
def _init_dist_env(self):
self.envs["HCCL_IF_IP"] = self.cur_ip
self.envs["GLOO_SOCKET_IFNAME"] = self.nic_name
self.envs["TP_SOCKET_IFNAME"] = self.nic_name
self.envs["HCCL_SOCKET_IFNAME"] = self.nic_name
self.envs["LOCAL_IP"] = self.cur_ip
self.envs["NIC_NAME"] = self.nic_name
master_ip = self.master_ip
if self.disaggregated_prefill:
if self.cur_index < self.decode_start_index:
# For prefiller nodes, use the default master ip(index==0) as DP master
master_ip = self.master_ip
else:
# For decoder nodes, use the first decoder node as DP master
master_ip = self.nodes_info[self.decode_start_index].ip
self.envs["MASTER_IP"] = master_ip
ascend_path = "/usr/local/Ascend/ascend-toolkit/latest/python/site-packages"
self.envs[
"LD_LIBRARY_PATH"] = f"{ascend_path}:{self.envs.get('LD_LIBRARY_PATH', os.environ.get('LD_LIBRARY_PATH', ''))}"
# keep the envs keys and values as strings
str_envs = {k: str(v) for k, v in self.envs.items()}
self.envs.clear()
self.envs.update(str_envs)
@staticmethod
def _expand_env_vars(cmd: str, env: dict) -> str:
"""Expand environment variables in the command string."""
cmd = str(cmd)
pattern = re.compile(r"\$(\w+)|\$\{(\w+)\}")
def replace_var(match):
var_name = match.group(1) or match.group(2)
return str(env.get(var_name, match.group(0)))
return pattern.sub(replace_var, cmd)
class _ProxyContext:
def __init__(self, outer, proxy_script):
self.outer = outer
self.proxy_script = proxy_script
self.process = None
def __enter__(self):
o = self.outer
if not o.disaggregated_prefill or not o.is_master:
logger.info(
"Disaggregated prefill not enabled or not master node, skipping proxy launch."
)
return self
prefiller_indices = o.disaggregated_prefill["prefiller_host_index"]
decoder_indices = o.disaggregated_prefill["decoder_host_index"]
common_indices = set(prefiller_indices) & set(decoder_indices)
assert not common_indices, f"Common indices found: {common_indices}"
assert o.proxy_port is not None, "proxy_port must be set"
cluster_ips = [node.ip for node in o.nodes_info]
prefiller_ips = [cluster_ips[i] for i in prefiller_indices]
decoder_ips = [cluster_ips[i] for i in decoder_indices]
prefiller_ports_list = [str(o.server_port)] * len(prefiller_ips)
decoder_ports_list = [str(o.server_port)] * len(decoder_ips)
proxy_cmd = [
"python",
self.proxy_script,
"--host",
o.cur_ip,
"--port",
str(o.proxy_port),
"--prefiller-hosts",
*prefiller_ips,
"--prefiller-ports",
*prefiller_ports_list,
"--decoder-hosts",
*decoder_ips,
"--decoder-ports",
*decoder_ports_list,
]
env = os.environ.copy()
env.update(o.envs)
logger.info(f"Launching proxy: {' '.join(proxy_cmd)}")
self.process = subprocess.Popen(proxy_cmd, env=env)
o.proxy_process = self.process
return self
def __exit__(self, exc_type, exc_val, exc_tb):
if self.process:
logger.info("Terminating proxy server process...")
try:
self.process.terminate()
self.process.wait(timeout=5)
except subprocess.TimeoutExpired:
logger.warning(
"Proxy process did not terminate, killing it...")
self.process.kill()
logger.info("Proxy server process terminated.")
def launch_server_proxy(self, proxy_script: str):
"""Return a context manager that launches the proxy server if disaggregated prefill is enabled."""
return self._ProxyContext(self, proxy_script)
@classmethod
def from_yaml(cls, yaml_path: Optional[str] = None):
if not yaml_path:
yaml_path = os.getenv("CONFIG_YAML_PATH", "DeepSeek-V3.yaml")
yaml_path = os.path.join(CONFIG_BASE_PATH, yaml_path)
with open(yaml_path, 'r') as file:
config_data = yaml.safe_load(file)
test_name = config_data.get("test_name", "default_test")
model = config_data.get("model", "default_model")
envs = config_data.get("env_common", {})
num_nodes = config_data.get("num_nodes", 2)
npu_per_node = config_data.get("npu_per_node", 16)
disaggregated_prefill = config_data.get("disaggregated_prefill")
# If disaggregated_prefill is set, override server_port to an available port for proxy running
server_port = config_data.get("server_port", 8080)
deployments = config_data.get("deployment", [])
assert len(deployments) == num_nodes, \
f"Number of deployments ({len(deployments)}) must match num_nodes ({num_nodes})"
cluster_ips = config_data.get("cluster_hosts", None)
if cluster_ips:
assert len(cluster_ips) == num_nodes, \
"Must provide cluster_ips for all nodes if it is explicitly specified."
else:
logger.info("Resolving cluster IPs via DNS...")
cluster_ips = get_cluster_ips(num_nodes)
nodes_info = []
for index, deployment in enumerate(deployments):
# after assert len(deployments) == num_nodes, we can assume that this will must have a match
server_cmd = deployment.get("server_cmd", "")
headless = "--headless" in server_cmd
nodes_info.append(
NodeInfo(ip=cluster_ips[index],
index=index,
headless=headless,
server_port=server_port,
server_cmd=server_cmd))
benchmarks = config_data.get("benchmarks") or {}
assert benchmarks is not None, "benchmarks must be provided"
perf_cmd = benchmarks.get("perf")
acc_cmd = benchmarks.get("acc")
return cls(model=model,
test_name=test_name,
npu_per_node=npu_per_node,
envs=envs,
server_port=server_port,
disaggregated_prefill=disaggregated_prefill,
nodes_info=nodes_info,
perf_cmd=perf_cmd,
acc_cmd=acc_cmd)
@property
def world_size(self):
return self.num_nodes * self.npu_per_node
@property
def is_master(self):
return self.cur_index == 0

View File

@@ -0,0 +1,349 @@
import logging
import os
import subprocess
from dataclasses import dataclass
from typing import Optional
import regex as re
import yaml
# isort: off
from tests.e2e.nightly.multi_node.scripts.utils import (
CONFIG_BASE_PATH, DEFAULT_SERVER_PORT, get_all_ipv4, get_cluster_ips,
get_net_interface, setup_logger, get_avaliable_port)
# isort: on
setup_logger()
logger = logging.getLogger(__name__)
@dataclass(frozen=True)
class NodeInfo:
index: int
ip: str
server_cmd: str
envs: dict | None = None
headless: bool = False
def __post_init__(self):
if not self.ip:
raise ValueError("NodeInfo.ip must not be empty")
def __str__(self) -> str:
return ("NodeInfo(\n"
f" index={self.index},\n"
f" ip={self.ip},\n"
f" headless={self.headless},\n"
")")
class DisaggregatedPrefillCfg:
def __init__(self, raw_cfg: dict, num_nodes: int):
self.prefiller_indices: list[int] = raw_cfg.get(
"prefiller_host_index", [])
self.decoder_indices: list[int] = raw_cfg.get("decoder_host_index", [])
if not self.decoder_indices:
raise RuntimeError("decoder_host_index must be provided")
self._validate(num_nodes)
self.decode_start_index = self.decoder_indices[0]
self.num_prefillers = len(self.prefiller_indices)
self.num_decoders = len(self.decoder_indices)
def _validate(self, num_nodes: int):
overlap = set(self.prefiller_indices) & set(self.decoder_indices)
if overlap:
raise AssertionError(f"Prefiller and decoder overlap: {overlap}")
all_indices = self.prefiller_indices + self.decoder_indices
if any(i >= num_nodes for i in all_indices):
raise ValueError("Disaggregated prefill index out of range")
def is_prefiller(self, index: int) -> bool:
return index in self.prefiller_indices
def is_decoder(self, index: int) -> bool:
return index in self.decoder_indices
def master_ip_for_node(self, index: int, nodes: list[NodeInfo]) -> str:
if self.is_prefiller(index):
return nodes[0].ip
return nodes[self.decode_start_index].ip
class DistEnvBuilder:
def __init__(
self,
*,
cur_node: NodeInfo,
master_ip: str,
common_envs: dict,
):
self.cur_ip = cur_node.ip
self.nic_name = get_net_interface(self.cur_ip)
self.master_ip = master_ip
# envs
common_envs = common_envs
current_envs = cur_node.envs or {}
# Node-specific envs override common envs
self.base_envs = {**common_envs, **current_envs}
def build(self) -> dict:
envs = dict(self.base_envs)
envs.update({
"HCCL_IF_IP": self.cur_ip,
"HCCL_SOCKET_IFNAME": self.nic_name,
"GLOO_SOCKET_IFNAME": self.nic_name,
"TP_SOCKET_IFNAME": self.nic_name,
"LOCAL_IP": self.cur_ip,
"NIC_NAME": self.nic_name,
"MASTER_IP": self.master_ip,
})
return {k: str(v) for k, v in envs.items()}
class ProxyLauncher:
def __init__(
self,
*,
nodes: list[NodeInfo],
envs: dict,
proxy_port: int,
cur_index: int,
disagg_cfg: DisaggregatedPrefillCfg | None = None,
):
self.nodes = nodes
self.cfg = disagg_cfg
self.server_port = envs.get("SERVER_PORT", DEFAULT_SERVER_PORT)
self.proxy_port = proxy_port
self.proxy_script = envs.get(
"DISAGGREGATED_PREFILL_PROXY_SCRIPT",
'examples/disaggregated_prefill_v1/load_balance_proxy_server_example.py'
)
self.envs = envs
self.is_master = cur_index == 0
self.cur_ip = nodes[cur_index].ip
self.process: Optional[subprocess.Popen[bytes]] = None
def __enter__(self):
if not self.is_master or self.cfg is None:
logger.info("Not launching proxy on non-master node")
return self
prefiller_ips = [self.nodes[i].ip for i in self.cfg.prefiller_indices]
decoder_ips = [self.nodes[i].ip for i in self.cfg.decoder_indices]
cmd = [
"python",
self.proxy_script,
"--host",
self.cur_ip,
"--port",
str(self.proxy_port),
"--prefiller-hosts",
*prefiller_ips,
"--prefiller-ports",
*[str(self.server_port)] * len(prefiller_ips),
"--decoder-hosts",
*decoder_ips,
"--decoder-ports",
*[str(self.server_port)] * len(decoder_ips),
]
logger.info("Launching proxy: %s", " ".join(cmd))
self.process = subprocess.Popen(cmd, env={**os.environ, **self.envs})
return self
def __exit__(self, exc_type, exc, tb):
if not self.process:
return
logger.info("Stopping proxy server...")
self.process.terminate()
try:
self.process.wait(timeout=5)
except subprocess.TimeoutExpired:
self.process.kill()
class MultiNodeConfig:
def __init__(
self,
*,
model: str,
test_name: str,
nodes: list[NodeInfo],
npu_per_node: int,
envs: dict,
disaggregated_prefill: dict | None,
perf_cmd: str | None,
acc_cmd: str | None,
):
self.model = model
self.test_name = test_name
self.nodes = nodes
self.npu_per_node = npu_per_node
self.perf_cmd = perf_cmd
self.acc_cmd = acc_cmd
self.cur_index = self._resolve_cur_index()
self.cur_node = self.nodes[self.cur_index]
self.disagg_cfg = (DisaggregatedPrefillCfg(disaggregated_prefill,
len(nodes))
if disaggregated_prefill else None)
master_ip = (self.disagg_cfg.master_ip_for_node(
self.cur_index, self.nodes)
if self.disagg_cfg else self.nodes[0].ip)
self.proxy_port = get_avaliable_port()
self.envs = DistEnvBuilder(
cur_node=self.cur_node,
master_ip=master_ip,
common_envs=envs,
).build()
logger.info("Node %d envs: %s", self.cur_index, self.envs)
self.server_cmd = self._expand_env(self.cur_node.server_cmd)
def _resolve_cur_index(self) -> int:
if (idx := os.environ.get("LWS_WORKER_INDEX")):
return int(idx)
local_ips = get_all_ipv4()
for i, node in enumerate(self.nodes):
if node.ip in local_ips:
return i
raise RuntimeError("Unable to determine current node index")
def _expand_env(self, cmd: str) -> str:
pattern = re.compile(r"\$(\w+)|\$\{(\w+)\}")
def repl(m):
key = m.group(1) or m.group(2)
return self.envs.get(key, m.group(0))
return pattern.sub(repl, cmd)
@property
def world_size(self) -> int:
return len(self.nodes) * self.npu_per_node
@property
def is_master(self) -> bool:
return self.cur_index == 0
@property
def server_port(self) -> int:
return self.envs.get("SERVER_PORT", DEFAULT_SERVER_PORT)
@property
def master_ip(self) -> str:
return self.nodes[0].ip
@property
def benchmark_endpoint(self) -> tuple[str, int]:
"""
Endpoint used by benchmark clients.
"""
master_ip = self.nodes[0].ip
server_port = self.envs.get("SERVER_PORT", DEFAULT_SERVER_PORT)
if self.disagg_cfg:
return master_ip, self.proxy_port
return master_ip, server_port
class MultiNodeConfigLoader:
"""Load MultiNodeConfig from yaml file."""
DEFAULT_CONFIG_NAME = "DeepSeek-V3.yaml"
@classmethod
def from_yaml(cls, yaml_path: Optional[str] = None) -> MultiNodeConfig:
config = cls._load_yaml(yaml_path)
cls._validate_root(config)
nodes = cls._parse_nodes(config)
benchmarks = cls._parse_benchmarks(config)
return MultiNodeConfig(
model=config["model"],
test_name=config.get("test_name", "untitled_test"),
nodes=nodes,
npu_per_node=config.get("npu_per_node", 16),
envs=config.get("env_common", {}),
disaggregated_prefill=config.get("disaggregated_prefill"),
perf_cmd=benchmarks.get("perf"),
acc_cmd=benchmarks.get("acc"),
)
@classmethod
def _load_yaml(cls, yaml_path: Optional[str]) -> dict:
if not yaml_path:
yaml_path = os.getenv("CONFIG_YAML_PATH", cls.DEFAULT_CONFIG_NAME)
full_path = os.path.join(CONFIG_BASE_PATH, yaml_path)
logger.info("Loading config yaml: %s", full_path)
with open(full_path, "r") as f:
return yaml.safe_load(f)
@staticmethod
def _validate_root(cfg: dict):
required = [
"model", "deployment", "num_nodes", "npu_per_node", "env_common",
"benchmarks"
]
missing = [k for k in required if k not in cfg]
if missing:
raise KeyError(f"Missing required config fields: {missing}")
@classmethod
def _parse_nodes(cls, cfg: dict) -> list[NodeInfo]:
num_nodes = cfg["num_nodes"]
deployments = cfg["deployment"]
if len(deployments) != num_nodes:
raise AssertionError(
f"deployment size ({len(deployments)}) != num_nodes ({num_nodes})"
)
cluster_ips = cls._resolve_cluster_ips(cfg, num_nodes)
nodes: list[NodeInfo] = []
for idx, deploy in enumerate(deployments):
cmd = deploy.get("server_cmd", "")
envs = deploy.get("envs", {})
nodes.append(
NodeInfo(
index=idx,
ip=cluster_ips[idx],
server_cmd=cmd,
envs=envs,
headless="--headless" in cmd,
))
return nodes
@staticmethod
def _parse_benchmarks(cfg: dict) -> dict:
benchmarks = cfg.get("benchmarks") or {}
return benchmarks
@staticmethod
def _resolve_cluster_ips(cfg: dict, num_nodes: int) -> list[str]:
if "cluster_hosts" in cfg and cfg["cluster_hosts"]:
ips = cfg["cluster_hosts"]
if len(ips) != num_nodes:
raise AssertionError("cluster_hosts size mismatch")
return ips
logger.info("Resolving cluster IPs via DNS...")
return get_cluster_ips(num_nodes)

View File

@@ -9,11 +9,15 @@ RED="\033[0;31m"
NC="\033[0m" # No Color
# Configuration
LOG_DIR="/root/.cache/tests/logs"
OVERWRITE_LOGS=true
export LD_LIBRARY_PATH=/usr/local/Ascend/ascend-toolkit/latest/python/site-packages:$LD_LIBRARY_PATH
# Home path for aisbench
export BENCHMARK_HOME=${WORKSPACE}/vllm-ascend/benchmark
# Logging configurations
export VLLM_LOGGING_LEVEL="INFO"
# Reduce glog verbosity for mooncake
export GLOG_minloglevel=1
# Set transformers to offline mode to avoid downloading models during tests
export TRANSFORMERS_OFFLINE="1"
# Function to print section headers
@@ -131,7 +135,7 @@ kill_npu_processes() {
run_tests_with_log() {
set +e
kill_npu_processes
pytest -sv --show-capture=no tests/e2e/nightly/multi_node/test_multi_node.py
pytest -sv --show-capture=no tests/e2e/nightly/multi_node/scripts/test_multi_node.py
ret=$?
set -e
if [ "$LWS_WORKER_INDEX" -eq 0 ]; then

View File

@@ -0,0 +1,46 @@
import pytest
from tests.e2e.conftest import RemoteOpenAIServer
from tests.e2e.nightly.multi_node.scripts.multi_node_config import (
MultiNodeConfigLoader, ProxyLauncher)
from tools.aisbench import run_aisbench_cases
@pytest.mark.asyncio
async def test_multi_node() -> None:
config = MultiNodeConfigLoader.from_yaml()
with ProxyLauncher(
nodes=config.nodes,
disagg_cfg=config.disagg_cfg,
envs=config.envs,
proxy_port=config.proxy_port,
cur_index=config.cur_index,
) as proxy:
with RemoteOpenAIServer(
model=config.model,
vllm_serve_args=config.server_cmd,
server_port=config.server_port,
server_host=config.master_ip,
env_dict=config.envs,
auto_port=False,
proxy_port=proxy.proxy_port,
disaggregated_prefill=config.disagg_cfg,
nodes_info=config.nodes,
max_wait_seconds=2800,
) as server:
host, port = config.benchmark_endpoint
if config.is_master:
run_aisbench_cases(
model=config.model,
port=port,
aisbench_cases=[config.acc_cmd, config.perf_cmd],
host_ip=host,
)
else:
# We should keep listening on the master node's server url determining when to exit.
server.hang_until_terminated(
f"http://{host}:{config.server_port}/health")

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@@ -3,10 +3,14 @@ import os
import socket
import time
from contextlib import contextmanager
from typing import Optional
from typing import List, Optional
import psutil
DISAGGEGATED_PREFILL_PORT = 5333
CONFIG_BASE_PATH = "tests/e2e/nightly/multi_node/config/"
DEFAULT_SERVER_PORT = 8080
@contextmanager
def temp_env(env_dict):
@@ -41,13 +45,29 @@ def dns_resolver(retries: int = 240, base_delay: float = 0.5):
return resolve
def get_cluster_dns_list(word_size: int) -> list[str]:
def get_cluster_dns_list(world_size: int) -> List[str]:
if world_size < 1:
raise ValueError(f"world_size must be >= 1, got {world_size}")
leader_dns = os.getenv("LWS_LEADER_ADDRESS")
if not leader_dns:
raise RuntimeError("LWS_LEADER_ADDRESS is not set")
raise RuntimeError(
"environment variable LWS_LEADER_ADDRESS is not set")
workers = [f"vllm-0-{i}.vllm.vllm-project" for i in range(1, word_size)]
return [leader_dns] + workers
# Expected format:
# <leader-name>.<group-name>.<namespace>
parts = leader_dns.split(".")
if len(parts) < 3:
raise ValueError(f"invalid leader DNS format: {leader_dns}")
leader_name, group_name, namespace = parts[0], parts[1], parts[2]
worker_dns_list = [
f"{leader_name}-{idx}.{group_name}.{namespace}"
for idx in range(1, world_size)
]
return [leader_dns, *worker_dns_list]
def get_cluster_ips(word_size: int = 2) -> list[str]:
@@ -92,7 +112,7 @@ def get_cur_ip(retries: int = 20, base_delay: float = 0.5):
delay = min(delay * 1.5, 5)
def get_net_interface(ip: Optional[str] = None) -> Optional[str]:
def get_net_interface(ip: Optional[str] = None) -> str:
"""
Returns specified IP's inetwork interface.
If no IP is provided, uses the first from hostname -I.
@@ -104,7 +124,7 @@ def get_net_interface(ip: Optional[str] = None) -> Optional[str]:
for addr in addrs:
if addr.family == socket.AF_INET and addr.address == ip:
return iface
return None
raise RuntimeError(f"No network interface found for IP {ip}")
def get_all_ipv4():

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@@ -1,130 +0,0 @@
import time
from typing import Any, List, Optional, Union
import httpx
import pytest
from modelscope import snapshot_download # type: ignore
from requests.exceptions import ConnectionError, HTTPError, Timeout
from tests.e2e.conftest import RemoteOpenAIServer
from tests.e2e.nightly.multi_node.config.multi_node_config import \
MultiNodeConfig
from tools.aisbench import run_aisbench_cases
prompts = [
"San Francisco is a",
]
api_keyword_args = {
"max_tokens": 10,
}
def get_local_model_path_with_retry(
model: str,
revision: str = "master",
max_retries: int = 5,
delay: int = 5,
) -> Optional[str]:
for attempt in range(1, max_retries + 1):
try:
local_model_path = snapshot_download(
model_id=model,
revision=revision,
)
return local_model_path
except HTTPError:
continue
except (ConnectionError, Timeout):
continue
if attempt < max_retries:
time.sleep(delay)
return None
async def get_completions(url: str, model: str, prompts: Union[str, List[str]],
**api_kwargs: Any) -> List[str]:
"""
Asynchronously send HTTP requests to endpoint.
Args:
url: Full endpoint URL, e.g. "http://localhost:1025/v1/completions"
model: Model name or local model path
prompts: A single prompt string or a list of prompts
**api_kwargs: Additional parameters (e.g., max_tokens, temperature)
Returns:
List[str]: A list of generated texts corresponding to each prompt
"""
headers = {"Content-Type": "application/json"}
if isinstance(prompts, str):
prompts = [prompts]
results = []
async with httpx.AsyncClient(timeout=600.0) as client:
for prompt in prompts:
payload = {"model": model, "prompt": prompt, **api_kwargs}
response = await client.post(url, headers=headers, json=payload)
if response.status_code != 200:
raise RuntimeError(
f"Request failed with status {response.status_code}: {response.text}"
)
resp_json = response.json()
choices = resp_json.get("choices", [])
if not choices or not choices[0].get("text"):
raise ValueError("Empty response from server")
results.append(choices[0]["text"])
return results
@pytest.mark.asyncio
async def test_multi_node() -> None:
config = MultiNodeConfig.from_yaml()
# To avoid modelscope 400 HttpError, we should download the model with retry
local_model_path = get_local_model_path_with_retry(config.model)
config.server_cmd = config.server_cmd.replace(config.model,
local_model_path)
assert local_model_path is not None, "can not find any local weight for test"
env_dict = config.envs
perf_cmd = config.perf_cmd
acc_cmd = config.acc_cmd
nodes_info = config.nodes_info
disaggregated_prefill = config.disaggregated_prefill
server_port = config.server_port
proxy_port = config.proxy_port
server_host = config.master_ip
proxy_script = config.envs.get("DISAGGREGATED_PREFILL_PROXY_SCRIPT", \
'examples/disaggregated_prefill_v1/load_balance_proxy_server_example.py')
with config.launch_server_proxy(proxy_script):
with RemoteOpenAIServer(
model=local_model_path,
vllm_serve_args=config.server_cmd,
server_port=server_port,
server_host=server_host,
env_dict=env_dict,
auto_port=False,
proxy_port=proxy_port,
disaggregated_prefill=disaggregated_prefill,
nodes_info=nodes_info,
max_wait_seconds=2800,
) as remote_server:
if config.is_master:
port = proxy_port if disaggregated_prefill else server_port
# aisbench test
aisbench_cases = [acc_cmd, perf_cmd]
run_aisbench_cases(local_model_path,
port,
aisbench_cases,
host_ip=config.master_ip)
else:
# for the nodes except master, should hang until the task complete
master_url = f"http://{config.master_ip}:{server_port}/health"
remote_server.hang_until_terminated(master_url)