[misc] Centralize bench launch-vs-connect into a reusable acquire_endpoint (#28592)
This commit is contained in:
@@ -0,0 +1,126 @@
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"""Connection target for HTTP benchmark scripts.
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Owns the launch-vs-connect decision in one place: a benchmark only needs a base
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URL, which comes either from a server we launch or one already running.
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"""
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import dataclasses
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import multiprocessing
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import os
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import time
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from typing import Callable, Optional
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import requests
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from sglang.srt.entrypoints.http_server import launch_server
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from sglang.srt.server_args import ServerArgs
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from sglang.srt.utils import kill_process_tree
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DEFAULT_TIMEOUT = 600
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# Field defaults of ServerArgs, used to detect when --host/--port were set
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# explicitly (and would be silently ignored in connect mode).
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_SERVER_ARGS_DEFAULTS = {f.name: f.default for f in dataclasses.fields(ServerArgs)}
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def server_is_up(base_url: str, timeout: float = DEFAULT_TIMEOUT) -> bool:
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"""Return True if a server answers /v1/models with 200 at base_url."""
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try:
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headers = {
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"Content-Type": "application/json; charset=utf-8",
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}
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response = requests.get(
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f"{base_url}/v1/models", headers=headers, timeout=timeout
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)
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return response.status_code == 200
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except requests.RequestException:
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return False
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def _launch_server_target(launch_server_func: Callable, server_args: ServerArgs):
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try:
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launch_server_func(server_args)
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except Exception as e:
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raise e
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finally:
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kill_process_tree(os.getpid(), include_parent=False)
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def launch_or_reuse_server(launch_server_func: Callable, server_args: ServerArgs):
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base_url = f"http://{server_args.host}:{server_args.port}"
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# Reuse an already-running server instead of forking a second one onto the
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# occupied port, where it would orphan, compete for the GPU, and OOM.
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if server_is_up(base_url, timeout=5):
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print(
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f"WARNING: reusing the server already running at {base_url} "
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f"(--model and server-launch args ignored). Pass --base-url to silence."
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)
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return None, base_url
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proc = multiprocessing.Process(
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target=_launch_server_target,
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args=(
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launch_server_func,
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server_args,
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),
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)
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proc.start()
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start_time = time.time()
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while time.time() - start_time < DEFAULT_TIMEOUT:
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# Fail fast if the server died during startup (e.g. OOM).
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if not proc.is_alive():
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raise RuntimeError(
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f"Server process exited during startup (exit code "
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f"{proc.exitcode}); see the traceback above for the cause."
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)
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if server_is_up(base_url):
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return proc, base_url
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time.sleep(10)
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# Timed out: kill the half-started server so it does not linger as an orphan.
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kill_process_tree(proc.pid)
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raise TimeoutError("Server failed to start within the timeout period.")
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@dataclasses.dataclass
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class BenchEndpoint:
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"""A base URL plus the lifecycle of any server we launched to back it.
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``close()`` tears down a launched server; for a connected one it is a no-op.
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"""
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base_url: str
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_proc: Optional[multiprocessing.Process] = None
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def close(self) -> None:
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if self._proc is not None:
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kill_process_tree(self._proc.pid)
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self._proc = None
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def acquire_endpoint(
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server_args: ServerArgs,
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base_url: str = "",
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launch_server_func: Callable = launch_server,
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) -> BenchEndpoint:
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"""Resolve the benchmark target -- the single launch-vs-connect decision.
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base_url given: connect to it (server_args is ignored). base_url empty:
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launch a server from server_args. Caller must close() the result.
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"""
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if base_url:
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ignored = [
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f"--{name}"
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for name in ("host", "port")
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if getattr(server_args, name) != _SERVER_ARGS_DEFAULTS[name]
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]
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if ignored:
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print(
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f"WARNING: --base-url is set, so {' / '.join(ignored)} (and other "
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f"launch args) are ignored; benchmarking the server at {base_url}."
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)
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return BenchEndpoint(base_url=base_url)
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proc, url = launch_or_reuse_server(launch_server_func, server_args)
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return BenchEndpoint(base_url=url, _proc=proc)
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@@ -2,8 +2,6 @@ import argparse
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import dataclasses
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import dataclasses
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import itertools
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import itertools
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import json
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import json
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import multiprocessing
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import os
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import random
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import random
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import re
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import re
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import time
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import time
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@@ -17,12 +15,13 @@ from tabulate import tabulate
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from transformers import AutoProcessor, PreTrainedTokenizer
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from transformers import AutoProcessor, PreTrainedTokenizer
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from sglang.benchmark.datasets import get_dataset
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from sglang.benchmark.datasets import get_dataset
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from sglang.benchmark.endpoint import acquire_endpoint
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from sglang.benchmark.utils import get_processor, get_tokenizer
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from sglang.benchmark.utils import get_processor, get_tokenizer
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from sglang.profiler import run_profile
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from sglang.profiler import run_profile
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from sglang.srt.disaggregation.utils import FAKE_BOOTSTRAP_HOST
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from sglang.srt.disaggregation.utils import FAKE_BOOTSTRAP_HOST
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from sglang.srt.entrypoints.http_server import launch_server
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from sglang.srt.entrypoints.http_server import launch_server
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from sglang.srt.server_args import ServerArgs
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from sglang.srt.server_args import ServerArgs
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from sglang.srt.utils import is_blackwell, kill_process_tree
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from sglang.srt.utils import is_blackwell
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from sglang.test.test_utils import is_in_ci, write_github_step_summary
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from sglang.test.test_utils import is_in_ci, write_github_step_summary
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DEFAULT_TIMEOUT = 600
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DEFAULT_TIMEOUT = 600
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@@ -372,67 +371,6 @@ class BenchOneCaseResult(BaseModel):
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fout.write(json.dumps(res) + "\n")
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fout.write(json.dumps(res) + "\n")
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def launch_server_internal(launch_server_func: Callable, server_args: ServerArgs):
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try:
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launch_server_func(server_args)
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except Exception as e:
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raise e
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finally:
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kill_process_tree(os.getpid(), include_parent=False)
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def server_is_up(base_url: str, timeout: float = DEFAULT_TIMEOUT) -> bool:
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"""Return True if a server answers /v1/models with 200 at base_url."""
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try:
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headers = {
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"Content-Type": "application/json; charset=utf-8",
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}
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response = requests.get(
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f"{base_url}/v1/models", headers=headers, timeout=timeout
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)
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return response.status_code == 200
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except requests.RequestException:
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return False
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def launch_server_process(launch_server_func: Callable, server_args: ServerArgs):
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base_url = f"http://{server_args.host}:{server_args.port}"
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# Reuse an already-running server instead of forking a second one onto the
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# occupied port, where it would orphan, compete for the GPU, and OOM.
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if server_is_up(base_url, timeout=5):
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print(
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f"WARNING: reusing the server already running at {base_url} "
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f"(--model and server-launch args ignored). Pass --base-url to silence."
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)
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return None, base_url
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proc = multiprocessing.Process(
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target=launch_server_internal,
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args=(
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launch_server_func,
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server_args,
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),
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)
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proc.start()
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start_time = time.time()
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while time.time() - start_time < DEFAULT_TIMEOUT:
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# Fail fast if the server died during startup (e.g. OOM).
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if not proc.is_alive():
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raise RuntimeError(
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f"Server process exited during startup (exit code "
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f"{proc.exitcode}); see the traceback above for the cause."
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)
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if server_is_up(base_url):
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return proc, base_url
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time.sleep(10)
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# Timed out: kill the half-started server so it does not linger as an orphan.
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kill_process_tree(proc.pid)
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raise TimeoutError("Server failed to start within the timeout period.")
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def _warmup_cache(
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def _warmup_cache(
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url: str,
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url: str,
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input_ids: List[List[int]],
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input_ids: List[List[int]],
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@@ -907,11 +845,9 @@ def run_benchmark_internal(
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random.seed(bench_args.seed)
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random.seed(bench_args.seed)
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np.random.seed(bench_args.seed)
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np.random.seed(bench_args.seed)
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# launch a server or use the provided base_url
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# Resolve the benchmark target: launch a server, or connect to --base-url.
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if bench_args.base_url:
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endpoint = acquire_endpoint(server_args, bench_args.base_url, launch_server_func)
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proc, base_url = None, bench_args.base_url
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base_url = endpoint.base_url
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else:
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proc, base_url = launch_server_process(launch_server_func, server_args)
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# Get tokenizer and server info
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# Get tokenizer and server info
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if bench_args.backend == "vllm":
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if bench_args.backend == "vllm":
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@@ -1162,8 +1098,7 @@ def run_benchmark_internal(
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for res, profile_res in zip(results, profile_results, strict=False):
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for res, profile_res in zip(results, profile_results, strict=False):
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res.profile_link = profile_res.profile_link
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res.profile_link = profile_res.profile_link
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finally:
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finally:
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if proc:
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endpoint.close()
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kill_process_tree(proc.pid)
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print(f"\nResults are saved to {bench_args.result_filename}")
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print(f"\nResults are saved to {bench_args.result_filename}")
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