xinyun/vllm
1
0
Fork 0
mirror of https://git.datalinker.icu/vllm-project/vllm.git synced 2025-12-09 21:55:50 +08:00
Code Issues Packages Projects Releases Wiki Activity

fix: enable trust-remote-code in api server & benchmark. (#509)

Browse Source
This commit is contained in:
Ricardo Lu 2023-07-20 08:06:15 +08:00 committed by GitHub
parent cf21a9bd5c
commit 8c4b2592fb
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
4 changed files with 14 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
benchmarks/benchmark_latency.py
View File

@ -21,6 +21,7 @@ def main(args: argparse.Namespace):
tensor_parallel_size=args.tensor_parallel_size,
max_num_seqs=args.batch_size,
max_num_batched_tokens=args.batch_size * args.input_len,
trust_remote_code=args.trust_remote_code,
)
sampling_params = SamplingParams(
@ -74,5 +75,7 @@ if __name__ == '__main__':
parser.add_argument('--use-beam-search', action='store_true')
parser.add_argument('--num-iters', type=int, default=3,
help='Number of iterations to run.')
parser.add_argument('--trust-remote-code', action='store_true',
help='trust remote code from huggingface')
args = parser.parse_args()
main(args)

4
benchmarks/benchmark_serving.py
View File

@ -177,7 +177,7 @@ def main(args: argparse.Namespace):
np.random.seed(args.seed)
api_url = f"http://{args.host}:{args.port}/generate"
tokenizer = get_tokenizer(args.tokenizer)
tokenizer = get_tokenizer(args.tokenizer, trust_remote_code=args.trust_remote_code)
input_requests = sample_requests(args.dataset, args.num_prompts, tokenizer)
benchmark_start_time = time.time()
@ -227,5 +227,7 @@ if __name__ == "__main__":
"Otherwise, we use Poisson process to synthesize "
"the request arrival times.")
parser.add_argument("--seed", type=int, default=0)
parser.add_argument('--trust-remote-code', action='store_true',
help='trust remote code from huggingface')
args = parser.parse_args()
main(args)

10
benchmarks/benchmark_throughput.py
View File

@ -74,7 +74,7 @@ def run_vllm(
tokenizer=tokenizer,
tensor_parallel_size=tensor_parallel_size,
seed=seed,
trust_remote_code=trust_remote_code
trust_remote_code=trust_remote_code,
)
# Add the requests to the engine.
@ -111,7 +111,8 @@ def run_hf(
trust_remote_code: bool,
) -> float:
assert not use_beam_search
llm = AutoModelForCausalLM.from_pretrained(model, torch_dtype=torch.float16, trust_remote_code=trust_remote_code)
llm = AutoModelForCausalLM.from_pretrained(model,
torch_dtype=torch.float16, trust_remote_code=trust_remote_code)
if llm.config.model_type == "llama":
# To enable padding in the HF backend.
tokenizer.pad_token = tokenizer.eos_token
@ -173,8 +174,9 @@ def main(args: argparse.Namespace):
args.seed, args.n, args.use_beam_search, args.trust_remote_code)
elif args.backend == "hf":
assert args.tensor_parallel_size == 1
elapsed_time = run_hf(requests, args.model, tokenizer, args.n,
args.use_beam_search, args.hf_max_batch_size)
elapsed_time = run_hf(
requests, args.model, tokenizer, args.n, args.use_beam_search,
args.hf_max_batch_size, args.trust_remote_code)
else:
raise ValueError(f"Unknown backend: {args.backend}")
total_num_tokens = sum(

3
vllm/entrypoints/openai/api_server.py
View File

@ -585,7 +585,8 @@ if __name__ == "__main__":
# A separate tokenizer to map token IDs to strings.
tokenizer = get_tokenizer(engine_args.tokenizer,
tokenizer_mode=engine_args.tokenizer_mode)
tokenizer_mode=engine_args.tokenizer_mode,
trust_remote_code=engine_args.trust_remote_code)
uvicorn.run(app,
host=args.host,