104 lines
2.8 KiB
Python
104 lines
2.8 KiB
Python
|
import itertools
|
||
|
|
import json
|
||
|
|
import random
|
||
|
|
import string
|
||
|
|
import threading
|
||
|
|
import time
|
||
|
|
from argparse import ArgumentParser
|
||
|
|
|
||
|
|
import sglang as sgl
|
||
|
|
from sglang.srt.hf_transformers_utils import get_tokenize
|
||
|
|
from sglang.test.test_utils import (
|
||
|
|
add_common_sglang_args_and_parse,
|
||
|
|
select_sglang_backend,
|
||
|
|
)
|
||
|
|
from sglang.utils import dump_state_text
|
||
|
|
|
||
|
|
random.seed(42)
|
||
|
|
|
||
|
|
|
||
|
|
def gen_prompt(tokenizer, token_num):
|
||
|
|
all_available_tokens = list(tokenizer.get_vocab().values())
|
||
|
|
selected_tokens = random.choices(all_available_tokens, k=token_num)
|
||
|
|
ret = tokenizer.decode(selected_tokens)
|
||
|
|
return ret
|
||
|
|
|
||
|
|
|
||
|
|
def gen_arguments(args, tokenizer):
|
||
|
|
multi_qas = [
|
||
|
|
{"system_prompt": gen_prompt(tokenizer, args.system_prompt_len), "qas": []}
|
||
|
|
for _ in range(args.num_qa)
|
||
|
|
]
|
||
|
|
for i in range(args.num_qa):
|
||
|
|
qas = multi_qas[i]["qas"]
|
||
|
|
for j in range(args.turns):
|
||
|
|
qas.append(
|
||
|
|
{
|
||
|
|
"prompt": gen_prompt(tokenizer, args.len_q),
|
||
|
|
"new_tokens": args.len_a,
|
||
|
|
}
|
||
|
|
)
|
||
|
|
return multi_qas
|
||
|
|
|
||
|
|
|
||
|
|
@sgl.function
|
||
|
|
def multi_turns(s, system_prompt, qas):
|
||
|
|
s += system_prompt
|
||
|
|
|
||
|
|
for qa in qas:
|
||
|
|
s += qa["prompt"]
|
||
|
|
s += sgl.gen(max_tokens=qa["new_tokens"], ignore_eos=True)
|
||
|
|
|
||
|
|
|
||
|
|
def main(args):
|
||
|
|
tokenizer = get_tokenizer(args.tokenizer, trust_remote_code=args.trust_remote_code)
|
||
|
|
|
||
|
|
multi_qas = gen_arguments(args, tokenizer)
|
||
|
|
|
||
|
|
backend = select_sglang_backend(args)
|
||
|
|
|
||
|
|
tic = time.time()
|
||
|
|
states = multi_turns.run_batch(
|
||
|
|
multi_qas,
|
||
|
|
temperature=0,
|
||
|
|
backend=backend,
|
||
|
|
num_threads=args.parallel,
|
||
|
|
progress_bar=True,
|
||
|
|
)
|
||
|
|
latency = time.time() - tic
|
||
|
|
|
||
|
|
print(f"Latency: {latency:.3f}")
|
||
|
|
|
||
|
|
dump_state_text(f"tmp_output_{args.backend}.txt", states)
|
||
|
|
|
||
|
|
with open(args.result_file, "a") as fout:
|
||
|
|
value = {
|
||
|
|
"task": "multi_turn_system_prompt_chat",
|
||
|
|
"backend": args.backend,
|
||
|
|
"num_gpus": 1,
|
||
|
|
"latency": round(latency, 3),
|
||
|
|
"num_requests": args.num_qa,
|
||
|
|
"num_turns": args.turns,
|
||
|
|
"other": {
|
||
|
|
"parallel": args.parallel,
|
||
|
|
},
|
||
|
|
}
|
||
|
|
fout.write(json.dumps(value) + "\n")
|
||
|
|
|
||
|
|
|
||
|
|
if __name__ == "__main__":
|
||
|
|
parser = ArgumentParser()
|
||
|
|
parser.add_argument("--turns", type=int, default=8)
|
||
|
|
parser.add_argument("--num-qa", type=int, default=128)
|
||
|
|
parser.add_argument("--system-prompt-len", type=int, default=2048)
|
||
|
|
parser.add_argument("--len-q", type=int, default=32)
|
||
|
|
parser.add_argument("--len-a", type=int, default=128)
|
||
|
|
parser.add_argument(
|
||
|
|
"--tokenizer", type=str, default="meta-llama/Meta-Llama-3-8B-Instruct"
|
||
|
|
)
|
||
|
|
parser.add_argument("--trust-remote-code", action="store_true")
|
||
|
|
args = add_common_sglang_args_and_parse(parser)
|
||
|
|
|
||
|
|
print(args)
|
||
|
|
main(args)
|