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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

110 lines
3.2 KiB
Python

import argparse
import json
import os
import time
import numpy as np
from sglang.lang.api import set_default_backend
from sglang.test.test_utils import (
add_common_sglang_args_and_parse,
select_sglang_backend,
)
from sglang.utils import download_and_cache_file, read_jsonl
def get_one_example(lines, i, include_answer):
ret = lines[i]["activity_label"] + ": " + lines[i]["ctx"] + " "
if include_answer:
ret += lines[i]["endings"][lines[i]["label"]]
return ret
def get_few_shot_examples(lines, k):
ret = ""
for i in range(k):
ret += get_one_example(lines, i, True) + "\n\n"
return ret
def main(args):
# Select backend
set_default_backend(select_sglang_backend(args))
# Read data
data_path = args.data_path
url = "https://raw.githubusercontent.com/rowanz/hellaswag/master/data/hellaswag_val.jsonl"
if not os.path.isfile(data_path):
data_path = download_and_cache_file(url)
lines = list(read_jsonl(data_path))
# Construct prompts
num_questions = args.num_questions
num_shots = args.num_shots
few_shot_examples = get_few_shot_examples(lines, num_shots)
questions = []
choices = []
labels = []
for i in range(len(lines[:num_questions])):
questions.append(get_one_example(lines, i, False))
choices.append(lines[i]["endings"])
labels.append(lines[i]["label"])
arguments = [{"question": q, "choices": c} for q, c in zip(questions, choices)]
#####################################
######### SGL Program Begin #########
#####################################
import sglang as sgl
@sgl.function
def few_shot_hellaswag(s, question, choices):
s += few_shot_examples + question
s += sgl.select("answer", choices=choices)
#####################################
########## SGL Program End ##########
#####################################
# Run requests
tic = time.perf_counter()
rets = few_shot_hellaswag.run_batch(
arguments,
temperature=0,
num_threads=args.parallel,
progress_bar=True,
)
preds = [choices[i].index(rets[i]["answer"]) for i in range(len(rets))]
latency = time.perf_counter() - tic
# Compute accuracy
acc = np.mean(np.array(preds) == np.array(labels))
print(f"Latency: {latency:.3f}")
print(f"Accuracy: {acc:.3f}")
# Write results
with open(args.result_file, "a") as fout:
value = {
"task": "hellaswag",
"backend": args.backend,
"num_gpus": 1,
"latency": round(latency, 3),
"accuracy": round(acc, 3),
"num_requests": args.num_questions,
"other": {
"num_questions": args.num_questions,
"parallel": args.parallel,
},
}
fout.write(json.dumps(value) + "\n")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--num-shots", type=int, default=20)
parser.add_argument("--data-path", type=str, default="hellaswag_val.jsonl")
parser.add_argument("--num-questions", type=int, default=200)
args = add_common_sglang_args_and_parse(parser)
main(args)