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

139 lines
3.8 KiB
Python

import argparse
import json
import os
import random
import re
import time
import numpy as np
from datasets import load_dataset
from sglang.lang.api import set_default_backend
from sglang.test.test_utils import (
add_common_sglang_args_and_parse,
select_sglang_backend,
)
choices = ["A", "B", "C", "D"]
def get_one_example(line, include_answer):
res = line["question"]
res += f"\nA. {line['A']}"
res += f"\nB. {line['B']}"
res += f"\nC. {line['C']}"
res += f"\nD. {line['D']}"
if include_answer:
res += f"\nAnswer: {line['answer']} \n\n"
return res
def get_few_shot_examples(lines):
res = ""
for line in lines:
res += get_one_example(line, True) + "\n\n"
return res
def get_answer_value(response):
pattern = r"(Answer:|answer:|答案是|答案是:|正确答案是:|答案:|Assistant:)\s*([A-D])(?![\w])"
match = re.search(pattern, response)
if match:
return match.group(2)
return random.choice(choices)
def main(args):
# Read data && Construct prompts
arguments = []
labels = []
examples = "examples:\n"
data_path = args.data_path
for subject in os.listdir(data_path):
subject_path = os.path.join(data_path, subject)
if os.path.isdir(subject_path) and subject != ".git":
dataset = load_dataset(data_path, name=subject)
dev_lines_temp = dataset["dev"]
val_lines_temp = dataset["val"]
few_shot_examples = get_few_shot_examples(dev_lines_temp)
examples += f"{few_shot_examples}"
for val_line in val_lines_temp:
arguments.append(
{
"examples": few_shot_examples,
"question": get_one_example(val_line, False),
}
)
labels.append(val_line["answer"])
#####################################
######### SGL Program Begin #########
#####################################
import sglang as sgl
@sgl.function
def few_shot_ceval(s, examples, question):
s += examples + question + sgl.gen("Answer")
#####################################
########## SGL Program End ##########
#####################################
num_questions = args.num_questions if args.num_questions else len(arguments)
# Select backend
set_default_backend(select_sglang_backend(args))
# Run requests
tic = time.perf_counter()
states = few_shot_ceval.run_batch(
arguments[:num_questions],
temperature=0,
num_threads=args.parallel,
progress_bar=True,
)
latency = time.perf_counter() - tic
preds = [get_answer_value(states[i]["Answer"]) for i in range(num_questions)]
# Compute accuracy
acc = np.mean(np.array(preds) == np.array(labels[:num_questions]))
# Compute speed
num_output_tokens = sum(
s.get_meta_info("Answer")["completion_tokens"] for s in states
)
output_throughput = num_output_tokens / latency
# Print results
print(f"Accuracy: {acc:.3f}")
print(f"Latency: {latency:.3f} s")
print(f"Output throughput: {output_throughput:.3f} token/s")
# Write results
with open(args.result_file, "a") as fout:
value = {
"task": "ceval",
"backend": args.backend,
"num_gpus": 1,
"latency": round(latency, 3),
"accuracy": round(acc, 3),
"num_requests": args.num_questions,
"other": {
"parallel": args.parallel,
},
}
fout.write(json.dumps(value) + "\n")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--data-path", type=str, default="ceval/ceval-exam")
parser.add_argument("--num-questions", type=int, default=None)
args = add_common_sglang_args_and_parse(parser)
main(args)