sglang/benchmark/gsm8k/bench_other.py

import argparse
import ast
import asyncio
import json
import re
import time
from concurrent.futures import ThreadPoolExecutor

import numpy as np
from tqdm import tqdm

from sglang.test.test_utils import add_common_other_args_and_parse, get_call_generate
from sglang.utils import download_and_cache_file, dump_state_text, read_jsonl

INVALID = -9999999


def get_one_example(lines, i, include_answer):
    ret = "Question: " + lines[i]["question"] + "\nAnswer:"
    if include_answer:
        ret += " " + lines[i]["answer"]
    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 get_answer_value(answer_str):
    answer_str = answer_str.replace(",", "")
    numbers = re.findall(r"\d+", answer_str)
    if len(numbers) < 1:
        return INVALID
    try:
        return ast.literal_eval(numbers[-1])
    except SyntaxError:
        return INVALID


def main(args):
    # Select backend
    call_generate = get_call_generate(args)

    # Read data
    url = "https://raw.githubusercontent.com/openai/grade-school-math/master/grade_school_math/data/test.jsonl"
    filename = download_and_cache_file(url)
    lines = list(read_jsonl(filename))

    # Construct prompts
    num_questions = args.num_questions
    num_shots = args.num_shots
    few_shot_examples = get_few_shot_examples(lines, num_shots)

    questions = []
    labels = []
    for i in range(len(lines[:num_questions])):
        questions.append(get_one_example(lines, i, False))
        labels.append(get_answer_value(lines[i]["answer"]))
    assert all(l != INVALID for l in labels)

    states = [None] * len(labels)

    # Run requests
    if args.backend != "lmql":
        # Use thread pool
        def get_one_answer(i):
            answer = call_generate(
                prompt=few_shot_examples + questions[i],
                temperature=0,
                max_tokens=256,
                stop=["Question", "Assistant:", "<|separator|>"],
            )
            states[i] = answer

        tic = time.time()
        if args.parallel == 1:
            for i in tqdm(range(len(questions))):
                get_one_answer(i)
        else:
            with ThreadPoolExecutor(args.parallel) as executor:
                list(
                    tqdm(
                        executor.map(get_one_answer, list(range(len(questions)))),
                        total=len(questions),
                    )
                )

    else:
        # Use asyncio
        async def batched_call(batch_size):
            for i in range(0, len(questions), batch_size):
                tasks = []
                for q in questions[i : i + batch_size]:
                    tasks.append(
                        call_generate(
                            few_shot_examples + q,
                            temperature=0,
                            max_tokens=256,
                            stop="Question",
                        )
                    )
                rets = await asyncio.gather(*tasks)
                for j in range(len(rets)):
                    states[i + j] = rets[j]

        tic = time.time()
        asyncio.run(batched_call(batch_size=args.parallel))
    latency = time.time() - tic

    preds = []
    for i in range(len(states)):
        preds.append(get_answer_value(states[i]))

    # Compute accuracy
    acc = np.mean(np.array(preds) == np.array(labels))
    invalid = np.mean(np.array(preds) == INVALID)

    # Print results
    print(f"Accuracy: {acc:.3f}")
    print(f"Invalid: {invalid:.3f}")
    print(f"Latency: {latency:.3f} s")

    # Dump results
    dump_state_text(f"tmp_output_{args.backend}.txt", states)

    with open(args.result_file, "a") as fout:
        value = {
            "task": "gsm8k",
            "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=5)
    parser.add_argument("--data-path", type=str, default="test.jsonl")
    parser.add_argument("--num-questions", type=int, default=200)
    args = add_common_other_args_and_parse(parser)
    main(args)