import argparse import ast import json import os import re import time import numpy as np from sglang.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, 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 set_default_backend(select_sglang_backend(args)) # Read data data_path = args.data_path url = "https://raw.githubusercontent.com/openai/grade-school-math/master/grade_school_math/data/test.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 = [] 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) arguments = [{"question": q} for q in questions] ##################################### ######### SGL Program Begin ######### ##################################### import sglang as sgl @sgl.function def few_shot_gsm8k(s, question): s += few_shot_examples + question s += sgl.gen( "answer", max_tokens=512, stop=["Question", "Assistant:", "<|separator|>"] ) ##################################### ########## SGL Program End ########## ##################################### # Run requests tic = time.time() states = few_shot_gsm8k.run_batch( arguments, temperature=0, num_threads=args.parallel, progress_bar=True, ) latency = time.time() - tic preds = [] for i in range(len(states)): preds.append(get_answer_value(states[i]["answer"])) # Compute accuracy acc = np.mean(np.array(preds) == np.array(labels)) invalid = np.mean(np.array(preds) == INVALID) # 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"Invalid: {invalid:.3f}") print(f"Latency: {latency:.3f} s") print(f"Output throughput: {output_throughput:.3f} token/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_sglang_args_and_parse(parser) main(args)