import argparse import json import os import random import re import time import numpy as np from datasets import load_dataset from sglang.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, subject) 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-exam") parser.add_argument("--num-questions", type=int, default=None) args = add_common_sglang_args_and_parse(parser) main(args)