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import argparse |
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import ast |
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import json |
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import re |
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import time |
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import numpy as np |
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from sglang.api import set_default_backend |
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from sglang.test.test_utils import ( |
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add_common_sglang_args_and_parse, |
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select_sglang_backend, |
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) |
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from sglang.utils import download_and_cache_file, dump_state_text, read_jsonl |
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INVALID = -9999999 |
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def get_one_example(lines, i, include_answer): |
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ret = "Question: " + lines[i]["question"] + "\nAnswer:" |
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if include_answer: |
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ret += " " + lines[i]["answer"] |
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return ret |
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def get_few_shot_examples(lines, k): |
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ret = "" |
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for i in range(k): |
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ret += get_one_example(lines, i, True) + "\n\n" |
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return ret |
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def get_answer_value(answer_str): |
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answer_str = answer_str.replace(",", "") |
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numbers = re.findall(r"\d+", answer_str) |
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if len(numbers) < 1: |
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return INVALID |
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try: |
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return ast.literal_eval(numbers[-1]) |
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except SyntaxError: |
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return INVALID |
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def main(args): |
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set_default_backend(select_sglang_backend(args)) |
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url = "https://raw.githubusercontent.com/openai/grade-school-math/master/grade_school_math/data/test.jsonl" |
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filename = download_and_cache_file(url) |
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lines = list(read_jsonl(filename)) |
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num_questions = args.num_questions |
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num_shots = args.num_shots |
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few_shot_examples = get_few_shot_examples(lines, num_shots) |
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questions = [] |
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labels = [] |
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for i in range(len(lines[:num_questions])): |
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questions.append(get_one_example(lines, i, False)) |
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labels.append(get_answer_value(lines[i]["answer"])) |
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assert all(l != INVALID for l in labels) |
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arguments = [{"question": q} for q in questions] |
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import sglang as sgl |
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@sgl.function |
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def few_shot_gsm8k(s, question): |
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s += few_shot_examples + question |
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s += sgl.gen( |
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"answer", max_tokens=512, stop=["Question", "Assistant:", "<|separator|>"] |
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) |
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tic = time.time() |
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states = few_shot_gsm8k.run_batch( |
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arguments, |
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temperature=0, |
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num_threads=args.parallel, |
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progress_bar=True, |
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) |
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latency = time.time() - tic |
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preds = [] |
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for i in range(len(states)): |
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preds.append(get_answer_value(states[i]["answer"])) |
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acc = np.mean(np.array(preds) == np.array(labels)) |
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invalid = np.mean(np.array(preds) == INVALID) |
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num_output_tokens = sum( |
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s.get_meta_info("answer")["completion_tokens"] for s in states |
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) |
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output_throughput = num_output_tokens / latency |
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print(f"Accuracy: {acc:.3f}") |
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print(f"Invalid: {invalid:.3f}") |
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print(f"Latency: {latency:.3f} s") |
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print(f"Output throughput: {output_throughput:.3f} token/s") |
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dump_state_text(f"tmp_output_{args.backend}.txt", states) |
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with open(args.result_file, "a") as fout: |
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value = { |
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"task": "gsm8k", |
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"backend": args.backend, |
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"num_gpus": 1, |
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"latency": round(latency, 3), |
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"accuracy": round(acc, 3), |
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"num_requests": args.num_questions, |
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"other": { |
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"num_questions": args.num_questions, |
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"parallel": args.parallel, |
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}, |
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} |
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fout.write(json.dumps(value) + "\n") |
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if __name__ == "__main__": |
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parser = argparse.ArgumentParser() |
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parser.add_argument("--num-shots", type=int, default=5) |
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parser.add_argument("--data-path", type=str, default="test.jsonl") |
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parser.add_argument("--num-questions", type=int, default=200) |
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args = add_common_sglang_args_and_parse(parser) |
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main(args) |
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