126 lines
3.7 KiB
Python
126 lines
3.7 KiB
Python
import argparse
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import json
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import time
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from concurrent.futures import ThreadPoolExecutor
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from functools import partial
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from sglang.test.test_utils import (
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add_common_other_args_and_parse,
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call_generate_outlines,
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)
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from sglang.utils import dump_state_text, read_jsonl
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from sglang.lang.ir import REGEX_INT, REGEX_STRING, REGEX_FLOAT
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from tqdm import tqdm
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REGEX_LIST = r"\[(" + REGEX_STRING + ", )*" + REGEX_STRING + r"\]"
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# fmt: off
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def json_decode(document, generate):
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s = "Please extract the information of a city from the following wikipedia page.\n"
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s += "Page begin.\n" + document + "Page end.\n"
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s += "Here is the name, country, and symbol of the city in JSON format.\n"
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s += "{\n"
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s += ' "name": '
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s += generate(s, max_tokens=8, regex=REGEX_STRING + ",") + "\n"
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s += ' "country": '
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s += generate(s, max_tokens=8, regex=REGEX_STRING + ",") + "\n"
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s += ' "latitude": '
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s += generate(s, max_tokens=8, regex=REGEX_FLOAT + ",") + "\n"
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s += ' "population": '
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s += generate(s, max_tokens=8, regex=REGEX_INT + ",") + "\n"
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s += ' "top 3 landmarks": '
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s += generate(s, max_tokens=24, regex=REGEX_LIST) + "\n"
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s += "}\n"
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return s
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# fmt: on
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def main(args):
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lines = read_jsonl(args.data_path)
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arguments = []
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for i in range(len(lines[: args.num_questions])):
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arguments.append(
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{
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"document": lines[i]["document"],
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}
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)
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states = [None] * len(arguments)
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# Select backend
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if args.backend == "vllm":
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url = f"{args.host}:{args.port}/generate"
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generate = partial(call_generate_outlines, url=url, temperature=0)
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elif args.backend == "guidance":
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from guidance import gen, models
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model = models.LlamaCpp(
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"/home/ubuntu/model_weights/Llama-2-7b-chat-hf/ggml-model-f16.gguf",
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n_gpu_layers=-1,
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n_ctx=4096,
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)
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def generate(prompt, max_tokens, stop=None, regex=None):
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out = (
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model
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+ prompt
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+ gen(
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name="answer",
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max_tokens=max_tokens,
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temperature=0,
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stop=stop,
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regex=regex,
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)
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)
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return out["answer"]
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# warmup
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for _ in range(3):
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generate("Hello!" * 10, max_tokens=64, stop=None)
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else:
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raise ValueError(f"Invalid backend: {args.backend}")
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# Run requests
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def get_one_answer(i):
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states[i] = json_decode(generate=generate, **arguments[i])
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tic = time.time()
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if args.parallel == 1:
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for i in tqdm(range(len(arguments))):
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get_one_answer(i)
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else:
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with ThreadPoolExecutor(args.parallel) as executor:
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rets = executor.map(get_one_answer, list(range(len(arguments))))
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for _ in rets:
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pass
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latency = time.time() - tic
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# Compute accuracy
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print(f"Latency: {latency:.3f}")
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# Write results
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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": "json_decode_regex",
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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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"num_requests": args.num_questions,
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"other": {
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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("--data-path", type=str, default="questions.jsonl")
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parser.add_argument("--num-questions", type=int, default=20)
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args = add_common_other_args_and_parse(parser)
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main(args)
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