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Format Benchmark Code (#399)

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Liangsheng Yin
2024-04-28 21:06:22 +08:00
committed by GitHub
parent 19818b9c2f
commit 95c4e0dfac
41 changed files with 1169 additions and 608 deletions
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100
benchmark/tree_of_thought_deep/bench_other.py
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@@ -1,25 +1,29 @@
import argparse
import ast
import asyncio
from collections import Counter
from concurrent.futures import ThreadPoolExecutor
from functools import partial
import json
import re
import time
from collections import Counter
from concurrent.futures import ThreadPoolExecutor
from functools import partial
import numpy as np
from tqdm import tqdm
from sglang.test.test_utils import add_common_other_args_and_parse, call_generate_lightllm, call_generate_vllm, call_generate_srt_raw
from sglang.utils import read_jsonl, dump_state_text
from sglang.test.test_utils import (
add_common_other_args_and_parse,
call_generate_lightllm,
call_generate_srt_raw,
call_generate_vllm,
)
from sglang.utils import dump_state_text, read_jsonl
INVALID = -9999999
def get_answer_value(answer_str):
answer_str = answer_str.replace(",", "")
numbers = re.findall(r'\d+', answer_str)
numbers = re.findall(r"\d+", answer_str)
if len(numbers) < 1:
return INVALID
try:
@@ -47,35 +51,56 @@ temp = 0.001
def propose_plan(s, question, num_branches, call_generate):
s += (USER_PREFIX +
"""Please generate a high-level plan for solving the following question. As the first step, just say what method and idea you will use to solve the question. You can reorganize the information in the question. Do not do the actual calculation. Keep your response concise and within 80 words. Question: """ + question + USER_SUFFIX)
s += (
USER_PREFIX
+ """Please generate a high-level plan for solving the following question. As the first step, just say what method and idea you will use to solve the question. You can reorganize the information in the question. Do not do the actual calculation. Keep your response concise and within 80 words. Question: """
+ question
+ USER_SUFFIX
)
s += ASSISTANT_PREFIX
comps = call_generate(s, max_tokens=256, temperature=temp, stop=None, n=num_branches)
comps = call_generate(
s, max_tokens=256, temperature=temp, stop=None, n=num_branches
)
return [s + comp + ASSISTANT_SUFFIX for comp in comps]
def execute_plan(s, num_branches, call_generate):
s += (USER_PREFIX +
"""The plan looks good! Now, use real numbers and do the calculation. Please solve the question step-by-step according to the high-level plan. Give me the final answer. Make your response short.""" + USER_SUFFIX)
s += (
USER_PREFIX
+ """The plan looks good! Now, use real numbers and do the calculation. Please solve the question step-by-step according to the high-level plan. Give me the final answer. Make your response short."""
+ USER_SUFFIX
)
s += ASSISTANT_PREFIX
comps = call_generate(s, max_tokens=256, temperature=temp, stop=None, n=num_branches)
comps = call_generate(
s, max_tokens=256, temperature=temp, stop=None, n=num_branches
)
return [s + comp + ASSISTANT_SUFFIX for comp in comps]
def reflect_solution(s, num_branches, call_generate):
s += (USER_PREFIX +
"""Okay. Now, evaluate your own solution and give it a score on a scale of 1 to 5. Please do rigorous check of the correctness.""" + USER_SUFFIX)
s += (
USER_PREFIX
+ """Okay. Now, evaluate your own solution and give it a score on a scale of 1 to 5. Please do rigorous check of the correctness."""
+ USER_SUFFIX
)
s += ASSISTANT_PREFIX
comps = call_generate(s, max_tokens=256, temperature=temp, stop=None, n=num_branches)
comps = call_generate(
s, max_tokens=256, temperature=temp, stop=None, n=num_branches
)
return [s + comp + ASSISTANT_SUFFIX for comp in comps]
def get_final_answer(s, num_branches, call_generate):
s += (USER_PREFIX +
"""Based on your reflection, do you change your mind? Now, give me the final answer after careful consideration.""" + USER_SUFFIX)
s += (
USER_PREFIX
+ """Based on your reflection, do you change your mind? Now, give me the final answer after careful consideration."""
+ USER_SUFFIX
)
s += ASSISTANT_PREFIX
comps = call_generate(s, max_tokens=256, temperature=temp, stop=None, n=num_branches)
comps = call_generate(
s, max_tokens=256, temperature=temp, stop=None, n=num_branches
)
return [s + comp + ASSISTANT_SUFFIX for comp in comps]
@@ -107,7 +132,7 @@ def main(args):
num_branches = 2
questions = []
labels = []
for i in range(len(lines[:args.num_questions])):
for i in range(len(lines[: args.num_questions])):
questions.append(lines[i]["question"])
labels.append(get_answer_value(lines[i]["answer"]))
assert all(l != INVALID for l in labels)
@@ -124,20 +149,40 @@ def main(args):
url = f"{args.host}:{args.port}/generate"
call_generate = partial(call_generate_srt_raw, url=url)
elif args.backend == "guidance":
from guidance import models, gen
from guidance import gen, models
model = models.LlamaCpp("/home/ubuntu/model_weights/Llama-2-7b-chat.gguf", n_gpu_layers=-1, n_ctx=4096)
model = models.LlamaCpp(
"/home/ubuntu/model_weights/Llama-2-7b-chat.gguf",
n_gpu_layers=-1,
n_ctx=4096,
)
def call_generate(prompt, temperature, max_tokens, stop, n):
if n == 1:
out = model + prompt + gen(name="answer",
max_tokens=max_tokens, temperature=temperature, stop=stop)
out = (
model
+ prompt
+ gen(
name="answer",
max_tokens=max_tokens,
temperature=temperature,
stop=stop,
)
)
return out["answer"]
else:
rets = []
for i in range(n):
out = model + prompt + gen(name="answer",
max_tokens=max_tokens, temperature=temperature, stop=stop)
out = (
model
+ prompt
+ gen(
name="answer",
max_tokens=max_tokens,
temperature=temperature,
stop=stop,
)
)
rets.append(out["answer"])
return rets
@@ -146,6 +191,7 @@ def main(args):
# Run requests
states = [None] * len(questions)
def get_one_answer(i):
states[i] = tree_search(**arguments[i], call_generate=call_generate)
@@ -188,7 +234,7 @@ def main(args):
"other": {
"num_questions": args.num_questions,
"parallel": args.parallel,
}
},
}
fout.write(json.dumps(value) + "\n")