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Merge pull request QwenLM#219 from tuhahaha/main
add example: auto_comments
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# Auto Comments | ||
本文档介绍Auto Comments,这是一个利用Qwen模型为代码文件自动生成注释的使用案例。 | ||
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# 使用方法 | ||
您可以直接执行如下命令,为提供的代码文件生成注释: | ||
``` | ||
python auto_comments.py --path 'path of file or folder' | ||
``` | ||
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参数: | ||
- path:文件路径。可以是文件(目前支持python代码文件),也可以是文件夹(会扫描文件夹下所有python代码文件) | ||
- regenerate:重新生成。默认False,如果针对同一文件需要重新生成注释,请设置为True | ||
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# 使用样例 | ||
- 执行:python auto_comments.py --path test_file.py | ||
- test_file.py 内容为: | ||
``` | ||
import numpy as np | ||
import pandas as pd | ||
import seaborn as sns | ||
sns.set_theme(style="whitegrid") | ||
rs = np.random.RandomState(365) | ||
values = rs.randn(365, 4).cumsum(axis=0) | ||
dates = pd.date_range("1 1 2016", periods=365, freq="D") | ||
data = pd.DataFrame(values, dates, columns=["A", "B", "C", "D"]) | ||
data = data.rolling(7).mean() | ||
sns.lineplot(data=data, palette="tab10", linewidth=2.5) | ||
``` | ||
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- 输出:test_file_comments.py(包含注释的代码文件),文件内容如下: | ||
``` | ||
# 导入需要的库 | ||
import numpy as np | ||
import pandas as pd | ||
import seaborn as sns | ||
# 设置 Seaborn 的主题风格为白色网格 | ||
sns.set_theme(style="whitegrid") | ||
# 生成随机数 | ||
rs = np.random.RandomState(365) | ||
# 生成 365 行 4 列的随机数,并按行累加 | ||
values = rs.randn(365, 4).cumsum(axis=0) | ||
# 生成日期 | ||
dates = pd.date_range("1 1 2016", periods=365, freq="D") | ||
# 将随机数和日期组合成 DataFrame | ||
data = pd.DataFrame(values, dates, columns=["A", "B", "C", "D"]) | ||
# 对 DataFrame 进行 7 天滑动平均 | ||
data = data.rolling(7).mean() | ||
# 使用 Seaborn 绘制折线图 | ||
sns.lineplot(data=data, palette="tab10", linewidth=2.5) | ||
``` |
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# 运行方式:python auto_comments.py --path 'path of file or folder' | ||
# 脚本功能:使用QWen-7B-Chat为提供的代码文件自动生成注释。(详见auto_comments.md) | ||
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import argparse | ||
import os | ||
from transformers import AutoModelForCausalLM, AutoTokenizer | ||
from transformers.generation import GenerationConfig | ||
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MaxLine = 50 # 限制单次处理最大代码行数 | ||
SplitKey = ["\ndef "] # 自定义的切分代码标识 | ||
CodeFileType = ["py"] # 目前仅测试过对python文件生成注释 | ||
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def parse_args(): | ||
parser = argparse.ArgumentParser() | ||
parser.add_argument('--path', type=str, default='Qwen-7B/eval/evaluate_ceval.py') | ||
parser.add_argument('--regenerate', action='store_true', default=False) #如果已经生成过注释,默认不会重新生成 | ||
args = parser.parse_args() | ||
return args | ||
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class QWenChat(): | ||
def __init__(self): | ||
self.tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-7B-Chat", trust_remote_code=True) | ||
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# use bf16 | ||
# model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-7B-Chat", device_map="auto", trust_remote_code=True, bf16=True).eval() | ||
# use fp16 | ||
# model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-7B-Chat", device_map="auto", trust_remote_code=True, fp16=True).eval() | ||
# use cpu only | ||
# model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-7B-Chat", device_map="cpu", trust_remote_code=True).eval() | ||
# use auto mode, automatically select precision based on the device. | ||
self.model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-7B-Chat", device_map="auto", trust_remote_code=True).eval() | ||
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# Specify hyperparameters for generation | ||
self.model.generation_config = GenerationConfig.from_pretrained("Qwen/Qwen-7B-Chat", trust_remote_code=True) | ||
self.history = None | ||
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def chat(self, query, system = ""): | ||
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# use history | ||
# response, history = self.model.chat(self.tokenizer, query, history=self.history) | ||
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# 默认不使用history | ||
response, history = self.model.chat(self.tokenizer, query, history=None) | ||
self.history = history | ||
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return response | ||
# 生成注释 | ||
def gen_code_comments(context, model = None, **kwargs): | ||
prompt = "\n为以上代码生成细致的中文注释,注意使用合适的语法。要求必须在每个函数开头生成一段统一的函数功能注释。\n除了注释,请保证原始代码内容不变。不要返回除了注释和代码以外的其余信息,不要生成额外代码。\n" | ||
return model.chat(context + prompt) | ||
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def read_file(path): | ||
f = open(path, "r",encoding='utf-8') | ||
lines = f.readlines() | ||
return "".join(lines) | ||
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def write_file(path, context): | ||
with open(path,'w') as f: | ||
f.write(context) | ||
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# 如果代码文件过长,可以简单按照最大行数切分代码 | ||
def split_context_by_maxline(text): | ||
lines = text.split("\n") | ||
lines_len = len(lines) | ||
res = [] | ||
for i in range(MaxLine, lines_len, MaxLine): | ||
res.append("\n".join(lines[i-MaxLine:i])) | ||
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if i < lines_len: | ||
res.append("\n".join(lines[i:])) | ||
return res | ||
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# 如果代码文件过长,可以简单按照函数切分代码 | ||
def split_context_by_splitkey(text): | ||
blocks = text.split(SplitKey[0]) | ||
return [blocks[0]] + [SplitKey[0]+x for x in blocks[1:]] | ||
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# merge原始代码和生成的注释,目的是保证原始代码不被更改。这部分可以使用各种不同的策略处理。 | ||
def merge_code_and_comments(original_file, comments_path): | ||
res = [] | ||
ori_f = open(original_file, "r",encoding='utf-8') | ||
ori_lines = ori_f.readlines() | ||
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com_f = open(comments_path, "r",encoding='utf-8') | ||
com_lines = com_f.readlines() | ||
len_com_lines = len(com_lines) | ||
p = 0 | ||
j = 0 | ||
for i, line in enumerate(ori_lines): | ||
if line.isspace(): | ||
continue | ||
if line.strip()[0] == '#': | ||
res.append(line) | ||
continue | ||
while j < len_com_lines and line[:-1] not in com_lines[j]: | ||
j += 1 | ||
if j < len_com_lines: | ||
p = j - 1 | ||
up_comments = [] | ||
triple_dot_flag = 0 | ||
while p < j: | ||
if p < 0 or (res and res[-1] and com_lines[p] == res[-1]): | ||
break | ||
if com_lines[p].strip() and (len(com_lines[p].strip())>3 and com_lines[p].strip()[-3:] == '"""' and com_lines[p].strip()[:3] == '"""') or (len(com_lines[p].strip())>3 and com_lines[p].strip()[-3:] == "'''" and com_lines[p].strip()[:3] == "'''"): | ||
up_comments.append(com_lines[p]) | ||
p -= 1 | ||
continue | ||
if com_lines[p].strip() and (com_lines[p].strip()[-3:] == '"""' or com_lines[p].strip()[:3] == '"""' or com_lines[p].strip()[-3:] == "'''" or com_lines[p].strip()[:3] == "'''"): | ||
triple_dot_flag = (triple_dot_flag + 1)%2 | ||
up_comments.append(com_lines[p]) | ||
p -= 1 | ||
continue | ||
if triple_dot_flag: | ||
up_comments.append(com_lines[p]) | ||
p -= 1 | ||
continue | ||
if (com_lines[p].strip()=="") or (com_lines[p].strip() and com_lines[p].strip()[0] == '#' and "省略部分内容" not in com_lines[p]): | ||
up_comments.append(com_lines[p]) | ||
else: | ||
break | ||
p -= 1 | ||
if up_comments: | ||
res.extend(reversed(up_comments)) | ||
if "#" in com_lines[j] and "#" not in line: | ||
in_line_comments = " #" + com_lines[j].split("#")[-1] | ||
res.append(line[:-1]+in_line_comments) | ||
else: | ||
res.append(line) | ||
p = j+1 | ||
else: | ||
res.append(line) | ||
j = p | ||
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write_file(comments_path, "".join(res)) | ||
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# 处理单个文件 | ||
def deal_one_file(model, path, args): | ||
context = read_file(path) | ||
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fname = path.split("/")[-1] | ||
fpath = "/".join(path.split("/")[:-1]) | ||
outfname = fname.split(".")[0]+"_comments."+fname.split(".")[-1] | ||
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comments_path = os.path.join(fpath, outfname) | ||
if (not args.regenerate) and os.path.exists(comments_path): | ||
print("use cache: ", comments_path) | ||
return | ||
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context_line = len(context.split("\n")) | ||
if context_line < MaxLine: | ||
res = gen_code_comments(context, model = model) | ||
elif SplitKey[0] not in context: | ||
context_list = split_context_by_maxline(context) | ||
res = "\n".join([gen_code_comments(context_block, model = model) for context_block in context_list]) | ||
else: | ||
context_list = split_context_by_splitkey(context) | ||
res = "\n".join([gen_code_comments(context_block, model = model) for context_block in context_list]) | ||
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write_file(comments_path, res) | ||
merge_code_and_comments(path, comments_path) | ||
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# 处理文件夹 | ||
def deal_folder(model, path, args): | ||
for fl in os.listdir(path): | ||
now_path = os.path.join(path, fl) | ||
if os.path.isfile(now_path): | ||
if (now_path.split(".")[-1] in CodeFileType) and ("_comments" not in now_path): | ||
deal_one_file(model, now_path, args) | ||
elif os.path.isdir(now_path): | ||
deal_folder(model, now_path, args) | ||
else: | ||
print("Please specify a correct path!") | ||
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def transfer(args): | ||
model = QWenChat() | ||
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if os.path.isfile(args.path): | ||
if (args.path.split(".")[-1] in CodeFileType) and ("_comments" not in args.path): | ||
deal_one_file(model, args.path, args) | ||
elif os.path.isdir(args.path): | ||
deal_folder(model, args.path, args) | ||
else: | ||
print("Please specify a correct path!") | ||
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if __name__ == '__main__': | ||
args = parse_args() | ||
print(args) | ||
transfer(args) |