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Inference optimization by adding CUDA graph for MFR model and provide multiprocessor demo #616

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add multi procs demo
lvhan028 committed Sep 14, 2024
commit 2d5cf52f5d755285da746e78837b6f0f4b1c1fd5
69 changes: 69 additions & 0 deletions demo/multiprocs.py
Original file line number Diff line number Diff line change
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import os
import json
import fire

from loguru import logger

from magic_pdf.pipe.UNIPipe import UNIPipe
from magic_pdf.rw.DiskReaderWriter import DiskReaderWriter
import concurrent.futures
import time

import magic_pdf.model as model_config
model_config.__use_inside_model__ = True



def process(pdf_list):
current_script_dir = os.path.dirname(os.path.abspath(__file__))
pid = os.getpid()
for index, pdf_path in enumerate(pdf_list):
if index == 1:
# We start to record time after the pipe processes the first pdf,
# since it creates model instances when processing the first one,
# and creating model instances is very time consuming
start = time.perf_counter()
try:
pdf_bytes = open(pdf_path, "rb").read()
model_json = [] # model_json传空list使用内置模型解析
jso_useful_key = {"_pdf_type": "", "model_list": model_json}
local_image_dir = os.path.join(current_script_dir, str(pid), 'images')
image_dir = str(os.path.basename(local_image_dir))
image_writer = DiskReaderWriter(local_image_dir)
pipe = UNIPipe(pdf_bytes, jso_useful_key, image_writer)
pipe.pipe_classify()
"""如果没有传入有效的模型数据,则使用内置model解析"""
if len(model_json) == 0:
if model_config.__use_inside_model__:
pipe.pipe_analyze()
else:
logger.error("need model list input")
exit(1)
pipe.pipe_parse()
md_content = pipe.pipe_mk_markdown(image_dir, drop_mode="none")
# TODO: postprocessing md_content
except Exception as e:
logger.exception(e)
end = time.perf_counter()
logger.warning(f'>>>>> {pid} spent {(end-start):2f} s on processing {len(pdf_list) - 1} PDFs')


def file_ext(file_path):
return os.path.splitext(file_path)[-1]


def main(file_path: str, max_proc_num: int=4):
with open(file_path) as f:
file_paths = f.readlines()
pdf_file_list = [_path.strip() for _path in file_paths if file_ext(_path.strip()) == '.pdf']
proc_file_list = []
files_per_proc = (len(pdf_file_list) + max_proc_num - 1) // max_proc_num
for i in range(0, len(pdf_file_list), files_per_proc):
file_list_per_proc = pdf_file_list[i : i + files_per_proc]
proc_file_list.append(file_list_per_proc)
with concurrent.futures.ProcessPoolExecutor() as executor:
executor.map(process, proc_file_list)


if __name__ == '__main__':
fire.Fire(main)