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

demo/multiprocs.py

@@ -0,0 +1,69 @@
+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)