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# Copyright (c) OpenMMLab. All rights reserved.
"""This file is for benchmark dataloading process. The command line to run this
file is:
$ python -m cProfile -o program.prof tools/analysis/bench_processing.py
configs/task/method/[config filename]
It use cProfile to record cpu running time and output to program.prof
To visualize cProfile output program.prof, use Snakeviz and run:
$ snakeviz program.prof
"""
import argparse
import os
import mmcv
from mmcv import Config
from mmaction import __version__
from mmaction.datasets import build_dataloader, build_dataset
from mmaction.utils import get_root_logger
def main():
parser = argparse.ArgumentParser(description='Benchmark dataloading')
parser.add_argument('config', help='train config file path')
args = parser.parse_args()
cfg = Config.fromfile(args.config)
# init logger before other steps
logger = get_root_logger()
logger.info(f'MMAction2 Version: {__version__}')
logger.info(f'Config: {cfg.text}')
# create bench data list
ann_file_bench = 'benchlist.txt'
if not os.path.exists(ann_file_bench):
with open(cfg.ann_file_train) as f:
lines = f.readlines()[:256]
with open(ann_file_bench, 'w') as f1:
f1.writelines(lines)
cfg.data.train.ann_file = ann_file_bench
dataset = build_dataset(cfg.data.train)
data_loader = build_dataloader(
dataset,
videos_per_gpu=cfg.data.videos_per_gpu,
workers_per_gpu=0,
persistent_workers=False,
num_gpus=1,
dist=False)
# Start progress bar after first 5 batches
prog_bar = mmcv.ProgressBar(
len(dataset) - 5 * cfg.data.videos_per_gpu, start=False)
for i, data in enumerate(data_loader):
if i == 5:
prog_bar.start()
for _ in data['imgs']:
if i < 5:
continue
prog_bar.update()
if __name__ == '__main__':
main()
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