在运行valid.py时候,c盘空间迅速消耗到50g,随后被召回,并报错。
具体错误如下。
Traceback (most recent call last):
File "run/pose2d/valid.py", line 159, in <module>
main()
File "run/pose2d/valid.py", line 154, in main
validate(config, valid_loader, valid_dataset, model, criterion,
File "D:\TransFusion-Pose\run\pose2d\..\..\lib\core\function.py", line 233, in validate
for i, (input, target, weight, meta) in enumerate(loader):
File "C:\procedure_for_study\Anaconda3\envs\transpose\lib\site-packages\torch\utils\data\dataloader.py", line 352, in __iter__
return self._get_iterator()
File "C:\procedure_for_study\Anaconda3\envs\transpose\lib\site-packages\torch\utils\data\dataloader.py", line 294, in _get_iterator
return _MultiProcessingDataLoaderIter(self)
File "C:\procedure_for_study\Anaconda3\envs\transpose\lib\site-packages\torch\utils\data\dataloader.py", line 801, in __init__
w.start()
File "C:\procedure_for_study\Anaconda3\envs\transpose\lib\multiprocessing\process.py", line 121, in start
self._popen = self._Popen(self)
File "C:\procedure_for_study\Anaconda3\envs\transpose\lib\multiprocessing\context.py", line 224, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "C:\procedure_for_study\Anaconda3\envs\transpose\lib\multiprocessing\context.py", line 327, in _Popen
return Popen(process_obj)
File "C:\procedure_for_study\Anaconda3\envs\transpose\lib\multiprocessing\popen_spawn_win32.py", line 93, in __init__
reduction.dump(process_obj, to_child)
File "C:\procedure_for_study\Anaconda3\envs\transpose\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj)
MemoryError
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "C:\procedure_for_study\Anaconda3\envs\transpose\lib\multiprocessing\spawn.py", line
116, in spawn_main
exitcode = _main(fd, parent_sentinel)
File "C:\procedure_for_study\Anaconda3\envs\transpose\lib\multiprocessing\spawn.py", line 126, in _main
self = reduction.pickle.load(from_parent)
EOFError: Ran out of input
我个人觉得是线程、内存错误但是不知如何去解决,也不知理解是否正确,麻烦帮忙看看,十分感谢。