运行中出现的错误serWarning: The use of the transforms.
你好,按照您的方法,运行test.py.我用的是CPU,在哪个ngpu那里设置为0,但是一运行的话就会出现下边的错误,您知道该怎么解决吗
D:\Anaconda\lib\site-packages\torchvision\transforms\transforms.py:207: UserWarning: The use of the transforms.Scale transform is deprecated, please use transforms.Resize instead.
warnings.warn("The use of the transforms.Scale transform is deprecated, " +
D:\Anaconda\lib\site-packages\torchvision\transforms\transforms.py:207: UserWarning: The use of the transforms.Scale transform is deprecated, please use transforms.Resize instead.
warnings.warn("The use of the transforms.Scale transform is deprecated, " +
Traceback (most recent call last):
File "
This probably means that you are not using fork to start your
child processes and you have forgotten to use the proper idiom
in the main module:
if __name__ == '__main__':
freeze_support()
...
The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce an executable.
return _DataLoaderIter(self) File "D:\Anaconda\lib\site-packages\torch\utils\data\dataloader.py", line 560, in init w.start() File "D:\Anaconda\lib\multiprocessing\process.py", line 112, in start self._popen = self._Popen(self) File "D:\Anaconda\lib\multiprocessing\context.py", line 223, in _Popen return _default_context.get_context().Process._Popen(process_obj) File "D:\Anaconda\lib\multiprocessing\context.py", line 322, in _Popen return Popen(process_obj) File "D:\Anaconda\lib\multiprocessing\popen_spawn_win32.py", line 33, in init prep_data = spawn.get_preparation_data(process_obj._name) File "D:\Anaconda\lib\multiprocessing\spawn.py", line 143, in get_preparation_data _check_not_importing_main() File "D:\Anaconda\lib\multiprocessing\spawn.py", line 136, in _check_not_importing_main is not going to be frozen to produce an executable.''') RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase.
This probably means that you are not using fork to start your
child processes and you have forgotten to use the proper idiom
in the main module:
if __name__ == '__main__':
freeze_support()
...
The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce an executable.
Hi, Don't know if still relevant, but I replaced all transforms.Scale at train.py with transforms.Resize, and moved all code in train.py to a if __name__ == '__main__': block, and resoved this 2 issues