Open LeMagicienHuang opened 3 years ago
Problem solved.
In files:
e:\users\admin\anaconda3\lib\site-packages\stylegan2_pytorch\cli.py e:\users\admin\anaconda3\lib\site-packages\stylegan2_pytorch\stylegan2_pytorch.py
Default: num_workers = None
Correction:
num_workers = 0
Problem solved.
In files:
e:\users\admin\anaconda3\lib\site-packages\stylegan2_pytorch\cli.py e:\users\admin\anaconda3\lib\site-packages\stylegan2_pytorch\stylegan2_pytorch.py
Default: num_workers = None
Correction:
num_workers = 0
thanks you!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Environment: Anaconda & Python3.7 CUDA 11.2 & cudnn 8.0.5 torch-gpu 1.7.1 & torchvision 0.8.2
When I run the training command
stylegan2_pytorch --data images/128a --image-size 128 --num-train-steps 100000
error occurred:
default<images/128a>: 0%| | 0/100000 [00:00<?, ?it/s]Traceback (most recent call last): File "", line 1, in
default<images/128a>: 0%| | 0/100000 [00:09<?, ?it/s]
Traceback (most recent call last):
File "e:\users\admin\anaconda3\lib\runpy.py", line 193, in _run_module_as_main
File "e:\users\admin\anaconda3\lib\multiprocessing\spawn.py", line 105, in spawn_main
exitcode = _main(fd)
"main", mod_spec) File "e:\users\admin\anaconda3\lib\multiprocessing\spawn.py", line 115, in _main
File "e:\users\admin\anaconda3\lib\runpy.py", line 85, in _run_code File "e:\users\admin\anaconda3\lib\site-packages\torch__init__.py", line 117, in
raise err
exec(code, run_globals)OSError: [WinError 1455] 页面文件太小,无法完成操作。 Error loading "e:\users\admin\anaconda3\lib\site-packages\torch\lib\caffe2_detectron_ops_gpu.dll" or one of its dependencies.
File "E:\Users\admin\anaconda3\Scripts\stylegan2_pytorch.exe__main.py", line 7, in
File "e:\users\admin\anaconda3\lib\site-packages\stylegan2_pytorch\cli.py", line 181, in main
fire.Fire(train_from_folder)
File "e:\users\admin\anaconda3\lib\site-packages\fire\core.py", line 138, in Fire
component_trace = _Fire(component, args, parsed_flag_args, context, name)
File "e:\users\admin\anaconda3\lib\site-packages\fire\core.py", line 468, in _Fire
target=component. name)
File "e:\users\admin\anaconda3\lib\site-packages\fire\core.py", line 672, in _CallAndUpdateTrace
component = fn(*varargs, *kwargs)
File "e:\users\admin\anaconda3\lib\site-packages\stylegan2_pytorch\cli.py", line 172, in train_from_folder
run_training(0, 1, model_args, data, load_from, new, num_train_steps, name, seed)
File "e:\users\admin\anaconda3\lib\site-packages\stylegan2_pytorch\cli.py", line 59, in run_training
retry_call(model.train, tries=3, exceptions=NanException)
File "e:\users\admin\anaconda3\lib\site-packages\retry\api.py", line 101, in retry_call
return __retry_internal(partial(f, args, **kwargs), exceptions, tries, delay, max_delay, backoff, jitter, logger)
File "e:\users\admin\anaconda3\lib\site-packages\retry\api.py", line 33, in retry_internal
return f()
File "e:\users\admin\anaconda3\lib\site-packages\stylegan2_pytorch\stylegan2_pytorch.py", line 943, in train
image_batch = next(self.loader).cuda(self.rank)
File "e:\users\admin\anaconda3\lib\site-packages\stylegan2_pytorch\stylegan2_pytorch.py", line 148, in cycle
for i in iterable:
File "e:\users\admin\anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 352, in iter__
return self._get_iterator()
File "e:\users\admin\anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 294, in _get_iterator
return _MultiProcessingDataLoaderIter(self)
File "e:\users\admin\anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 801, in init
w.start()
File "e:\users\admin\anaconda3\lib\multiprocessing\process.py", line 112, in start
self._popen = self._Popen(self)
File "e:\users\admin\anaconda3\lib\multiprocessing\context.py", line 223, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "e:\users\admin\anaconda3\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "e:\users\admin\anaconda3\lib\multiprocessing\popen_spawn_win32.py", line 89, in init__
reduction.dump(process_obj, to_child)
File "e:\users\admin\anaconda3\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj)
BrokenPipeError: [Errno 32] Broken pipe
anyone can help? thx in advance.