I run pytorch tutorial ‘s  Training a Classifier demo, but got this error:
[TypeError                                 Traceback (most recent call last)
 in 
12
13
—> 14 dataiter = iter(trainloader)strong text
15 images, labels = dataiter.next()
16
D:\DL_software\envs\pytorch\lib\site-packages\torch\utils\data\dataloader.py in iter(self)
817
818     def iter(self):
–> 819         return _DataLoaderIter(self)
820
821     def len(self):
D:\DL_software\envs\pytorch\lib\site-packages\torch\utils\data\dataloader.py in init(self, loader)
558                 #     before it starts, and del tries to join but will get:
559                 #     AssertionError: can only join a started process.
–> 560                 w.start()
561                 self.index_queues.append(index_queue)
562                 self.workers.append(w)
D:\DL_software\envs\pytorch\lib\multiprocessing\process.py in start(self)
103                ‘daemonic processes are not allowed to have children’
104         _cleanup()
–> 105         self._popen = self._Popen(self)
106         self._sentinel = self._popen.sentinel
107         # Avoid a refcycle if the target function holds an indirect
D:\DL_software\envs\pytorch\lib\multiprocessing\context.py in _Popen(process_obj)
221     @staticmethod
222     def _Popen(process_obj):
–> 223         return _default_context.get_context().Process._Popen(process_obj)
224
225 class DefaultContext(BaseContext):
D:\DL_software\envs\pytorch\lib\multiprocessing\context.py in _Popen(process_obj)
320         def _Popen(process_obj):
321             from .popen_spawn_win32 import Popen
–> 322             return Popen(process_obj)
323
324     class SpawnContext(BaseContext):
D:\DL_software\envs\pytorch\lib\multiprocessing\popen_spawn_win32.py in init(self, process_obj)
63             try:
64                 reduction.dump(prep_data, to_child)
—> 65                 reduction.dump(process_obj, to_child)
66             finally:
67                 set_spawning_popen(None)
D:\DL_software\envs\pytorch\lib\multiprocessing\reduction.py in dump(obj, file, protocol)
58 def dump(obj, file, protocol=None):
59     ‘’‘Replacement for pickle.dump() using ForkingPickler.’’’
—> 60     ForkingPickler(file, protocol).dump(obj)
61
62 #
TypeError: can’t pickle module objects](http://)