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When I run the training loop, I get the following error:
_---------------------------------------------------------------------------
OSError Traceback (most recent call last)
in ()
20
21 # train in batches
---> 22 for b, (y, X) in enumerate(train_gen):
23 # set label as cuda if device is cuda
24 X, y = X.to(device), y.to(device)
~\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py in init(self, loader)
287 for w in self.workers:
288 w.daemon = True # ensure that the worker exits on process exit
--> 289 w.start()
290
291 _update_worker_pids(id(self), tuple(w.pid for w in self.workers))
~\Anaconda3\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
~\Anaconda3\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):
~\Anaconda3\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):
When I run the training loop, I get the following error:
_---------------------------------------------------------------------------
OSError Traceback (most recent call last)
in ()
20
21 # train in batches
---> 22 for b, (y, X) in enumerate(train_gen):
23 # set label as cuda if device is cuda
24 X, y = X.to(device), y.to(device)
~\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py in iter(self)
499
500 def iter(self):
--> 501 return _DataLoaderIter(self)
502
503 def len(self):
~\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py in init(self, loader)
287 for w in self.workers:
288 w.daemon = True # ensure that the worker exits on process exit
--> 289 w.start()
290
291 _update_worker_pids(id(self), tuple(w.pid for w in self.workers))
~\Anaconda3\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
~\Anaconda3\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):
~\Anaconda3\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):
~\Anaconda3\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)
~\Anaconda3\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 #
OSError: [Errno 22] Invalid argument
I assumed it could be because of the large size of the pickle file so I changed the loading command to the code in this link:https://www.programmersought.com/article/3832726678/
but yet I am still getting the same error..
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