OSError: [Errno 22] Invalid argument

[bilgehanozkan]

Hello, I'm trying to run CombinedTM with different datasets. I get this error OS Error especially when dataset is larger and I can't figure if it is related with memory usage. Here is the traceback:

OSError Traceback (most recent call last)

in 1 ctm = CombinedTM(bow_size=len(tp.vocab), contextual_size=768, n_components=10, num_epochs=10) ----> 2 ctm.fit(training_dataset) # run the model E:\Users\blghn\anaconda3\lib\site-packages\contextualized_topic_models\models\ctm.py in fit(self, train_dataset, validation_dataset, save_dir, verbose, patience, delta, n_samples) 272 # train epoch 273 s = datetime.datetime.now() --> 274 sp, train_loss = self._train_epoch(train_loader) 275 samples_processed += sp 276 e = datetime.datetime.now() E:\Users\blghn\anaconda3\lib\site-packages\contextualized_topic_models\models\ctm.py in _train_epoch(self, loader) 171 samples_processed = 0 172 --> 173 for batch_samples in loader: 174 # batch_size x vocab_size 175 X_bow = batch_samples['X_bow'] E:\Users\blghn\anaconda3\lib\site-packages\torch\utils\data\dataloader.py in __iter__(self) 433 return self._iterator 434 else: --> 435 return self._get_iterator() 436 437 @property E:\Users\blghn\anaconda3\lib\site-packages\torch\utils\data\dataloader.py in _get_iterator(self) 379 else: 380 self.check_worker_number_rationality() --> 381 return _MultiProcessingDataLoaderIter(self) 382 383 @property E:\Users\blghn\anaconda3\lib\site-packages\torch\utils\data\dataloader.py in __init__(self, loader) 1032 # before it starts, and __del__ tries to join but will get: 1033 # AssertionError: can only join a started process. -> 1034 w.start() 1035 self._index_queues.append(index_queue) 1036 self._workers.append(w) E:\Users\blghn\anaconda3\lib\multiprocessing\process.py in start(self) 119 'daemonic processes are not allowed to have children' 120 _cleanup() --> 121 self._popen = self._Popen(self) 122 self._sentinel = self._popen.sentinel 123 # Avoid a refcycle if the target function holds an indirect E:\Users\blghn\anaconda3\lib\multiprocessing\context.py in _Popen(process_obj) 222 @staticmethod 223 def _Popen(process_obj): --> 224 return _default_context.get_context().Process._Popen(process_obj) 225 226 class DefaultContext(BaseContext): E:\Users\blghn\anaconda3\lib\multiprocessing\context.py in _Popen(process_obj) 325 def _Popen(process_obj): 326 from .popen_spawn_win32 import Popen --> 327 return Popen(process_obj) 328 329 class SpawnContext(BaseContext): E:\Users\blghn\anaconda3\lib\multiprocessing\popen_spawn_win32.py in __init__(self, process_obj) 91 try: 92 reduction.dump(prep_data, to_child) ---> 93 reduction.dump(process_obj, to_child) 94 finally: 95 set_spawning_popen(None) E:\Users\blghn\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 Thank you.

[vinid]

Hello!

Try to see if the issue is the same on reported here.

Setting the workers to 0 should solve the problems on Windows

[bilgehanozkan]

Thanks for the reply. When I set the workers to 0, I keep getting this error over and over again and jupyter crashes.

[vinid]

Ok good, that's a warning.

A few follow-up questions:

• How big is the dataset?
• Are you running this on a GPU?

can you see if adding this snippet before training helps?

import warnings
warnings.filterwarnings("ignore", category=DeprecationWarning) 

This is not good practice, but I just want to check if the notebook is crashing because of too many warnings or for something else.

[bilgehanozkan]

The dataset is very large and I'm running it on GPU. It works fine when warnings are ignored, thank you! :)

I'm closing the issue if it's ok.

[vinid]

no let's keep it open! thanks :)