Closed jaytimbadia closed 4 years ago
Issue got resolved, Thankyou.
I had the same issue. May I ask how did you resolve it? Thanks!
Hello!
are you using windows? Can you try setting num_data_loader_workers=0
in the CombinedTM/ZeroShotTM initialization?
from contextualized_topic_models.models.ctm import CTM from contextualized_topic_models.utils.data_preparation import TextHandler from contextualized_topic_models.utils.data_preparation import bert_embeddings_from_file from contextualized_topic_models.datasets.dataset import CTMDataset
handler = TextHandler("documents.txt") handler.prepare() # create vocabulary and training data
generate BERT data
training_bert = bert_embeddings_from_file("documents.txt", "distiluse-base-multilingual-cased")
training_dataset = CTMDataset(handler.bow, training_bert, handler.idx2token)
ctm = CTM(input_size=len(handler.vocab), bert_input_size=512, inference_type="combined", n_components=50)
ctm.fit(training_dataset) # run the model
output::::: Settings: N Components: 50 Topic Prior Mean: 0.0 Topic Prior Variance: 0.98 Model Type: prodLDA Hidden Sizes: (100, 100) Activation: softplus Dropout: 0.2 Learn Priors: True Learning Rate: 0.002 Momentum: 0.99 Reduce On Plateau: False Save Dir: None Traceback (most recent call last): Traceback (most recent call last): File "test3.py", line 22, in
File "", line 1, in
File "C:\Users\Jay\py36\lib\multiprocessing\spawn.py", line 105, in spawn_main
ctm.fit(training_dataset)
exitcode = _main(fd) File "C:\Users\Jay\py36\neo\lib\site-packages\contextualized_topic_models\models\ctm.py", line 225, in fit
sp, train_loss = self._train_epoch(train_loader) prepare(preparation_data) File "C:\Users\Jay\py36\neo\lib\site-packages\contextualized_topic_models\models\ctm.py", line 151, in _train_epoch
for batch_samples in loader: _fixup_main_from_path(data['init_main_from_path']) File "C:\Users\Jay\py36\neo\lib\site-packages\torch\utils\data\dataloader.py", line 291, in iter
return _MultiProcessingDataLoaderIter(self) run_name="__mp_main") File "C:\Users\Jay\py36\neo\lib\site-packages\torch\utils\data\dataloader.py", line 737, in init__
File "C:\Users\Jay\py36\lib\runpy.py", line 263, in run_path w.start() File "C:\Users\Jay\py36\lib\multiprocessing\process.py", line 105, in start pkg_name=pkg_name, script_name=fname) self._popen = self._Popen(self) File "C:\Users\Jay\py36\lib\runpy.py", line 96, in _run_module_code
mod_name, mod_spec, pkg_name, script_name) return _default_context.get_context().Process._Popen(process_obj) File "C:\Users\Jay\py36\lib\runpy.py", line 85, in _run_code
exec(code, run_globals) return Popen(process_obj) File "C:\Users\Jay\Desktop\try_backend\test3.py", line 22, in
ctm.fit(training_dataset) reduction.dump(process_obj, to_child) File "C:\Users\Jay\py36\neo\lib\site-packages\contextualized_topic_models\models\ctm.py", line 225, in fit
sp, train_loss = self._train_epoch(train_loader) ForkingPickler(file, protocol).dump(obj) File "C:\Users\Jay\py36\neo\lib\site-packages\contextualized_topic_models\models\ctm.py", line 151, in _train_epoch
[Errno 32] Broken pipe File "C:\Users\Jay\py36\neo\lib\site-packages\torch\utils\data\dataloader.py", line 291, in iter
File "C:\Users\Jay\py36\neo\lib\site-packages\torch\utils\data\dataloader.py", line 737, in init w.start() File "C:\Users\Jay\py36\lib\multiprocessing\process.py", line 105, in start self._popen = self._Popen(self) File "C:\Users\Jay\py36\lib\multiprocessing\context.py", line 223, in _Popen return _default_context.get_context().Process._Popen(process_obj) File "C:\Users\Jay\py36\lib\multiprocessing\context.py", line 322, in _Popen return Popen(process_obj) File "C:\Users\Jay\py36\lib\multiprocessing\popen_spawn_win32.py", line 33, in init prep_data = spawn.get_preparation_data(process_obj._name) File "C:\Users\Jay\py36\lib\multiprocessing\spawn.py", line 143, in get_preparation_data _check_not_importing_main() File "C:\Users\Jay\py36\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.
The thing you people mentioned in the github itself is not running.