Closed qvviko closed 2 years ago
Hi @qvviko,
Thanks for the such a detailed issue description - we are looking into it 👍
Alex
Hi, @qvviko.
Can you please provide the output of the ulimit -a
command in the terminal?
@CrustaceanJ
~ ulimit -a
-t: cpu time (seconds) unlimited
-f: file size (blocks) unlimited
-d: data seg size (kbytes) unlimited
-s: stack size (kbytes) 8192
-c: core file size (blocks) unlimited
-m: resident set size (kbytes) unlimited
-u: processes 256602
-n: file descriptors 1024
-l: locked-in-memory size (kbytes) 1024
-v: address space (kbytes) unlimited
-x: file locks unlimited
-i: pending signals 256602
-q: bytes in POSIX msg queues 819200
-e: max nice 0
-r: max rt priority 0
-N 15: unlimited
Stale issue message
When trying to use TabularNLPAutoML preset there is a problem occurs with DataLoader (
RuntimeError: DataLoader worker (pid 2645328) is killed by signal: Segmentation fault.
). Full log can be found here - full log.txt.To replicate I:
pip install -U lightautoml
(automl version 0.2.16, torch 1.8.1, can report any other packages if necessary)./tmp
directory):from lightautoml.automl.presets.text_presets import TabularNLPAutoML from lightautoml.tasks import Task from lightautoml.report.report_deco import ReportDecoNLP
data_dir = Path('./tmp') TARGET_NAME = 'label' THREAD_N = 32 FOLDS = 5 TIMEOUT = 3600 STATE = 42
df = pd.read_csv(data_dir / 'train.csv')
task = Task('binary') roles = {'target': TARGET_NAME, 'text': ['tweet'], } RD = ReportDecoNLP() automl = TabularNLPAutoML(task=task, timeout=TIMEOUT, cpu_limit=THREAD_N, general_params={'use_algos': [['lgb', 'lgb_tuned']]}, reader_params={'n_jobs': THREAD_N, 'cv': FOLDS, 'random_state': STATE}, gbm_pipeline_params={'text_features': "embed"}, text_params={'lang': 'multi'}, ) automl_rd = RD(automl) oof_pred = automl_rd.fit_predict(df, roles=roles) print('oof_pred:\n{}\nShape = {}'.format(oof_pred, oof_pred.shape))
Is this an intended behavior? What if someone would wanted to use the gpu to speed up their processing?