Bug using FutureWarning: You are using `torch.load` with `weights_only=False`

[VladIPlay]

This FutureWarning appears to be new in torch 2.4.0

.venv\Lib\site-packages\stanza\models\tokenize\trainer.py:85: FutureWarning: You are using torch.loadwithweights_only=False(the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value forweights_onlywill be flipped toTrue. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=Truefor any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. checkpoint = torch.load(filename, lambda storage, loc: storage)

[solar-sprout]

This is not ideal, but if you just want to suppress the warning so you can focus on more important messages, this worked for me:

# Suppress stanza/pytorch warnings
import warnings
warnings.filterwarnings("ignore", category=FutureWarning, module="stanza")

[janpeterka]

Can I suppress warnings when calling from cmd like argos-translate --from cs --to en "..."?

[autotunafish]

@janpeterka Add those lines to the argos-translate bin file, before 'cli.main()'. Mine lives in the '/home/me/.local/bin/' directory (after having followed normal pip installation). Just copypasta those lines into the file and save. It'll look something like this when its good:

#!/usr/bin/python3

from argostranslate import cli #Suppress stanza/pytorch warnings import warnings warnings.filterwarnings("ignore", category=FutureWarning, module="stanza")

cli.main()

[psifertex]

This look resolved upstream: https://github.com/stanfordnlp/stanza/issues/1429

It's resolved in the latest commits on GitHub but unfortunately the latest on pypi is pretty old and still shows the same behavior.