File size: 2,405 Bytes
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Silence a scikit-learn 1.8 false-positive: ``_FuncWrapper.__call__`` warns when
``warning_filters`` is empty, even though sklearn's ``Parallel`` ran correctly.
Upstream condition is ``if not config or not warning_filters``; an empty filter
list is valid, so we only warn when ``config`` was never propagated (misuse of
``delayed`` without sklearn's ``Parallel``).
"""
from __future__ import annotations
import warnings
from sklearn._config import config_context
from sklearn.utils import parallel as skp
_applied = False
def _apply() -> None:
global _applied
if _applied:
return
_applied = True
def __call__(self, *args, **kwargs):
config = getattr(self, "config", {})
warning_filters = getattr(self, "warning_filters", [])
if not config:
warnings.warn(
(
"`sklearn.utils.parallel.delayed` should be used with"
" `sklearn.utils.parallel.Parallel` to make it possible to"
" propagate the scikit-learn configuration of the current thread to"
" the joblib workers."
),
UserWarning,
)
with config_context(**config), warnings.catch_warnings():
warnings.resetwarnings()
warning_filter_keys = ["action", "message", "category", "module", "lineno"]
for filter_args in warning_filters:
this_warning_filter_dict = {
k: v
for k, v in zip(warning_filter_keys, filter_args)
if v is not None
}
if (
"message" not in this_warning_filter_dict
and "module" not in this_warning_filter_dict
):
warnings.simplefilter(**this_warning_filter_dict, append=True)
else:
for special_key in ["message", "module"]:
this_value = this_warning_filter_dict.get(special_key)
if this_value is not None and not isinstance(this_value, str):
this_warning_filter_dict[special_key] = this_value.pattern
warnings.filterwarnings(**this_warning_filter_dict, append=True)
return self.function(*args, **kwargs)
skp._FuncWrapper.__call__ = __call__
_apply()
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