| """ |
| 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() |
|
|
