import warnings
import lightgbm as lgb
from optuna import type_checking
if type_checking.TYPE_CHECKING:
from typing import Any # NOQA
from typing import Dict # NOQA
from typing import List # NOQA
class LGBMModel(lgb.LGBMModel):
"""Proxy of lightgbm.LGBMModel.
See: `pydoc lightgbm.LGBMModel`
"""
def __init__(self, *args, **kwargs):
# type: (List[Any], Dict[str, Any]) -> None
warnings.warn(
"LightGBMTuner doesn't support sklearn API. "
"Use `train()` or `LightGBMTuner` for hyperparameter tuning."
)
super(LGBMModel, self).__init__(*args, **kwargs)
class LGBMClassifier(lgb.LGBMClassifier):
"""Proxy of lightgbm.LGBMClassifier.
See: `pydoc lightgbm.LGBMClassifier`
"""
def __init__(self, *args, **kwargs):
# type: (List[Any], Dict[str, Any]) -> None
warnings.warn(
"LightGBMTuner doesn't support sklearn API. "
"Use `train()` or `LightGBMTuner` for hyperparameter tuning."
)
super(LGBMClassifier, self).__init__(*args, **kwargs)
class LGBMRegressor(lgb.LGBMRegressor):
"""Proxy of LGBMRegressor.
See: `pydoc lightgbm.LGBMRegressor`
"""
def __init__(self, *args, **kwargs):
# type: (List[Any], Dict[str, Any]) -> None
warnings.warn(
"LightGBMTuner doesn't support sklearn API. "
"Use `train()` or `LightGBMTuner` for hyperparameter tuning."
)
super(LGBMRegressor, self).__init__(*args, **kwargs)
