def __init__(
self,
id: str,
name: str,
class_def: type,
eq_function: Optional[type] = None,
args: Dict[str, Any] = None,
is_special: bool = False,
tune_grid: Dict[str, list] = None,
tune_distribution: Dict[str, Distribution] = None,
tune_args: Dict[str, Any] = None,
is_gpu_enabled: Optional[bool] = None,
) -> None:
if not args:
args = {}
if not tune_grid:
tune_grid = {}
if not tune_distribution:
tune_distribution = {}
if not tune_args:
tune_args = {}
super().__init__(
id=id,
name=name,
class_def=class_def,
eq_function=eq_function,
args=args,
is_special=is_special,
)
self.tune_grid = param_grid_to_lists(tune_grid)
self.tune_distribution = tune_distribution
self.tune_args = tune_args
if is_gpu_enabled is not None:
self.is_gpu_enabled = is_gpu_enabled
else:
self.is_gpu_enabled = bool(self.get_package_name() == "cuml")
def __init__(
self,
id: str,
name: str,
class_def: type,
is_turbo: bool = True,
eq_function: Optional[type] = None,
args: Dict[str, Any] = None,
is_special: bool = False,
tune_grid: Dict[str, list] = None,
tune_distribution: Dict[str, Distribution] = None,
tune_args: Dict[str, Any] = None,
shap: Union[bool, str] = False,
is_gpu_enabled: Optional[bool] = None,
is_boosting_supported: Optional[bool] = None,
is_soft_voting_supported: Optional[bool] = None,
) -> None:
self.shap = shap
if not (isinstance(shap, bool) or shap in ["type1", "type2"]):
raise ValueError("shap must be either bool or 'type1', 'type2'.")
if not args:
args = {}
if not tune_grid:
tune_grid = {}
if not tune_distribution:
tune_distribution = {}
if not tune_args:
tune_args = {}
super().__init__(
id=id,
name=name,
class_def=class_def,
eq_function=eq_function,
args=args,
is_special=is_special,
)
self.is_turbo = is_turbo
self.tune_grid = param_grid_to_lists(tune_grid)
self.tune_distribution = tune_distribution
self.tune_args = tune_args
try:
model_instance = class_def()
self.is_boosting_supported = bool(
hasattr(model_instance, "class_weights")
or hasattr(model_instance, "predict_proba"))
self.is_soft_voting_supported = bool(
hasattr(model_instance, "predict_proba"))
del model_instance
except:
self.is_boosting_supported = False
self.is_soft_voting_supported = False
finally:
if is_boosting_supported is not None:
self.is_boosting_supported = is_boosting_supported
if is_soft_voting_supported is not None:
self.is_soft_voting_supported = is_soft_voting_supported
if is_gpu_enabled is not None:
self.is_gpu_enabled = is_gpu_enabled
else:
self.is_gpu_enabled = bool(self.get_package_name() == "cuml")