# Original work of safe_instance:
# https://github.com/slundberg/shap/blob/master/shap/common.py
# -----------------------------------------------------------------------------
# The MIT License (MIT)
#
# Copyright (c) 2018 Scott Lundberg
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# furnished to do so, subject to the following conditions:
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# SOFTWARE.
# -----------------------------------------------------------------------------
import importlib
from typing import List, Tuple, Union
[docs]def is_instance(obj, class_path_str: Union[str, List, Tuple]) -> bool:
"""
Acts as a safe version of isinstance without having to explicitly
import packages which may not exist in the users environment.
Checks if obj is an instance of type specified by class_path_str.
Parameters
----------
obj: Any
Some object you want to test against
class_path_str: str or list
A string or list of strings specifying full class paths
Example: `sklearn.ensemble.RandomForestRegressor`
Returns
--------
bool: True if isinstance is true and the package exists, False otherwise
"""
if isinstance(class_path_str, str):
class_path_strs = [class_path_str]
elif isinstance(class_path_str, list) or isinstance(class_path_str, tuple):
class_path_strs = class_path_str
else:
class_path_strs = ['']
# try each module path in order
for class_path_str in class_path_strs:
if "." not in class_path_str:
raise ValueError("class_path_str must be a string or list of strings specifying a full \
module path to a class. Eg, 'sklearn.ensemble.RandomForestRegressor'")
# Splits on last occurence of "."
module_name, class_name = class_path_str.rsplit(".", 1)
# Check module exists
try:
spec = importlib.util.find_spec(module_name)
except:
spec = None
if spec is None:
continue
module = importlib.import_module(module_name)
# Get class
_class = getattr(module, class_name, None)
if _class is None:
continue
if isinstance(obj, _class):
return True
return False
def is_gbdt_instance(obj, algorithm_type: Union[str, Tuple]) -> bool:
if isinstance(algorithm_type, str):
algorithm_type = (algorithm_type,)
gbdt_instance_name = {
'lgbm': 'lightgbm.sklearn.LGBMModel',
'xgb': 'xgboost.sklearn.XGBModel',
'cat': 'catboost.core.CatBoost'
}
return is_instance(obj, tuple(gbdt_instance_name[t] for t in algorithm_type))