


'''simple docstring'''



import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor







def       _UpperCamelCase (						UpperCamelCase__   ):
			return (data["data"], data["target"])







def       _UpperCamelCase (						UpperCamelCase__	, UpperCamelCase__	, UpperCamelCase__   ):
			UpperCAmelCase__					:   Tuple       				=       XGBRegressor(verbosity=0	, random_state=4_2   )
			xgb.fit(UpperCamelCase__	, UpperCamelCase__   )
			# Predict target for test data
			UpperCAmelCase__					:   Tuple       				=       xgb.predict(UpperCamelCase__   )
			UpperCAmelCase__					:   int       				=       predictions.reshape(len(UpperCamelCase__   )	, 1   )
			return predictions







def       _UpperCamelCase (						):
			UpperCAmelCase__					:   Tuple       				=       fetch_california_housing()
			UpperCAmelCase__				,    UpperCAmelCase__					:   Union[str, Any]       				=       data_handling(UpperCamelCase__   )
			UpperCAmelCase__				,    UpperCAmelCase__				,    UpperCAmelCase__				,    UpperCAmelCase__					:   str       				=       train_test_split(
			    UpperCamelCase__	, UpperCamelCase__	, test_size=0.25	, random_state=1   )
			UpperCAmelCase__					:   Optional[int]       				=       xgboost(UpperCamelCase__	, UpperCamelCase__	, UpperCamelCase__   )
			# Error printing
			print(f'''Mean Absolute Error : {mean_absolute_error(UpperCamelCase__	, UpperCamelCase__   )}'''   )
			print(f'''Mean Square Error  : {mean_squared_error(UpperCamelCase__	, UpperCamelCase__   )}'''   )


if __name__ == "__main__":
		import doctest

		doctest.testmod(verbose=True)
		main()



'''simple docstring'''



import os
from datetime import datetime as dt

from github import Github


__A		=[
    'good first issue',
    'good second issue',
    'good difficult issue',
    'enhancement',
    'new pipeline/model',
    'new scheduler',
    'wip',
]







def       _UpperCamelCase (						):
			UpperCAmelCase__					:   Union[str, Any]       				=       Github(os.environ["""GITHUB_TOKEN"""]   )
			UpperCAmelCase__					:   Any       				=       g.get_repo("""huggingface/diffusers"""   )
			UpperCAmelCase__					:   Optional[int]       				=       repo.get_issues(state="""open"""   )

			for issue in open_issues:
						UpperCAmelCase__					:   Any       				=       sorted(issue.get_comments()	, key=lambda UpperCamelCase__   : i.created_at	, reverse=UpperCamelCase__   )
						UpperCAmelCase__					:   List[Any]       				=       comments[0] if len(UpperCamelCase__   ) > 0 else None
						if (
						    last_comment is not None
						    and last_comment.user.login == "github-actions[bot]"
						    and (dt.utcnow() - issue.updated_at).days > 7
						    and (dt.utcnow() - issue.created_at).days >= 3_0
						    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()   )
						):
									# Closes the issue after 7 days of inactivity since the Stalebot notification.
									issue.edit(state="""closed"""   )
						elif (
						    "stale" in issue.get_labels()
						    and last_comment is not None
						    and last_comment.user.login != "github-actions[bot]"
						):
									# Opens the issue if someone other than Stalebot commented.
									issue.edit(state="""open"""   )
									issue.remove_from_labels("""stale"""   )
						elif (
						    (dt.utcnow() - issue.updated_at).days > 2_3
						    and (dt.utcnow() - issue.created_at).days >= 3_0
						    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()   )
						):
									# Post a Stalebot notification after 23 days of inactivity.
									issue.create_comment(
									    """This issue has been automatically marked as stale because it has not had """
									    """recent activity. If you think this still needs to be addressed """
									    """please comment on this thread.\n\nPlease note that issues that do not follow the """
									    """[contributing guidelines](https://github.com/huggingface/diffusers/blob/main/CONTRIBUTING.md) """
									    """are likely to be ignored."""   )
									issue.add_to_labels("""stale"""   )


if __name__ == "__main__":
		main()