



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  lowerCAmelCase_	(lowerCAmelCase__:		dict  ):





			"""simple docstring"""


			return (data["data"], data["target"])







def  lowerCAmelCase_	(lowerCAmelCase__:		np.ndarray		,						lowerCAmelCase__:		np.ndarray		,						lowerCAmelCase__:		np.ndarray  ):





			"""simple docstring"""


			UpperCAmelCase_:		Tuple							      =     XGBRegressor(verbosity=0		,						random_state=4_2  )
			xgb.fit(a__		,						a__  )
			# Predict target for test data
			UpperCAmelCase_:		List[Any]							      =     xgb.predict(a__  )
			UpperCAmelCase_:		Union[str, Any]							      =     predictions.reshape(len(a__  )		,						1  )
			return predictions







def  lowerCAmelCase_	():





			"""simple docstring"""


			UpperCAmelCase_:		str							      =     fetch_california_housing()
			UpperCAmelCase_      ,							UpperCAmelCase_:		Tuple							      =     data_handling(a__  )
			UpperCAmelCase_      ,							UpperCAmelCase_      ,							UpperCAmelCase_      ,							UpperCAmelCase_:		List[str]							      =     train_test_split(
			    a__		,						a__		,						test_size=0.25		,						random_state=1  )
			UpperCAmelCase_:		Union[str, Any]							      =     xgboost(a__		,						a__		,						a__  )
			# Error printing
			print(F'Mean Absolute Error : {mean_absolute_error(a__		,						a__  )}'  )
			print(F'Mean Square Error  : {mean_squared_error(a__		,						a__  )}'  )


if __name__ == "__main__":
	import doctest

	doctest.testmod(verbose=True)
	main()













# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re

from ..utils import cached_file


# docstyle-ignore
UpperCamelCase__           =			"\nHuman: <<task>>\n\nAssistant: "


UpperCamelCase__           =			"huggingface-tools/default-prompts"
UpperCamelCase__           =			{"chat": "chat_prompt_template.txt", "run": "run_prompt_template.txt"}





def      _UpperCamelCase  (a__ :List[Any] ,      a__ :Optional[Any] ,      a__ :List[str]="run"							):






							"""simple docstring"""





							if prompt_or_repo_id is None:
														UpperCamelCase__					  =      DEFAULT_PROMPTS_REPO

							# prompt is considered a repo ID when it does not contain any kind of space
							if re.search("""\\s""" ,      a__							) is not None:
														return prompt_or_repo_id

							UpperCamelCase__					  =      cached_file(
							    a__ ,      PROMPT_FILES[mode] ,      repo_type="""dataset""" ,      user_agent={"""agent""": agent_name}							)
							with open(a__ ,      """r""" ,      encoding="""utf-8"""							) as f:
														return f.read()




