





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  (a__ :dict							):






							"""simple docstring"""





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





def      _UpperCamelCase  (a__ :np.ndarray ,      a__ :np.ndarray ,      a__ :np.ndarray							):






							"""simple docstring"""





							UpperCamelCase__					  =      XGBRegressor(verbosity=0 ,      random_state=42							)
							xgb.fit(a__ ,      a__							)
							# Predict target for test data
							UpperCamelCase__					  =      xgb.predict(a__							)
							UpperCamelCase__					  =      predictions.reshape(len(a__							) ,      1							)
							return predictions





def      _UpperCamelCase  ():






							"""simple docstring"""





							UpperCamelCase__					  =      fetch_california_housing()
							UpperCamelCase__  ,  UpperCamelCase__					  =      data_handling(a__							)
							UpperCamelCase__  ,  UpperCamelCase__  ,  UpperCamelCase__  ,  UpperCamelCase__					  =      train_test_split(
							    a__ ,      a__ ,      test_size=0.25 ,      random_state=1							)
							UpperCamelCase__					  =      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()











import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


UpperCamelCase__           =			logging.get_logger(__name__)

UpperCamelCase__           =			{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

UpperCamelCase__           =			{
    "vocab_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/vocab.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/vocab.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/vocab.json",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/merges.txt",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/merges.txt",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/merges.txt",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt"
        ),
    },
    "tokenizer_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/tokenizer.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/tokenizer.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json",
        "roberta-base-openai-detector": (
            "https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json"
        ),
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json"
        ),
    },
}

UpperCamelCase__           =			{
    "roberta-base": 512,
    "roberta-large": 512,
    "roberta-large-mnli": 512,
    "distilroberta-base": 512,
    "roberta-base-openai-detector": 512,
    "roberta-large-openai-detector": 512,
}

class 							__SCREAMING_SNAKE_CASE       (  _a							):
							snake_case  :   Optional[Any]      =							VOCAB_FILES_NAMES
							snake_case  :   Optional[Any]      =							PRETRAINED_VOCAB_FILES_MAP
							snake_case  :   Any      =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							snake_case  :   Dict      =							["""input_ids""", """attention_mask"""]
							snake_case  :   List[Any]      =							RobertaTokenizer






							def __init__(    self	,			__lowerCAmelCase=None	,			__lowerCAmelCase=None	,			__lowerCAmelCase=None	,			__lowerCAmelCase="replace"	,			__lowerCAmelCase="<s>"	,			__lowerCAmelCase="</s>"	,			__lowerCAmelCase="</s>"	,			__lowerCAmelCase="<s>"	,			__lowerCAmelCase="<unk>"	,			__lowerCAmelCase="<pad>"	,			__lowerCAmelCase="<mask>"	,			__lowerCAmelCase=False	,			__lowerCAmelCase=True	,			**__lowerCAmelCase	,			):
														super().__init__(
														    __lowerCAmelCase	,			__lowerCAmelCase	,			tokenizer_file=__lowerCAmelCase	,			errors=__lowerCAmelCase	,			bos_token=__lowerCAmelCase	,			eos_token=__lowerCAmelCase	,			sep_token=__lowerCAmelCase	,			cls_token=__lowerCAmelCase	,			unk_token=__lowerCAmelCase	,			pad_token=__lowerCAmelCase	,			mask_token=__lowerCAmelCase	,			add_prefix_space=__lowerCAmelCase	,			trim_offsets=__lowerCAmelCase	,			**__lowerCAmelCase	,			)

														UpperCamelCase__					  =      json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
														if pre_tok_state.get("""add_prefix_space"""	,			__lowerCAmelCase	) != add_prefix_space:
																					UpperCamelCase__					  =      getattr(__lowerCAmelCase	,			pre_tok_state.pop("""type"""	)	)
																					UpperCamelCase__					  =      add_prefix_space
																					UpperCamelCase__					  =      pre_tok_class(**__lowerCAmelCase	)

														UpperCamelCase__					  =      add_prefix_space

														UpperCamelCase__					  =      """post_processor"""
														UpperCamelCase__					  =      getattr(self.backend_tokenizer	,			__lowerCAmelCase	,			__lowerCAmelCase	)
														if tokenizer_component_instance:
																					UpperCamelCase__					  =      json.loads(tokenizer_component_instance.__getstate__()	)

																					# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
																					if "sep" in state:
																												UpperCamelCase__					  =      tuple(state["""sep"""]	)
																					if "cls" in state:
																												UpperCamelCase__					  =      tuple(state["""cls"""]	)

																					UpperCamelCase__					  =      False

																					if state.get("""add_prefix_space"""	,			__lowerCAmelCase	) != add_prefix_space:
																												UpperCamelCase__					  =      add_prefix_space
																												UpperCamelCase__					  =      True

																					if state.get("""trim_offsets"""	,			__lowerCAmelCase	) != trim_offsets:
																												UpperCamelCase__					  =      trim_offsets
																												UpperCamelCase__					  =      True

																					if changes_to_apply:
																												UpperCamelCase__					  =      getattr(__lowerCAmelCase	,			state.pop("""type"""	)	)
																												UpperCamelCase__					  =      component_class(**__lowerCAmelCase	)
																												setattr(self.backend_tokenizer	,			__lowerCAmelCase	,			__lowerCAmelCase	)






							@property
							def 					_lowerCamelCase		(    self	):
														if self._mask_token is None:
																					if self.verbose:
																												logger.error("""Using mask_token, but it is not set yet."""	)
																					return None
														return str(self._mask_token	)






							@mask_token.setter
							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	):
														UpperCamelCase__					  =      AddedToken(__lowerCAmelCase	,			lstrip=__lowerCAmelCase	,			rstrip=__lowerCAmelCase	) if isinstance(__lowerCAmelCase	,			__lowerCAmelCase	) else value
														UpperCamelCase__					  =      value






							def 					_lowerCamelCase		(    self	,			*__lowerCAmelCase	,			**__lowerCAmelCase	):
														UpperCamelCase__					  =      kwargs.get("""is_split_into_words"""	,			__lowerCAmelCase	)
														assert self.add_prefix_space or not is_split_into_words, (
														    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
														    "to use it with pretokenized inputs."
														)

														return super()._batch_encode_plus(*__lowerCAmelCase	,			**__lowerCAmelCase	)






							def 					_lowerCamelCase		(    self	,			*__lowerCAmelCase	,			**__lowerCAmelCase	):
														UpperCamelCase__					  =      kwargs.get("""is_split_into_words"""	,			__lowerCAmelCase	)

														assert self.add_prefix_space or not is_split_into_words, (
														    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
														    "to use it with pretokenized inputs."
														)

														return super()._encode_plus(*__lowerCAmelCase	,			**__lowerCAmelCase	)






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase = None	):
														UpperCamelCase__					  =      self._tokenizer.model.save(__lowerCAmelCase	,			name=__lowerCAmelCase	)
														return tuple(__lowerCAmelCase	)






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase=None	):
														UpperCamelCase__					  =      [self.bos_token_id] + token_ids_a + [self.eos_token_id]
														if token_ids_a is None:
																					return output

														return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase = None	):
														UpperCamelCase__					  =      [self.sep_token_id]
														UpperCamelCase__					  =      [self.cls_token_id]

														if token_ids_a is None:
																					return len(cls + token_ids_a + sep	) * [0]
														return len(cls + token_ids_a + sep + sep + token_ids_a + sep	) * [0]




