

import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging


lowerCAmelCase							:  List[str]   	=						logging.get_logger(__name__)

lowerCAmelCase							:  List[str]   	=						{"""vocab_file""": """spiece.model"""}

lowerCAmelCase							:  Union[str, Any]   	=						{
    """vocab_file""": {
        """TsinghuaAI/CPM-Generate""": """https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model""",
    }
}



class   __lowercase				( UpperCAmelCase_	):




			"""simple docstring"""







			def __init__( self  :     Tuple   ,						lowerCAmelCase__  :     List[Any]   ,						lowerCAmelCase__  :     Union[str, Any]=False   ,						lowerCAmelCase__  :     Any=True   ,						lowerCAmelCase__  :     List[Any]=False   ,						lowerCAmelCase__  :     int="<s>"   ,						lowerCAmelCase__  :     str="</s>"   ,						lowerCAmelCase__  :     Tuple="<unk>"   ,						lowerCAmelCase__  :     Tuple="<sep>"   ,						lowerCAmelCase__  :     List[Any]="<pad>"   ,						lowerCAmelCase__  :     Dict="<cls>"   ,						lowerCAmelCase__  :     str="<mask>"   ,						lowerCAmelCase__  :     str=["<eop>", "<eod>"]   ,						lowerCAmelCase__  :     Optional[Dict[str, Any]] = None   ,						**lowerCAmelCase__  :     List[Any]   ,						):
									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       AddedToken(lowerCAmelCase__   ,						lstrip=lowerCAmelCase__   ,						rstrip=lowerCAmelCase__) if isinstance(lowerCAmelCase__   ,						lowerCAmelCase__) else mask_token

									SCREAMING_SNAKE_CASE_: Optional[int]  		=       {} if sp_model_kwargs is None else sp_model_kwargs

									super().__init__(
									    do_lower_case=lowerCAmelCase__   ,						remove_space=lowerCAmelCase__   ,						keep_accents=lowerCAmelCase__   ,						bos_token=lowerCAmelCase__   ,						eos_token=lowerCAmelCase__   ,						unk_token=lowerCAmelCase__   ,						sep_token=lowerCAmelCase__   ,						pad_token=lowerCAmelCase__   ,						cls_token=lowerCAmelCase__   ,						mask_token=lowerCAmelCase__   ,						additional_special_tokens=lowerCAmelCase__   ,						sp_model_kwargs=self.sp_model_kwargs   ,						**lowerCAmelCase__   ,						)

									SCREAMING_SNAKE_CASE_: str  		=       3

									SCREAMING_SNAKE_CASE_: List[Any]  		=       do_lower_case
									SCREAMING_SNAKE_CASE_: Any  		=       remove_space
									SCREAMING_SNAKE_CASE_: Dict  		=       keep_accents
									SCREAMING_SNAKE_CASE_: List[str]  		=       vocab_file

									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       spm.SentencePieceProcessor(**self.sp_model_kwargs)
									self.sp_model.Load(lowerCAmelCase__)

									try:
															import jieba
									except ModuleNotFoundError as error:
															raise error.__class__(
															    "You need to install jieba to use CpmTokenizer or CpmTokenizerFast. "
															    "See https://pypi.org/project/jieba/ for installation.")
									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       jieba
									SCREAMING_SNAKE_CASE_: List[Any]  		=       str.maketrans(" \n"   ,						"\u2582\u2583")



			@property
			# Copied from transformers.models.xlnet.tokenization_xlnet.XLNetTokenizer.vocab_size
			def        _SCREAMING_SNAKE_CASE			( self  :     List[Any]):
									return len(self.sp_model)



			def        _SCREAMING_SNAKE_CASE			( self  :     Any):
									SCREAMING_SNAKE_CASE_: List[Any]  		=       {self.convert_ids_to_tokens(lowerCAmelCase__): i for i in range(self.vocab_size)}
									vocab.update(self.added_tokens_encoder)
									return vocab



			def __getstate__( self  :     Union[str, Any]):
									SCREAMING_SNAKE_CASE_: str  		=       self.__dict__.copy()
									SCREAMING_SNAKE_CASE_: List[str]  		=       None
									return state



			def __setstate__( self  :     Optional[Any]   ,						lowerCAmelCase__  :     int):
									SCREAMING_SNAKE_CASE_: Any  		=       d

									# for backward compatibility
									if not hasattr(self   ,						"sp_model_kwargs"):
															SCREAMING_SNAKE_CASE_: List[str]  		=       {}

									SCREAMING_SNAKE_CASE_: int  		=       spm.SentencePieceProcessor(**self.sp_model_kwargs)
									self.sp_model.Load(self.vocab_file)



			def        _SCREAMING_SNAKE_CASE			( self  :     int   ,						lowerCAmelCase__  :     List[Any]):
									if self.remove_space:
															SCREAMING_SNAKE_CASE_: Dict  		=       " ".join(inputs.strip().split())
									else:
															SCREAMING_SNAKE_CASE_: Optional[Any]  		=       inputs
									SCREAMING_SNAKE_CASE_: str  		=       outputs.replace("``"   ,						"\"").replace("''"   ,						"\"")

									if not self.keep_accents:
															SCREAMING_SNAKE_CASE_: Dict  		=       unicodedata.normalize("NFKD"   ,						lowerCAmelCase__)
															SCREAMING_SNAKE_CASE_: int  		=       "".join([c for c in outputs if not unicodedata.combining(lowerCAmelCase__)])
									if self.do_lower_case:
															SCREAMING_SNAKE_CASE_: List[str]  		=       outputs.lower()

									return outputs



			def        _SCREAMING_SNAKE_CASE			( self  :     List[Any]   ,						lowerCAmelCase__  :     str):
									SCREAMING_SNAKE_CASE_: List[str]  		=       self.preprocess_text(lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Dict  		=       self.sp_model.encode(lowerCAmelCase__   ,						out_type=lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Any  		=       []
									for piece in pieces:
															if len(lowerCAmelCase__) > 1 and piece[-1] == str(",") and piece[-2].isdigit():
																					SCREAMING_SNAKE_CASE_: str  		=       self.sp_model.EncodeAsPieces(piece[:-1].replace(lowerCAmelCase__   ,						""))
																					if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																											if len(cur_pieces[0]) == 1:
																																	SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       cur_pieces[1:]
																											else:
																																	SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       cur_pieces[0][1:]
																					cur_pieces.append(piece[-1])
																					new_pieces.extend(lowerCAmelCase__)
															else:
																					new_pieces.append(lowerCAmelCase__)

									return new_pieces



			def        _SCREAMING_SNAKE_CASE			( self  :     List[str]   ,						lowerCAmelCase__  :     Union[str, Any]):
									return self.sp_model.PieceToId(lowerCAmelCase__)



			def        _SCREAMING_SNAKE_CASE			( self  :     List[str]   ,						lowerCAmelCase__  :     List[str]):
									return self.sp_model.IdToPiece(lowerCAmelCase__)



			def        _SCREAMING_SNAKE_CASE			( self  :     Optional[Any]   ,						lowerCAmelCase__  :     Optional[Any]):
									SCREAMING_SNAKE_CASE_: Dict  		=       "".join(lowerCAmelCase__).replace(lowerCAmelCase__   ,						" ").strip()
									return out_string



			def        _SCREAMING_SNAKE_CASE			( self  :     Optional[int]   ,						lowerCAmelCase__  :     List[int]   ,						lowerCAmelCase__  :     Optional[List[int]] = None):
									SCREAMING_SNAKE_CASE_: List[str]  		=       [self.sep_token_id]
									SCREAMING_SNAKE_CASE_: Tuple  		=       [self.cls_token_id]
									if token_ids_a is None:
															return token_ids_a + sep + cls
									return token_ids_a + sep + token_ids_a + sep + cls



			def        _SCREAMING_SNAKE_CASE			( self  :     Tuple   ,						lowerCAmelCase__  :     List[int]   ,						lowerCAmelCase__  :     Optional[List[int]] = None   ,						lowerCAmelCase__  :     bool = False):

									if already_has_special_tokens:
															return super().get_special_tokens_mask(
															    token_ids_a=lowerCAmelCase__   ,						token_ids_a=lowerCAmelCase__   ,						already_has_special_tokens=lowerCAmelCase__)

									if token_ids_a is not None:
															return ([0] * len(lowerCAmelCase__)) + [1] + ([0] * len(lowerCAmelCase__)) + [1, 1]
									return ([0] * len(lowerCAmelCase__)) + [1, 1]



			def        _SCREAMING_SNAKE_CASE			( self  :     int   ,						lowerCAmelCase__  :     List[int]   ,						lowerCAmelCase__  :     Optional[List[int]] = None):
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       [self.sep_token_id]
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       [2]

									if token_ids_a is None:
															return len(token_ids_a + sep) * [0] + cls_segment_id
									return len(token_ids_a + sep) * [0] + len(token_ids_a + sep) * [1] + cls_segment_id



			def        _SCREAMING_SNAKE_CASE			( self  :     List[str]   ,						lowerCAmelCase__  :     str   ,						lowerCAmelCase__  :     Optional[str] = None):
									if not os.path.isdir(lowerCAmelCase__):
															logger.error(F"Vocabulary path ({save_directory}) should be a directory")
															return
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       os.path.join(
									    lowerCAmelCase__   ,						(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"])

									if os.path.abspath(self.vocab_file) != os.path.abspath(lowerCAmelCase__) and os.path.isfile(self.vocab_file):
															copyfile(self.vocab_file   ,						lowerCAmelCase__)
									elif not os.path.isfile(self.vocab_file):
															with open(lowerCAmelCase__   ,						"wb") as fi:
																					SCREAMING_SNAKE_CASE_: Optional[int]  		=       self.sp_model.serialized_model_proto()
																					fi.write(lowerCAmelCase__)

									return (out_vocab_file,)




			def        _SCREAMING_SNAKE_CASE			( self  :     str   ,						*lowerCAmelCase__  :     Optional[int]   ,						**lowerCAmelCase__  :     Union[str, Any]):
									SCREAMING_SNAKE_CASE_: List[str]  		=       super()._decode(*lowerCAmelCase__   ,						**lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Any  		=       text.replace(" "   ,						"").replace("\u2582"   ,						" ").replace("\u2583"   ,						"\n")
									return text









def 			A_      (    _UpperCAmelCase				,	_UpperCAmelCase = False    ):

						if not isinstance(_UpperCAmelCase				,	_UpperCAmelCase    ):
												SCREAMING_SNAKE_CASE_: str  		=       f"Expected string as input, found {type(_UpperCAmelCase    )}"
												raise ValueError(_UpperCAmelCase    )
						if not isinstance(_UpperCAmelCase				,	_UpperCAmelCase    ):
												SCREAMING_SNAKE_CASE_: Optional[Any]  		=       f"Expected boolean as use_pascal parameter, found {type(_UpperCAmelCase    )}"
												raise ValueError(_UpperCAmelCase    )

						SCREAMING_SNAKE_CASE_: Tuple  		=       input_str.split("_"    )

						SCREAMING_SNAKE_CASE_: str  		=       0 if use_pascal else 1

						SCREAMING_SNAKE_CASE_: int  		=       words[start_index:]

						SCREAMING_SNAKE_CASE_: List[str]  		=       [word[0].upper() + word[1:] for word in words_to_capitalize]

						SCREAMING_SNAKE_CASE_: List[Any]  		=       "" if use_pascal else words[0]

						return "".join([initial_word, *capitalized_words]    )


if __name__ == "__main__":
						from doctest import testmod

						testmod()






