




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


_snake_case										=       logging.get_logger(__name__)

_snake_case										=       {"vocab_file": "spiece.model"}

_snake_case										=       {
    "vocab_file": {
        "TsinghuaAI/CPM-Generate": "https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model",
    }
}







class 						lowercase							(   UpperCamelCase__		):

     def __init__(  self		,     _a		,     _a=False		,     _a=True		,     _a=False		,     _a="<s>"		,     _a="</s>"		,     _a="<unk>"		,     _a="<sep>"		,     _a="<pad>"		,     _a="<cls>"		,     _a="<mask>"		,     _a=["<eop>", "<eod>"]		,     _a = None		,     **_a		,     )						->							None:
           _A							:     Dict			=						AddedToken(_a		,     lstrip=_a		,     rstrip=_a				) if isinstance(_a		,     _a				) else mask_token

           _A							:     int			=						{} if sp_model_kwargs is None else sp_model_kwargs

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

           _A							:     List[str]			=						3

           _A							:     List[str]			=						do_lower_case
           _A							:     Dict			=						remove_space
           _A							:     Optional[int]			=						keep_accents
           _A							:     Union[str, Any]			=						vocab_file

           _A							:     int			=						spm.SentencePieceProcessor(**self.sp_model_kwargs				)
           self.sp_model.Load(_a				)

           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."""				)
           _A							:     Optional[int]			=						jieba
           _A							:     Union[str, Any]			=						str.maketrans(""" \n"""		,     """\u2582\u2583"""				)

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

     def 					a__	(  self				)						->							Tuple:
           _A							:     Optional[Any]			=						{self.convert_ids_to_tokens(_a				): i for i in range(self.vocab_size				)}
           vocab.update(self.added_tokens_encoder				)
           return vocab

     def __getstate__(  self				)						->							Tuple:
           _A							:     List[Any]			=						self.__dict__.copy()
           _A							:     Optional[int]			=						None
           return state

     def __setstate__(  self		,     _a				)						->							Union[str, Any]:
           _A							:     Dict			=						d

           # for backward compatibility
           if not hasattr(self		,     """sp_model_kwargs"""				):
                 _A							:     Optional[int]			=						{}

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

     def 					a__	(  self		,     _a				)						->							str:
           if self.remove_space:
                 _A							:     Dict			=						""" """.join(inputs.strip().split()				)
           else:
                 _A							:     List[str]			=						inputs
           _A							:     str			=						outputs.replace("""``"""		,     """\""""				).replace("""''"""		,     """\""""				)

           if not self.keep_accents:
                 _A							:     List[str]			=						unicodedata.normalize("""NFKD"""		,     _a				)
                 _A							:     Dict			=						"""""".join([c for c in outputs if not unicodedata.combining(_a				)]				)
           if self.do_lower_case:
                 _A							:     Union[str, Any]			=						outputs.lower()

           return outputs

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

           return new_pieces

     def 					a__	(  self		,     _a				)						->							Union[str, Any]:
           return self.sp_model.PieceToId(_a				)

     def 					a__	(  self		,     _a				)						->							Optional[Any]:
           return self.sp_model.IdToPiece(_a				)

     def 					a__	(  self		,     _a				)						->							int:
           _A							:     Tuple			=						"""""".join(_a				).replace(_a		,     """ """				).strip()
           return out_string

     def 					a__	(  self		,     _a		,     _a = None				)						->							List[int]:
           _A							:     Dict			=						[self.sep_token_id]
           _A							:     Union[str, Any]			=						[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 					a__	(  self		,     _a		,     _a = None		,     _a = False				)						->							List[int]:

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

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

     def 					a__	(  self		,     _a		,     _a = None				)						->							List[int]:
           _A							:     Union[str, Any]			=						[self.sep_token_id]
           _A							:     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 					a__	(  self		,     _a		,     _a = None				)						->							Tuple[str]:
           if not os.path.isdir(_a				):
                 logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''				)
                 return
           _A							:     Optional[int]			=						os.path.join(
               _a		,     (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)

           if os.path.abspath(self.vocab_file				) != os.path.abspath(_a				) and os.path.isfile(self.vocab_file				):
                 copyfile(self.vocab_file		,     _a				)
           elif not os.path.isfile(self.vocab_file				):
                 with open(_a		,     """wb"""				) as fi:
                       _A							:     List[Any]			=						self.sp_model.serialized_model_proto()
                       fi.write(_a				)

           return (out_vocab_file,)



     def 					a__	(  self		,     *_a		,     **_a				)						->							Optional[Any]:
           _A							:     Optional[Any]			=						super()._decode(*_a		,     **_a				)
           _A							:     Optional[int]			=						text.replace(""" """		,     """"""				).replace("""\u2582"""		,     """ """				).replace("""\u2583"""		,     """\n"""				)
           return text







def 				lowerCAmelCase_	(     snake_case_,snake_case_     ):
      while b:
            _A			,   _A							:     List[str]			=						b, a % b
      return a







def 				lowerCAmelCase_	(     snake_case_,snake_case_     ):
      return a if b == 0 else euclidean_gcd_recursive(snake_case_,a % b     )







def 				lowerCAmelCase_	(     ):
      print(f'''euclidean_gcd(3, 5) = {euclidean_gcd(3,5     )}'''     )
      print(f'''euclidean_gcd(5, 3) = {euclidean_gcd(5,3     )}'''     )
      print(f'''euclidean_gcd(1, 3) = {euclidean_gcd(1,3     )}'''     )
      print(f'''euclidean_gcd(3, 6) = {euclidean_gcd(3,6     )}'''     )
      print(f'''euclidean_gcd(6, 3) = {euclidean_gcd(6,3     )}'''     )

      print(f'''euclidean_gcd_recursive(3, 5) = {euclidean_gcd_recursive(3,5     )}'''     )
      print(f'''euclidean_gcd_recursive(5, 3) = {euclidean_gcd_recursive(5,3     )}'''     )
      print(f'''euclidean_gcd_recursive(1, 3) = {euclidean_gcd_recursive(1,3     )}'''     )
      print(f'''euclidean_gcd_recursive(3, 6) = {euclidean_gcd_recursive(3,6     )}'''     )
      print(f'''euclidean_gcd_recursive(6, 3) = {euclidean_gcd_recursive(6,3     )}'''     )


if __name__ == "__main__":
  main()

