


'''simple docstring'''
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						=					logging.get_logger(__name__)

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

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






class        lowerCAmelCase_  (     UpperCAmelCase	):






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

            _A				=							{} if sp_model_kwargs is None else sp_model_kwargs

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

            _A				=							3

            _A				=							do_lower_case
            _A				=							remove_space
            _A				=							keep_accents
            _A				=							vocab_file

            _A				=							spm.SentencePieceProcessor(**self.sp_model_kwargs   )
            self.sp_model.Load(_UpperCamelCase   )

            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				=							jieba
            _A				=							str.maketrans(' \n'			,     '\u2582\u2583'   )






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






       def   UpperCamelCase						( self   )->      List[str]:
            _A				=							{self.convert_ids_to_tokens(_UpperCamelCase   ): i for i in range(self.vocab_size   )}
            vocab.update(self.added_tokens_encoder   )
            return vocab






       def __getstate__( self   )->      Any:
            _A				=							self.__dict__.copy()
            _A				=							None
            return state






       def __setstate__( self			,     _UpperCamelCase   )->      List[Any]:
            _A				=							d

            # for backward compatibility
            if not hasattr(self			,     'sp_model_kwargs'   ):
                 _A				=							{}

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






       def   UpperCamelCase						( self			,     _UpperCamelCase   )->      str:
            if self.remove_space:
                 _A				=							' '.join(inputs.strip().split()   )
            else:
                 _A				=							inputs
            _A				=							outputs.replace('``'			,     '"'   ).replace('\'\''			,     '"'   )

            if not self.keep_accents:
                 _A				=							unicodedata.normalize('NFKD'			,     _UpperCamelCase   )
                 _A				=							''.join([c for c in outputs if not unicodedata.combining(_UpperCamelCase   )]   )
            if self.do_lower_case:
                 _A				=							outputs.lower()

            return outputs






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

            return new_pieces






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






       def   UpperCamelCase						( self			,     _UpperCamelCase   )->      Dict:
            return self.sp_model.IdToPiece(_UpperCamelCase   )






       def   UpperCamelCase						( self			,     _UpperCamelCase   )->      int:
            _A				=							''.join(_UpperCamelCase   ).replace(_UpperCamelCase			,     ' '   ).strip()
            return out_string






       def   UpperCamelCase						( self			,     _UpperCamelCase			,     _UpperCamelCase = None   )->      List[int]:
            _A				=							[self.sep_token_id]
            _A				=							[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   UpperCamelCase						( self			,     _UpperCamelCase			,     _UpperCamelCase = None			,     _UpperCamelCase = False   )->      List[int]:

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

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






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

            if os.path.abspath(self.vocab_file   ) != os.path.abspath(_UpperCamelCase   ) and os.path.isfile(self.vocab_file   ):
                 copyfile(self.vocab_file			,     _UpperCamelCase   )
            elif not os.path.isfile(self.vocab_file   ):
                 with open(_UpperCamelCase			,     'wb'   ) as fi:
                      _A				=							self.sp_model.serialized_model_proto()
                      fi.write(_UpperCamelCase   )

            return (out_vocab_file,)






       def   UpperCamelCase						( self			,     *_UpperCamelCase			,     **_UpperCamelCase   )->      Tuple:
            _A				=							super()._decode(*_UpperCamelCase			,     **_UpperCamelCase   )
            _A				=							text.replace(' '			,     ''   ).replace('\u2582'			,     ' '   ).replace('\u2583'			,     '\n'   )
            return text









'''simple docstring'''
from __future__ import annotations

def 					lowerCamelCase_ ( __UpperCamelCase					:       dict							,    __UpperCamelCase					:       str		)					->	set[str]:







     """simple docstring"""
     _A		,				_A				=							set(__UpperCamelCase		), [start]

     while stack:
          _A				=							stack.pop()
          explored.add(__UpperCamelCase		)
          # Differences from BFS:
          # 1) pop last element instead of first one
          # 2) add adjacent elements to stack without exploring them
          for adj in reversed(graph[v]		):
               if adj not in explored:
                    stack.append(__UpperCamelCase		)
     return explored


lowerCAmelCase						=					{
    """A""": ["""B""", """C""", """D"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F"""],
    """D""": ["""B""", """D"""],
    """E""": ["""B""", """F"""],
    """F""": ["""C""", """E""", """G"""],
    """G""": ["""F"""],
}

if __name__ == "__main__":
    import doctest

    doctest.testmod()
    print(depth_first_search(G, """A"""))





