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

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

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

       lowerCamelCase		:	str							=      3

       lowerCamelCase		:	List[Any]							=      do_lower_case
       lowerCamelCase		:	List[str]							=      remove_space
       lowerCamelCase		:	str							=      keep_accents
       lowerCamelCase		:	str							=      vocab_file

       lowerCamelCase		:	Any							=      spm.SentencePieceProcessor(**self.sp_model_kwargs      )
       self.sp_model.Load(__magic_name__      )

       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."""      )
       lowerCamelCase		:	List[str]							=      jieba
       lowerCamelCase		:	str							=      str.maketrans(""" \n"""    ,  """\u2582\u2583"""      )
      @property
      # Copied from transformers.models.xlnet.tokenization_xlnet.XLNetTokenizer.vocab_size
      def 						UpperCamelCase__							(      self      ):
       return len(self.sp_model      )
      def 						UpperCamelCase__							(      self      ):
       lowerCamelCase		:	Any							=      {self.convert_ids_to_tokens(__magic_name__      ): i for i in range(self.vocab_size      )}
       vocab.update(self.added_tokens_encoder      )
       return vocab
      def __getstate__(      self      ):
       lowerCamelCase		:	Optional[Any]							=      self.__dict__.copy()
       lowerCamelCase		:	Dict							=      None
       return state
      def __setstate__(      self    ,  __magic_name__      ):
       lowerCamelCase		:	Tuple							=      d

       # for backward compatibility
       if not hasattr(self    ,  """sp_model_kwargs"""      ):
        lowerCamelCase		:	int							=      {}

       lowerCamelCase		:	Optional[Any]							=      spm.SentencePieceProcessor(**self.sp_model_kwargs      )
       self.sp_model.Load(self.vocab_file      )
      def 						UpperCamelCase__							(      self    ,  __magic_name__      ):
       if self.remove_space:
        lowerCamelCase		:	Dict							=      """ """.join(inputs.strip().split()      )
       else:
        lowerCamelCase		:	Any							=      inputs
       lowerCamelCase		:	Optional[Any]							=      outputs.replace("""``"""    ,  """\""""      ).replace("""''"""    ,  """\""""      )

       if not self.keep_accents:
        lowerCamelCase		:	Any							=      unicodedata.normalize("""NFKD"""    ,  __magic_name__      )
        lowerCamelCase		:	int							=      """""".join([c for c in outputs if not unicodedata.combining(__magic_name__      )]      )
       if self.do_lower_case:
        lowerCamelCase		:	Tuple							=      outputs.lower()

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

       return new_pieces
      def 						UpperCamelCase__							(      self    ,  __magic_name__      ):
       return self.sp_model.PieceToId(__magic_name__      )
      def 						UpperCamelCase__							(      self    ,  __magic_name__      ):
       return self.sp_model.IdToPiece(__magic_name__      )
      def 						UpperCamelCase__							(      self    ,  __magic_name__      ):
       lowerCamelCase		:	str							=      """""".join(__magic_name__      ).replace(__magic_name__    ,  """ """      ).strip()
       return out_string
      def 						UpperCamelCase__							(      self    ,  __magic_name__    ,  __magic_name__ = None      ):
       lowerCamelCase		:	Tuple							=      [self.sep_token_id]
       lowerCamelCase		:	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 						UpperCamelCase__							(      self    ,  __magic_name__    ,  __magic_name__ = None    ,  __magic_name__ = False      ):

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

       if token_ids_a is not None:
        return ([0] * len(__magic_name__      )) + [1] + ([0] * len(__magic_name__      )) + [1, 1]
       return ([0] * len(__magic_name__      )) + [1, 1]
      def 						UpperCamelCase__							(      self    ,  __magic_name__    ,  __magic_name__ = None      ):
       lowerCamelCase		:	List[Any]							=      [self.sep_token_id]
       lowerCamelCase		:	str							=      [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    ,  __magic_name__    ,  __magic_name__ = None      ):
       if not os.path.isdir(__magic_name__      ):
        logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''      )
        return
       lowerCamelCase		:	List[Any]							=      os.path.join(
           __magic_name__    ,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]      )

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

       return (out_vocab_file,)






      def 						UpperCamelCase__							(      self    ,  *__magic_name__    ,  **__magic_name__      ):
       lowerCamelCase		:	int							=      super()._decode(*__magic_name__    ,  **__magic_name__      )
       lowerCamelCase		:	Optional[int]							=      text.replace(""" """    ,  """"""      ).replace("""\u2582"""    ,  """ """      ).replace("""\u2583"""    ,  """\n"""      )
       return text









"""simple docstring"""
from __future__ import annotations

from collections import Counter
from random import random
class 				lowerCamelCase  :






					'''simple docstring'''





					def __init__(       self:							Tuple						)   ->	Optional[Any]:
											snake_case_ :Optional[int]						=			{}






					def    lowerCAmelCase_				(       self:							Dict						,     snake_case:							str						)   ->	None:
											snake_case_ :str						=			{}






					def    lowerCAmelCase_				(       self:							Optional[int]						,     snake_case:							str						,     snake_case:							str						,     snake_case:							float						)   ->	None:
											if nodea not in self.connections:
																	self.add_node(snake_case						)
											if nodea not in self.connections:
																	self.add_node(snake_case						)
											snake_case_ :Dict						=			probability






					def    lowerCAmelCase_				(       self:							List[Any]						)   ->	list[str]:
											return list(self.connections						)






					def    lowerCAmelCase_				(       self:							Any						,     snake_case:							str						)   ->	str:
											snake_case_ :Optional[Any]						=			0
											snake_case_ :List[str]						=			random()

											for dest in self.connections[node]:
																	current_probability += self.connections[node][dest]
																	if current_probability > random_value:
																							return dest
											return ""

def    A_  (			_lowercase,					_lowercase,					_lowercase	):







						'''simple docstring'''


						snake_case_ :List[str]						=			MarkovChainGraphUndirectedUnweighted()

						for nodea, nodea, probability in transitions:
												graph.add_transition_probability(_lowercase,					_lowercase,					_lowercase	)

						snake_case_ :int						=			Counter(graph.get_nodes()	)
						snake_case_ :Optional[Any]						=			start

						for _ in range(_lowercase	):
												snake_case_ :Tuple						=			graph.transition(_lowercase	)
												visited[node] += 1

						return visited


if __name__ == "__main__":
						import doctest

						doctest.testmod()
