


"""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


__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 _lowerCAmelCase				(      snake_case_	):







   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:

       '''simple docstring'''




       snake_case    :      Union[str, Any]      					=    AddedToken(UpperCamelCase__						,	lstrip=UpperCamelCase__						,	rstrip=UpperCamelCase__						) if isinstance(UpperCamelCase__						,	UpperCamelCase__						) else mask_token

       snake_case    :      List[str]      					=    {} 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__						,	)

       snake_case    :      Any      					=    3

       snake_case    :      Dict      					=    do_lower_case
       snake_case    :      Optional[Any]      					=    remove_space
       snake_case    :      Optional[Any]      					=    keep_accents
       snake_case    :      Optional[int]      					=    vocab_file

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







   @property
   # Copied from transformers.models.xlnet.tokenization_xlnet.XLNetTokenizer.vocab_size
   def  lowerCamelCase		(	self						)	->		Tuple:

       '''simple docstring'''




       return len(self.sp_model						)







   def  lowerCamelCase		(	self						)	->		str:

       '''simple docstring'''




       snake_case    :      List[Any]      					=    {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						)	->		Union[str, Any]:

       '''simple docstring'''




       snake_case    :      int      					=    self.__dict__.copy()
       snake_case    :      Union[str, Any]      					=    None
       return state







   def __setstate__(	self						,	UpperCamelCase__						)	->		List[Any]:

       '''simple docstring'''




       snake_case    :      Union[str, Any]      					=    d

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

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







   def  lowerCamelCase		(	self						,	UpperCamelCase__						)	->		Any:

       '''simple docstring'''




       if self.remove_space:
           snake_case    :      Tuple      					=    " ".join(inputs.strip().split()						)
       else:
           snake_case    :      Union[str, Any]      					=    inputs
       snake_case    :      Tuple      					=    outputs.replace("``"						,	"\""						).replace("''"						,	"\""						)

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

       return outputs







   def  lowerCamelCase		(	self						,	UpperCamelCase__						)	->		List[str]:

       '''simple docstring'''




       snake_case    :      Tuple      					=    self.preprocess_text(UpperCamelCase__						)
       snake_case    :      Tuple      					=    self.sp_model.encode(UpperCamelCase__						,	out_type=UpperCamelCase__						)
       snake_case    :      Optional[int]      					=    []
       for piece in pieces:
           if len(UpperCamelCase__						) > 1 and piece[-1] == str(","						) and piece[-2].isdigit():
               snake_case    :      List[str]      					=    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:
                       snake_case    :      Optional[int]      					=    cur_pieces[1:]
                   else:
                       snake_case    :      Any      					=    cur_pieces[0][1:]
               cur_pieces.append(piece[-1]						)
               new_pieces.extend(UpperCamelCase__						)
           else:
               new_pieces.append(UpperCamelCase__						)

       return new_pieces







   def  lowerCamelCase		(	self						,	UpperCamelCase__						)	->		int:

       '''simple docstring'''




       return self.sp_model.PieceToId(UpperCamelCase__						)







   def  lowerCamelCase		(	self						,	UpperCamelCase__						)	->		Tuple:

       '''simple docstring'''




       return self.sp_model.IdToPiece(UpperCamelCase__						)







   def  lowerCamelCase		(	self						,	UpperCamelCase__						)	->		Optional[int]:

       '''simple docstring'''




       snake_case    :      Optional[int]      					=    "".join(UpperCamelCase__						).replace(UpperCamelCase__						,	" "						).strip()
       return out_string







   def  lowerCamelCase		(	self						,	UpperCamelCase__						,	UpperCamelCase__ = None						)	->		List[int]:

       '''simple docstring'''




       snake_case    :      Optional[int]      					=    [self.sep_token_id]
       snake_case    :      Dict      					=    [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  lowerCamelCase		(	self						,	UpperCamelCase__						,	UpperCamelCase__ = None						,	UpperCamelCase__ = False						)	->		List[int]:

       '''simple docstring'''




       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  lowerCamelCase		(	self						,	UpperCamelCase__						,	UpperCamelCase__ = None						)	->		List[int]:

       '''simple docstring'''




       snake_case    :      Dict      					=    [self.sep_token_id]
       snake_case    :      Tuple      					=    [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  lowerCamelCase		(	self						,	UpperCamelCase__						,	UpperCamelCase__ = None						)	->		Tuple[str]:

       '''simple docstring'''




       if not os.path.isdir(UpperCamelCase__						):
           logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
           return
       snake_case    :      str      					=    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:
               snake_case    :      Optional[Any]      					=    self.sp_model.serialized_model_proto()
               fi.write(UpperCamelCase__						)

       return (out_vocab_file,)







   def  lowerCamelCase		(	self						,	*UpperCamelCase__						,	**UpperCamelCase__						)	->		List[str]:

       '''simple docstring'''




       snake_case    :      Dict      					=    super()._decode(*UpperCamelCase__						,	**UpperCamelCase__						)
       snake_case    :      Optional[int]      					=    text.replace(" "						,	""						).replace("\u2582"						,	" "						).replace("\u2583"						,	"\n"						)
       return text









"""simple docstring"""



def   __lowerCAmelCase						(						lowercase  :  list[int] )	->						float:


    """simple docstring"""





    if not nums:  # Makes sure that the list is not empty
        raise ValueError("List is empty" )

    snake_case    :      List[str]      					=    sum(lowercase ) / len(lowercase )  # Calculate the average
    return sum(abs(x - average ) for x in nums ) / len(lowercase )


if __name__ == "__main__":
  import doctest

  doctest.testmod()





