




"""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


SCREAMING_SNAKE_CASE    =	logging.get_logger(__name__)

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

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




class      UpperCAmelCase_  (						A_							):




    def __init__(   self						:	List[str]     ,			snake_case_						:	Tuple     ,			snake_case_						:	Union[str, Any]=False     ,			snake_case_						:	List[str]=True     ,			snake_case_						:	Any=False     ,			snake_case_						:	Union[str, Any]="<s>"     ,			snake_case_						:	Any="</s>"     ,			snake_case_						:	Optional[Any]="<unk>"     ,			snake_case_						:	str="<sep>"     ,			snake_case_						:	List[str]="<pad>"     ,			snake_case_						:	str="<cls>"     ,			snake_case_						:	Tuple="<mask>"     ,			snake_case_						:	str=["<eop>", "<eod>"]     ,			snake_case_						:	Optional[Dict[str, Any]] = None     ,			**snake_case_						:	Tuple     ,			)				->							None:




     '''simple docstring'''

     A__	=    AddedToken(snake_case_     ,			lstrip=snake_case_     ,			rstrip=snake_case_				) if isinstance(snake_case_     ,			snake_case_				) else mask_token

     A__	=    {} if sp_model_kwargs is None else sp_model_kwargs

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

     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(snake_case_				)

     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 							__magic_name__							(   self						:	List[str]				)				->							Dict:




     '''simple docstring'''

     return len(self.sp_model				)




    def 							__magic_name__							(   self						:	List[Any]				)				->							List[Any]:




     '''simple docstring'''

     A__	=    {self.convert_ids_to_tokens(snake_case_				): i for i in range(self.vocab_size				)}
     vocab.update(self.added_tokens_encoder				)
     return vocab




    def __getstate__(   self						:	Optional[int]				)				->							str:




     '''simple docstring'''

     A__	=    self.__dict__.copy()
     A__	=    None
     return state




    def __setstate__(   self						:	List[Any]     ,			snake_case_						:	Dict				)				->							Union[str, Any]:




     '''simple docstring'''

     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 							__magic_name__							(   self						:	List[str]     ,			snake_case_						:	Dict				)				->							Union[str, Any]:




     '''simple docstring'''

     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"     ,			snake_case_				)
      A__	=    "".join([c for c in outputs if not unicodedata.combining(snake_case_				)]				)
     if self.do_lower_case:
      A__	=    outputs.lower()

     return outputs




    def 							__magic_name__							(   self						:	Optional[Any]     ,			snake_case_						:	str				)				->							List[str]:




     '''simple docstring'''

     A__	=    self.preprocess_text(snake_case_				)
     A__	=    self.sp_model.encode(snake_case_     ,			out_type=snake_case_				)
     A__	=    []
     for piece in pieces:
      if len(snake_case_				) > 1 and piece[-1] == str(","				) and piece[-2].isdigit():
       A__	=    self.sp_model.EncodeAsPieces(piece[:-1].replace(snake_case_     ,			""				)				)
       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(snake_case_				)
      else:
       new_pieces.append(snake_case_				)

     return new_pieces




    def 							__magic_name__							(   self						:	List[Any]     ,			snake_case_						:	Optional[int]				)				->							int:




     '''simple docstring'''

     return self.sp_model.PieceToId(snake_case_				)




    def 							__magic_name__							(   self						:	List[str]     ,			snake_case_						:	Union[str, Any]				)				->							str:




     '''simple docstring'''

     return self.sp_model.IdToPiece(snake_case_				)




    def 							__magic_name__							(   self						:	Union[str, Any]     ,			snake_case_						:	Union[str, Any]				)				->							str:




     '''simple docstring'''

     A__	=    "".join(snake_case_				).replace(snake_case_     ,			" "				).strip()
     return out_string




    def 							__magic_name__							(   self						:	Optional[Any]     ,			snake_case_						:	List[int]     ,			snake_case_						:	Optional[List[int]] = None				)				->							List[int]:




     '''simple docstring'''

     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 							__magic_name__							(   self						:	Any     ,			snake_case_						:	List[int]     ,			snake_case_						:	Optional[List[int]] = None     ,			snake_case_						:	bool = False				)				->							List[int]:




     '''simple docstring'''

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

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




    def 							__magic_name__							(   self						:	List[str]     ,			snake_case_						:	List[int]     ,			snake_case_						:	Optional[List[int]] = None				)				->							List[int]:




     '''simple docstring'''

     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 							__magic_name__							(   self						:	str     ,			snake_case_						:	str     ,			snake_case_						:	Optional[str] = None				)				->							Tuple[str]:




     '''simple docstring'''

     if not os.path.isdir(snake_case_				):
      logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""				)
      return
     A__	=    os.path.join(
         snake_case_     ,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]				)

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

     return (out_vocab_file,)




    def 							__magic_name__							(   self						:	List[Any]     ,			*snake_case_						:	Any     ,			**snake_case_						:	int				)				->							str:




     '''simple docstring'''

     A__	=    super()._decode(*snake_case_     ,			**snake_case_				)
     A__	=    text.replace(" "     ,			""				).replace("\u2582"     ,			" "				).replace("\u2583"     ,			"\n"				)
     return text











"""simple docstring"""



SCREAMING_SNAKE_CASE    =	"\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"

SCREAMING_SNAKE_CASE    =	[{"type": "code", "content": INSTALL_CONTENT}]
SCREAMING_SNAKE_CASE    =	{
    "{processor_class}": "FakeProcessorClass",
    "{model_class}": "FakeModelClass",
    "{object_class}": "FakeObjectClass",
}





