



'''simple docstring'''






import os
from datetime import datetime as dt

from github import Github


UpperCamelCase__:   Union[str, Any]								=			[
    "good first issue",
    "feature request",
    "wip",
]


def  snake_case_     (					)      ->   int:
							UpperCAmelCase :       Dict 							=		Github(os.environ['''GITHUB_TOKEN''']  )
							UpperCAmelCase :       Any 							=		g.get_repo('''huggingface/accelerate'''  )
							UpperCAmelCase :       str 							=		repo.get_issues(state='''open'''  )

							for issue in open_issues:
														UpperCAmelCase :       Optional[int] 							=		sorted([comment for comment in issue.get_comments()]   ,      key=lambda _lowerCAmelCase  : i.created_at   ,      reverse=_lowerCAmelCase  )
														UpperCAmelCase :       Optional[Any] 							=		comments[0] if len(_lowerCAmelCase  ) > 0 else None
														UpperCAmelCase :       Optional[int] 							=		dt.utcnow()
														UpperCAmelCase :       Union[str, Any] 							=		(current_time - issue.updated_at).days
														UpperCAmelCase :       Optional[Any] 							=		(current_time - issue.created_at).days
														if (
														    last_comment is not None
														    and last_comment.user.login == "github-actions[bot]"
														    and days_since_updated > 7
														    and days_since_creation >= 30
														    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()  )
														):
																					# Close issue since it has been 7 days of inactivity since bot mention.
																					issue.edit(state='''closed'''  )
														elif (
														    days_since_updated > 23
														    and days_since_creation >= 30
														    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()  )
														):
																					# Add stale comment
																					issue.create_comment(
																					    '''This issue has been automatically marked as stale because it has not had '''
																					    '''recent activity. If you think this still needs to be addressed '''
																					    '''please comment on this thread.\n\nPlease note that issues that do not follow the '''
																					    '''[contributing guidelines](https://github.com/huggingface/accelerate/blob/main/CONTRIBUTING.md) '''
																					    '''are likely to be ignored.'''  )


if __name__ == "__main__":
						main()











import os
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 logging


_UpperCAmelCase		:  Any	=   logging.get_logger(__name__)

_UpperCAmelCase		:  List[Any]	=   {"vocab_file": "sentencepiece.bpe.model"}

_UpperCAmelCase		:  List[str]	=   {
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    }
}

_UpperCAmelCase		:  Any	=   {
    "camembert-base": 512,
}

_UpperCAmelCase		:  List[Any]	=   "▁"




class       __lowerCAmelCase				(							lowerCAmelCase):
       _a           =  VOCAB_FILES_NAMES
       _a           =  PRETRAINED_VOCAB_FILES_MAP
       _a           =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       _a           =  ['''input_ids''', '''attention_mask''']






       def __init__(      self:    List[str]				,    _lowerCAmelCase:    Optional[int]				,    _lowerCAmelCase:    Dict="<s>"				,    _lowerCAmelCase:    Union[str, Any]="</s>"				,    _lowerCAmelCase:    Optional[int]="</s>"				,    _lowerCAmelCase:    List[Any]="<s>"				,    _lowerCAmelCase:    Tuple="<unk>"				,    _lowerCAmelCase:    Union[str, Any]="<pad>"				,    _lowerCAmelCase:    str="<mask>"				,    _lowerCAmelCase:    int=["<s>NOTUSED", "</s>NOTUSED"]				,    _lowerCAmelCase:    Optional[Dict[str, Any]] = None				,    **_lowerCAmelCase:    Any				,    ):
         # Mask token behave like a normal word, i.e. include the space before it
         lowercase			:Dict							=  AddedToken(_lowerCAmelCase				,    lstrip=_lowerCAmelCase				,    rstrip=_lowerCAmelCase ) if isinstance(_lowerCAmelCase				,    _lowerCAmelCase ) else mask_token

         lowercase			:Optional[int]							=  {} if sp_model_kwargs is None else sp_model_kwargs

         super().__init__(
             bos_token=_lowerCAmelCase				,    eos_token=_lowerCAmelCase				,    unk_token=_lowerCAmelCase				,    sep_token=_lowerCAmelCase				,    cls_token=_lowerCAmelCase				,    pad_token=_lowerCAmelCase				,    mask_token=_lowerCAmelCase				,    additional_special_tokens=_lowerCAmelCase				,    sp_model_kwargs=self.sp_model_kwargs				,    **_lowerCAmelCase				,    )
         lowercase			:Dict							=  spm.SentencePieceProcessor(**self.sp_model_kwargs )
         self.sp_model.Load(str(_lowerCAmelCase ) )
         lowercase			:Tuple							=  vocab_file
         # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
         # sentencepiece vocabulary (this is the case for <s> and </s>
         lowercase			:int							=  {"<s>NOTUSED": 0, "<pad>": 1, "</s>NOTUSED": 2, "<unk>": 3}
         lowercase			:Tuple							=  len(self.fairseq_tokens_to_ids )
         lowercase			:int							=  len(self.sp_model ) + len(self.fairseq_tokens_to_ids )
         lowercase			:Any							=  {v: k for k, v in self.fairseq_tokens_to_ids.items()}






       def     SCREAMING_SNAKE_CASE			(      self:    Tuple				,    _lowerCAmelCase:    List[int]				,    _lowerCAmelCase:    Optional[List[int]] = None ):

         if token_ids_a is None:
           return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         lowercase			:List[Any]							=  [self.cls_token_id]
         lowercase			:List[str]							=  [self.sep_token_id]
         return cls + token_ids_a + sep + sep + token_ids_a + sep






       def     SCREAMING_SNAKE_CASE			(      self:    Dict				,    _lowerCAmelCase:    List[int]				,    _lowerCAmelCase:    Optional[List[int]] = None				,    _lowerCAmelCase:    bool = False ):
         if already_has_special_tokens:
           return super().get_special_tokens_mask(
               token_ids_a=_lowerCAmelCase				,    token_ids_a=_lowerCAmelCase				,    already_has_special_tokens=_lowerCAmelCase )

         if token_ids_a is None:
           return [1] + ([0] * len(_lowerCAmelCase )) + [1]
         return [1] + ([0] * len(_lowerCAmelCase )) + [1, 1] + ([0] * len(_lowerCAmelCase )) + [1]






       def     SCREAMING_SNAKE_CASE			(      self:    Union[str, Any]				,    _lowerCAmelCase:    List[int]				,    _lowerCAmelCase:    Optional[List[int]] = None ):
         lowercase			:Any							=  [self.sep_token_id]
         lowercase			:str							=  [self.cls_token_id]

         if token_ids_a is None:
           return len(cls + token_ids_a + sep ) * [0]
         return len(cls + token_ids_a + sep + sep + token_ids_a + sep ) * [0]






       @property
       def     SCREAMING_SNAKE_CASE			(      self:    Union[str, Any] ):
         return len(self.fairseq_tokens_to_ids ) + len(self.sp_model )






       def     SCREAMING_SNAKE_CASE			(      self:    Tuple ):
         lowercase			:Any							=  {self.convert_ids_to_tokens(_lowerCAmelCase ): i for i in range(self.vocab_size )}
         vocab.update(self.added_tokens_encoder )
         return vocab






       def     SCREAMING_SNAKE_CASE			(      self:    int				,    _lowerCAmelCase:    str ):
         return self.sp_model.encode(_lowerCAmelCase				,    out_type=_lowerCAmelCase )






       def     SCREAMING_SNAKE_CASE			(      self:    Dict				,    _lowerCAmelCase:    List[str] ):
         if token in self.fairseq_tokens_to_ids:
           return self.fairseq_tokens_to_ids[token]
         elif self.sp_model.PieceToId(_lowerCAmelCase ) == 0:
           # Convert sentence piece unk token to fairseq unk token index
           return self.unk_token_id
         return self.fairseq_offset + self.sp_model.PieceToId(_lowerCAmelCase )






       def     SCREAMING_SNAKE_CASE			(      self:    str				,    _lowerCAmelCase:    Tuple ):
         if index in self.fairseq_ids_to_tokens:
           return self.fairseq_ids_to_tokens[index]
         return self.sp_model.IdToPiece(index - self.fairseq_offset )






       def     SCREAMING_SNAKE_CASE			(      self:    List[Any]				,    _lowerCAmelCase:    List[str] ):
         lowercase			:Tuple							=  []
         lowercase			:Any							=  ""
         lowercase			:str							=  False
         for token in tokens:
           # make sure that special tokens are not decoded using sentencepiece model
           if token in self.all_special_tokens:
             if not prev_is_special:
               out_string += " "
             out_string += self.sp_model.decode(_lowerCAmelCase ) + token
             lowercase			:Optional[int]							=  True
             lowercase			:Any							=  []
           else:
             current_sub_tokens.append(_lowerCAmelCase )
             lowercase			:str							=  False
         out_string += self.sp_model.decode(_lowerCAmelCase )
         return out_string.strip()






       def __getstate__(      self:    Dict ):
         lowercase			:int							=  self.__dict__.copy()
         lowercase			:List[str]							=  None
         return state






       def __setstate__(      self:    Optional[Any]				,    _lowerCAmelCase:    Dict ):
         lowercase			:int							=  d

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

         lowercase			:List[str]							=  spm.SentencePieceProcessor(**self.sp_model_kwargs )
         self.sp_model.Load(self.vocab_file )






       def     SCREAMING_SNAKE_CASE			(      self:    Optional[int]				,    _lowerCAmelCase:    str				,    _lowerCAmelCase:    Optional[str] = None ):
         if not os.path.isdir(_lowerCAmelCase ):
           logger.error(F"Vocabulary path ({save_directory}) should be a directory" )
           return
         lowercase			:Any							=  os.path.join(
             _lowerCAmelCase				,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )

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

         return (out_vocab_file,)



