





import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


snake_case__					:							List[str]													=     logging.get_logger(__name__)

snake_case__					:							int													=     '▁'

snake_case__					:							str													=     {'vocab_file': 'sentencepiece.bpe.model'}

snake_case__					:							Tuple													=     {
    'vocab_file': {
        'facebook/mbart-large-en-ro': (
            'https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'
        ),
        'facebook/mbart-large-cc25': (
            'https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'
        ),
    }
}

snake_case__					:							str													=     {
    'facebook/mbart-large-en-ro': 1024,
    'facebook/mbart-large-cc25': 1024,
}

# fmt: off
snake_case__					:							Any													=     ['ar_AR', 'cs_CZ', 'de_DE', 'en_XX', 'es_XX', 'et_EE', 'fi_FI', 'fr_XX', 'gu_IN', 'hi_IN', 'it_IT', 'ja_XX', 'kk_KZ', 'ko_KR', 'lt_LT', 'lv_LV', 'my_MM', 'ne_NP', 'nl_XX', 'ro_RO', 'ru_RU', 'si_LK', 'tr_TR', 'vi_VN', 'zh_CN']





class A_					(			_lowerCamelCase   ):
   lowerCAmelCase__        = VOCAB_FILES_NAMES
   lowerCAmelCase__        = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCAmelCase__        = PRETRAINED_VOCAB_FILES_MAP
   lowerCAmelCase__        = ["""input_ids""", """attention_mask"""]

   lowerCAmelCase__        = []
   lowerCAmelCase__        = []




   def __init__(self	:Union[str, Any]    ,   _UpperCamelCase	:Optional[int]    ,   _UpperCamelCase	:Any="<s>"    ,   _UpperCamelCase	:int="</s>"    ,   _UpperCamelCase	:Any="</s>"    ,   _UpperCamelCase	:str="<s>"    ,   _UpperCamelCase	:str="<unk>"    ,   _UpperCamelCase	:Optional[int]="<pad>"    ,   _UpperCamelCase	:Optional[Any]="<mask>"    ,   _UpperCamelCase	:str=None    ,   _UpperCamelCase	:List[str]=None    ,   _UpperCamelCase	:Any=None    ,   _UpperCamelCase	:Optional[Dict[str, Any]] = None    ,   _UpperCamelCase	:Tuple=None    ,   **_UpperCamelCase	:int    ,   )->					str:
         # Mask token behave like a normal word, i.e. include the space before it
         __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__(
             bos_token=_UpperCamelCase    ,   eos_token=_UpperCamelCase    ,   unk_token=_UpperCamelCase    ,   sep_token=_UpperCamelCase    ,   cls_token=_UpperCamelCase    ,   pad_token=_UpperCamelCase    ,   mask_token=_UpperCamelCase    ,   tokenizer_file=_UpperCamelCase    ,   src_lang=_UpperCamelCase    ,   tgt_lang=_UpperCamelCase    ,   additional_special_tokens=_UpperCamelCase    ,   sp_model_kwargs=self.sp_model_kwargs    ,   **_UpperCamelCase    ,   )

         __A          =				spm.SentencePieceProcessor(**self.sp_model_kwargs )
         self.sp_model.Load(str(_UpperCamelCase ) )
         __A          =				vocab_file

         # Original fairseq vocab and spm vocab must be "aligned":
         # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
         # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
         # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
         # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

         # Mimic fairseq token-to-id alignment for the first 4 token
         __A          =				{'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

         # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
         __A          =				1

         __A          =				len(self.sp_model )
         __A          =				{
             code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(_UpperCamelCase )
         }
         __A          =				{v: k for k, v in self.lang_code_to_id.items()}
         __A          =				len(self.sp_model ) + len(self.lang_code_to_id ) + self.fairseq_offset

         self.fairseq_tokens_to_ids.update(self.lang_code_to_id )
         __A          =				{v: k for k, v in self.fairseq_tokens_to_ids.items()}
         __A          =				list(self.lang_code_to_id.keys() )

         if additional_special_tokens is not None:
               # Only add those special tokens if they are not already there.
               self._additional_special_tokens.extend(
                   [t for t in additional_special_tokens if t not in self._additional_special_tokens] )

         __A          =				src_lang if src_lang is not None else '''en_XX'''
         __A          =				self.lang_code_to_id[self._src_lang]
         __A          =				tgt_lang
         self.set_src_lang_special_tokens(self._src_lang )




   def __getstate__(self	:Optional[int] )->					Dict:
         __A          =				self.__dict__.copy()
         __A          =				None
         __A          =				self.sp_model.serialized_model_proto()
         return state




   def __setstate__(self	:Dict    ,   _UpperCamelCase	:List[Any] )->					Optional[int]:
         __A          =				d

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

         __A          =				spm.SentencePieceProcessor(**self.sp_model_kwargs )
         self.sp_model.LoadFromSerializedProto(self.sp_model_proto )




   @property
   def _lowerCAmelCase      (self	:Tuple )->					Union[str, Any]:
         return len(self.sp_model ) + len(self.lang_code_to_id ) + self.fairseq_offset + 1  # Plus 1 for the mask token




   @property
   def _lowerCAmelCase      (self	:List[str] )->					str:
         return self._src_lang




   @src_lang.setter
   def _lowerCAmelCase      (self	:Any    ,   _UpperCamelCase	:str )->					None:
         __A          =				new_src_lang
         self.set_src_lang_special_tokens(self._src_lang )




   def _lowerCAmelCase      (self	:Optional[Any]    ,   _UpperCamelCase	:List[int]    ,   _UpperCamelCase	:Optional[List[int]] = None    ,   _UpperCamelCase	:bool = 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 )

         __A          =				[1] * len(self.prefix_tokens )
         __A          =				[1] * len(self.suffix_tokens )
         if token_ids_a is None:
               return prefix_ones + ([0] * len(_UpperCamelCase )) + suffix_ones
         return prefix_ones + ([0] * len(_UpperCamelCase )) + ([0] * len(_UpperCamelCase )) + suffix_ones




   def _lowerCAmelCase      (self	:Tuple    ,   _UpperCamelCase	:List[int]    ,   _UpperCamelCase	:Optional[List[int]] = None )->					List[int]:
         if token_ids_a is None:
               return self.prefix_tokens + token_ids_a + self.suffix_tokens
         # We don't expect to process pairs, but leave the pair logic for API consistency
         return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens




   def _lowerCAmelCase      (self	:List[Any]    ,   _UpperCamelCase	:List[int]    ,   _UpperCamelCase	:Optional[List[int]] = None )->					List[int]:
         __A          =				[self.sep_token_id]
         __A          =				[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]




   def _lowerCAmelCase      (self	:List[Any]    ,   _UpperCamelCase	:Tuple    ,   _UpperCamelCase	:str    ,   _UpperCamelCase	:Optional[str]    ,   _UpperCamelCase	:Optional[str]    ,   **_UpperCamelCase	:int )->					Optional[int]:
         if src_lang is None or tgt_lang is None:
               raise ValueError('''Translation requires a `src_lang` and a `tgt_lang` for this model''' )
         __A          =				src_lang
         __A          =				self(_UpperCamelCase    ,   add_special_tokens=_UpperCamelCase    ,   return_tensors=_UpperCamelCase    ,   **_UpperCamelCase )
         __A          =				self.convert_tokens_to_ids(_UpperCamelCase )
         __A          =				tgt_lang_id
         return inputs




   def _lowerCAmelCase      (self	:str )->					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 _lowerCAmelCase      (self	:int    ,   _UpperCamelCase	:str )->					List[str]:
         return self.sp_model.encode(_UpperCamelCase    ,   out_type=_UpperCamelCase )




   def _lowerCAmelCase      (self	:Dict    ,   _UpperCamelCase	:Optional[Any] )->					Dict:
         if token in self.fairseq_tokens_to_ids:
               return self.fairseq_tokens_to_ids[token]
         __A          =				self.sp_model.PieceToId(_UpperCamelCase )

         # Need to return unknown token if the SP model returned 0
         return spm_id + self.fairseq_offset if spm_id else self.unk_token_id




   def _lowerCAmelCase      (self	:List[str]    ,   _UpperCamelCase	:List[str] )->					str:
         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 _lowerCAmelCase      (self	:Optional[Any]    ,   _UpperCamelCase	:List[str] )->					Dict:
         __A          =				''''''.join(_UpperCamelCase ).replace(_UpperCamelCase    ,   ''' ''' ).strip()
         return out_string




   def _lowerCAmelCase      (self	:Optional[Any]    ,   _UpperCamelCase	:str    ,   _UpperCamelCase	:Optional[str] = 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 _lowerCAmelCase      (self	:Dict    ,   _UpperCamelCase	:List[str]    ,   _UpperCamelCase	:str = "en_XX"    ,   _UpperCamelCase	:Optional[List[str]] = None    ,   _UpperCamelCase	:str = "ro_RO"    ,   **_UpperCamelCase	:str    ,   )->					BatchEncoding:
         __A          =				src_lang
         __A          =				tgt_lang
         return super().prepare_seqaseq_batch(_UpperCamelCase    ,   _UpperCamelCase    ,   **_UpperCamelCase )




   def _lowerCAmelCase      (self	:Any )->					Optional[Any]:
         return self.set_src_lang_special_tokens(self.src_lang )




   def _lowerCAmelCase      (self	:Union[str, Any] )->					int:
         return self.set_tgt_lang_special_tokens(self.tgt_lang )




   def _lowerCAmelCase      (self	:List[str]    ,   _UpperCamelCase	:Any )->					None:
         __A          =				self.lang_code_to_id[src_lang]
         __A          =				[]
         __A          =				[self.eos_token_id, self.cur_lang_code]






   def _lowerCAmelCase      (self	:Any    ,   _UpperCamelCase	:str )->					None:
         __A          =				self.lang_code_to_id[lang]
         __A          =				[]
         __A          =				[self.eos_token_id, self.cur_lang_code]












import os
from datetime import datetime as dt

from github import Github


snake_case__					:							Union[str, Any]													=     [
    'good first issue',
    'feature request',
    'wip',
]



def _a				(	)	->						List[Any]:







      '''simple docstring'''






      __A          =				Github(os.environ['''GITHUB_TOKEN'''] )
      __A          =				g.get_repo('''huggingface/accelerate''' )
      __A          =				repo.get_issues(state='''open''' )

      for issue in open_issues:
            __A          =				sorted([comment for comment in issue.get_comments()]					,				key=lambda lowerCamelCase : i.created_at					,				reverse=lowerCamelCase )
            __A          =				comments[0] if len(lowerCamelCase ) > 0 else None
            __A          =				dt.utcnow()
            __A          =				(current_time - issue.updated_at).days
            __A          =				(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()





