





'''simple docstring'''
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


a__							:							Any =logging.get_logger(__name__)

a__							:							List[str] ='''▁'''

a__							:							Optional[Any] ={'''vocab_file''': '''sentencepiece.bpe.model'''}

a__							:							Any ={
    '''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'''
        ),
    }
}

a__							:							Optional[int] ={
    '''facebook/mbart-large-en-ro''': 1_024,
    '''facebook/mbart-large-cc25''': 1_024,
}

# fmt: off
a__							:							Optional[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      snake_case     (    __lowerCamelCase       ):




 """simple docstring"""



 SCREAMING_SNAKE_CASE_	:					Tuple					=VOCAB_FILES_NAMES
 SCREAMING_SNAKE_CASE_	:					List[str]					=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 SCREAMING_SNAKE_CASE_	:					Dict					=PRETRAINED_VOCAB_FILES_MAP
 SCREAMING_SNAKE_CASE_	:					List[str]					=["input_ids", "attention_mask"]

 SCREAMING_SNAKE_CASE_	:					List[int]					=[]
 SCREAMING_SNAKE_CASE_	:					List[int]					=[]






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

        __UpperCamelCase       =  {} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=__A							,	eos_token=__A							,	unk_token=__A							,	sep_token=__A							,	cls_token=__A							,	pad_token=__A							,	mask_token=__A							,	tokenizer_file=__A							,	src_lang=__A							,	tgt_lang=__A							,	additional_special_tokens=__A							,	sp_model_kwargs=self.sp_model_kwargs							,	**__A							,	)

        __UpperCamelCase       =  spm.SentencePieceProcessor(**self.sp_model_kwargs	)
        self.sp_model.Load(str(__A	)	)
        __UpperCamelCase       =  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
        __UpperCamelCase       =  {'<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
        __UpperCamelCase       =  1

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

        self.fairseq_tokens_to_ids.update(self.lang_code_to_id	)
        __UpperCamelCase       =  {v: k for k, v in self.fairseq_tokens_to_ids.items()}
        __UpperCamelCase       =  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]	)

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






 def __getstate__(       self       :							List[Any]	):
        __UpperCamelCase       =  self.__dict__.copy()
        __UpperCamelCase       =  None
        __UpperCamelCase       =  self.sp_model.serialized_model_proto()
        return state






 def __setstate__(       self       :							Optional[Any]							,	__A       :							int	):
        __UpperCamelCase       =  d

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

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






 @property
 def        _lowerCamelCase					(       self       :							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]	):
        return self._src_lang






 @src_lang.setter
 def        _lowerCamelCase					(       self       :							Optional[int]							,	__A       :							str	):
        __UpperCamelCase       =  new_src_lang
        self.set_src_lang_special_tokens(self._src_lang	)






 def        _lowerCamelCase					(       self       :							Optional[Any]							,	__A       :							List[int]							,	__A       :							Optional[List[int]] = None							,	__A       :							bool = False	):

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

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






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






 def        _lowerCamelCase					(       self       :							str	):
        __UpperCamelCase       =  {self.convert_ids_to_tokens(__A	): i for i in range(self.vocab_size	)}
        vocab.update(self.added_tokens_encoder	)
        return vocab






 def        _lowerCamelCase					(       self       :							List[Any]							,	__A       :							str	):
        return self.sp_model.encode(__A							,	out_type=__A	)






 def        _lowerCamelCase					(       self       :							Optional[int]							,	__A       :							List[str]	):
        if token in self.fairseq_tokens_to_ids:
               return self.fairseq_tokens_to_ids[token]
        __UpperCamelCase       =  self.sp_model.PieceToId(__A	)

        # 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       :							Dict							,	__A       :							List[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]							,	__A       :							Optional[Any]	):
        __UpperCamelCase       =  ''.join(__A	).replace(__A							,	' '	).strip()
        return out_string






 def        _lowerCamelCase					(       self       :							Tuple							,	__A       :							str							,	__A       :							Optional[str] = None	):
        if not os.path.isdir(__A	):
               logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''	)
               return
        __UpperCamelCase       =  os.path.join(
            __A							,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)

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

        return (out_vocab_file,)






 def        _lowerCamelCase					(       self       :							Tuple							,	__A       :							List[str]							,	__A       :							str = "en_XX"							,	__A       :							Optional[List[str]] = None							,	__A       :							str = "ro_RO"							,	**__A       :							int							,	):
        __UpperCamelCase       =  src_lang
        __UpperCamelCase       =  tgt_lang
        return super().prepare_seqaseq_batch(__A							,	__A							,	**__A	)






 def        _lowerCamelCase					(       self       :							Optional[Any]	):
        return self.set_src_lang_special_tokens(self.src_lang	)






 def        _lowerCamelCase					(       self       :							Optional[Any]	):
        return self.set_tgt_lang_special_tokens(self.tgt_lang	)






 def        _lowerCamelCase					(       self       :							Dict							,	__A       :							List[Any]	):
        __UpperCamelCase       =  self.lang_code_to_id[src_lang]
        __UpperCamelCase       =  []
        __UpperCamelCase       =  [self.eos_token_id, self.cur_lang_code]






 def        _lowerCamelCase					(       self       :							Tuple							,	__A       :							str	):
        __UpperCamelCase       =  self.lang_code_to_id[lang]
        __UpperCamelCase       =  []
        __UpperCamelCase       =  [self.eos_token_id, self.cur_lang_code]








"""simple docstring"""





import argparse
import json
import subprocess







def      lowerCamelCase__       (							_lowerCamelCase       :		Tuple		,				_lowerCamelCase       :		str )      ->				List[Any]:
  lowerCamelCase_         =						[]

  lowerCamelCase_         =						(
      F'''curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {token}"'''
      ' https://api.github.com/repos/huggingface/transformers/actions/runners'
  )
  lowerCamelCase_         =						subprocess.run(_lowerCamelCase		,				shell=_lowerCamelCase		,				stdout=subprocess.PIPE )
  lowerCamelCase_         =						output.stdout.decode('utf-8' )
  lowerCamelCase_         =						json.loads(_lowerCamelCase )

  lowerCamelCase_         =						status['runners']
  for runner in runners:
    if runner["name"] in target_runners:
      if runner["status"] == "offline":
        offline_runners.append(_lowerCamelCase )

    # save the result so we can report them on Slack
  with open('offline_runners.txt'		,				'w' ) as fp:
    fp.write(json.dumps(_lowerCamelCase ) )

  if len(_lowerCamelCase ) > 0:
    lowerCamelCase_         =						'\n'.join([x['name'] for x in offline_runners] )
    raise ValueError(F'''The following runners are offline:\n{failed}''' )


if __name__ == "__main__":







  def      lowerCamelCase__       (							_lowerCamelCase       :		Dict )      ->				Tuple:
    return values.split(',' )

  _SCREAMING_SNAKE_CASE					:				Union[str, Any]					    =						argparse.ArgumentParser()
  # Required parameters
  parser.add_argument(
      '''--target_runners''',
      default=None,
      type=list_str,
      required=True,
      help='''Comma-separated list of runners to check status.''',
  )

  parser.add_argument(
      '''--token''', default=None, type=str, required=True, help='''A token that has actions:read permission.'''
  )
  _SCREAMING_SNAKE_CASE					:				Any					    =						parser.parse_args()






  get_runner_status(args.target_runners, args.token)




