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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
     from .tokenization_camembert import CamembertTokenizer
else:
     __snake_case						=			None


__snake_case						=			logging.get_logger(__name__)

__snake_case						=			{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

__snake_case						=			{
    '''vocab_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/tokenizer.json''',
    },
}

__snake_case						=			{
    '''camembert-base''': 5_12,
}

__snake_case						=			'''▁'''







class 	__snake_case      (   lowerCamelCase__      ):
 __lowerCamelCase			:      Tuple           =					VOCAB_FILES_NAMES
 __lowerCamelCase			:      Optional[int]           =					PRETRAINED_VOCAB_FILES_MAP
 __lowerCamelCase			:      Optional[int]           =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCamelCase			:      Optional[Any]           =					["""input_ids""", """attention_mask"""]
 __lowerCamelCase			:      str           =					CamembertTokenizer
 def __init__(     self						,      snake_case__=None						,      snake_case__=None						,      snake_case__="<s>"						,      snake_case__="</s>"						,      snake_case__="</s>"						,      snake_case__="<s>"						,      snake_case__="<unk>"						,      snake_case__="<pad>"						,      snake_case__="<mask>"						,      snake_case__=["<s>NOTUSED", "</s>NOTUSED"]						,      **snake_case__						,      )		->							Any:
       '''simple docstring'''





       UpperCAmelCase			:       Optional[Any]			     =AddedToken(snake_case__						,      lstrip=snake_case__						,      rstrip=snake_case__  ) if isinstance(snake_case__						,      snake_case__  ) else mask_token

       super().__init__(
           snake_case__						,      tokenizer_file=snake_case__						,      bos_token=snake_case__						,      eos_token=snake_case__						,      sep_token=snake_case__						,      cls_token=snake_case__						,      unk_token=snake_case__						,      pad_token=snake_case__						,      mask_token=snake_case__						,      additional_special_tokens=snake_case__						,      **snake_case__						,      )

       UpperCAmelCase			:       Dict			     =vocab_file
       UpperCAmelCase			:       Optional[Any]			     =False if not self.vocab_file else True
 def 		UpperCAmelCase__				(     self						,      snake_case__						,      snake_case__ = None  )		->							List[int]:
       '''simple docstring'''





       if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       UpperCAmelCase			:       Optional[Any]			     =[self.cls_token_id]
       UpperCAmelCase			:       int			     =[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep
 def 		UpperCAmelCase__				(     self						,      snake_case__						,      snake_case__ = None  )		->							List[int]:
       '''simple docstring'''





       UpperCAmelCase			:       List[str]			     =[self.sep_token_id]
       UpperCAmelCase			:       Union[str, Any]			     =[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 		UpperCAmelCase__				(     self						,      snake_case__						,      snake_case__ = None  )		->							Tuple[str]:
       '''simple docstring'''





       if not self.can_save_slow_tokenizer:
             raise ValueError(
                 '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
                 '''tokenizer.'''  )

       if not os.path.isdir(snake_case__  ):
             logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''  )
             return
       UpperCAmelCase			:       Union[str, Any]			     =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__  ):
             copyfile(self.vocab_file						,      snake_case__  )

       return (out_vocab_file,)



import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests
def      a      (			A__	:   Dict     )    ->      str:





      """simple docstring"""



      _lowercase	       ={}

      _lowercase	       =job['started_at']
      _lowercase	       =job['completed_at']

      _lowercase	       =date_parser.parse(A__     )
      _lowercase	       =date_parser.parse(A__     )

      _lowercase	       =round((end_datetime - start_datetime).total_seconds() / 60.0     )

      _lowercase	       =start
      _lowercase	       =end
      _lowercase	       =duration_in_min

      return job_info
def      a      (			A__	:   Dict      ,   A__	:   str=None     )    ->      Tuple:





      """simple docstring"""



      _lowercase	       =None
      if token is not None:
            _lowercase	       ={'Accept': 'application/vnd.github+json', 'Authorization': F'''Bearer {token}'''}

      _lowercase	       =F'''https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100'''
      _lowercase	       =requests.get(A__      ,   headers=A__     ).json()
      _lowercase	       ={}

      try:
            job_time.update({job['name']: extract_time_from_single_job(A__     ) for job in result['jobs']}     )
            _lowercase	       =math.ceil((result['total_count'] - 100) / 100     )

            for i in range(A__     ):
                  _lowercase	       =requests.get(url + F'''&page={i + 2}'''      ,   headers=A__     ).json()
                  job_time.update({job['name']: extract_time_from_single_job(A__     ) for job in result['jobs']}     )

            return job_time
      except Exception:
            print(F'''Unknown error, could not fetch links:\n{traceback.format_exc()}'''     )

      return {}


if __name__ == "__main__":
  lowercase_									=   argparse.ArgumentParser()
  # Required parameters
  parser.add_argument('--workflow_run_id', type=str, required=True, help='A GitHub Actions workflow run id.')
  lowercase_									=   parser.parse_args()

  lowercase_									=   get_job_time(args.workflow_run_id)
  lowercase_									=   dict(sorted(job_time.items(), key=lambda item: item[1]["duration"], reverse=True))

  for k, v in job_time.items():
    print(f"{k}: {v['duration']}")


