"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple

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


if is_sentencepiece_available():
      from .tokenization_pegasus import PegasusTokenizer
else:
      lowercase__ 	=     None


lowercase__ 	=     logging.get_logger(__name__)


lowercase__ 	=     '▁'

lowercase__ 	=     {'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

lowercase__ 	=     {
    'vocab_file': {'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'},
    'tokenizer_file': {
        'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/tokenizer.json'
    },
}

lowercase__ 	=     {
    'google/pegasus-xsum': 512,
}




class        __snake_case	(					__lowerCAmelCase    ):
      a__				=		VOCAB_FILES_NAMES
      a__				=		PRETRAINED_VOCAB_FILES_MAP
      a__				=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a__				=		PegasusTokenizer
      a__				=		["""input_ids""", """attention_mask"""]



      def __init__(						self   ,      lowercase=None   ,      lowercase=None   ,      lowercase="<pad>"   ,      lowercase="</s>"   ,      lowercase="<unk>"   ,      lowercase="<mask_2>"   ,      lowercase="<mask_1>"   ,      lowercase=None   ,      lowercase=1_03   ,      **lowercase   ,      )     ->      List[Any]:





        '''simple docstring'''





        a__:					Optional[Any]      							=     offset

        if additional_special_tokens is not None:
          if not isinstance(lowercase   ,      lowercase):
            raise TypeError(
                f'additional_special_tokens should be of type {type(lowercase)}, but is'
                f' {type(lowercase)}')

          a__:					Union[str, Any]      							=     (
              ([mask_token_sent] + additional_special_tokens)
              if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
              else additional_special_tokens
          )
          # fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
          additional_special_tokens_extended += [
              f'<unk_{i}>' for i in range(len(lowercase)   ,      self.offset - 1)
          ]

          if len(set(lowercase)) != len(lowercase):
            raise ValueError(
                'Please make sure that the provided additional_special_tokens do not contain an incorrectly'
                f' shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.')
          a__:					str      							=     additional_special_tokens_extended
        else:
          a__:					Tuple      							=     [mask_token_sent] if mask_token_sent is not None else []
          additional_special_tokens += [f'<unk_{i}>' for i in range(2   ,      self.offset)]

        super().__init__(
            lowercase   ,      tokenizer_file=lowercase   ,      pad_token=lowercase   ,      eos_token=lowercase   ,      unk_token=lowercase   ,      mask_token=lowercase   ,      mask_token_sent=lowercase   ,      offset=lowercase   ,      additional_special_tokens=lowercase   ,      **lowercase   ,      )
        a__:					Optional[int]      							=     vocab_file
        a__:					Optional[int]      							=     False if not self.vocab_file else True



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      List[Any]:





        '''simple docstring'''





        a__:					Any      							=     set(self.all_special_ids)  # call it once instead of inside list comp
        all_special_ids.remove(self.unk_token_id)  # <unk> is only sometimes special

        if all_special_ids != set(range(len(self.additional_special_tokens) + 3)):
          raise ValueError(
              'There should be 3 special tokens: mask_token, pad_token, and eos_token +'
              f' {len(self.additional_special_tokens)} additional_special_tokens, but got {all_special_ids}')

        return [1 if x in all_special_ids else 0 for x in seq]



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = None   ,      lowercase = False)     ->      List[int]:





        '''simple docstring'''





        if already_has_special_tokens:
          return self._special_token_mask(lowercase)
        elif token_ids_a is None:
          return self._special_token_mask(lowercase) + [1]
        else:
          return self._special_token_mask(token_ids_a + token_ids_a) + [1]



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase=None)     ->      List[int]:





        '''simple docstring'''





        if token_ids_a is None:
          return token_ids_a + [self.eos_token_id]
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return token_ids_a + token_ids_a + [self.eos_token_id]



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = 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(lowercase):
          logger.error(f'Vocabulary path ({save_directory}) should be a directory')
          return
        a__:					int      							=     os.path.join(
            lowercase   ,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

        if os.path.abspath(self.vocab_file) != os.path.abspath(lowercase):
          copyfile(self.vocab_file   ,      lowercase)

        return (out_vocab_file,)



"""simple docstring"""
import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests







def 						__a       (     _SCREAMING_SNAKE_CASE       )     ->Tuple:
  a__:					Tuple      							=     {}

  a__:					Tuple      							=     job['started_at']
  a__:					int      							=     job['completed_at']

  a__:					Any      							=     date_parser.parse(_SCREAMING_SNAKE_CASE       )
  a__:					Tuple      							=     date_parser.parse(_SCREAMING_SNAKE_CASE       )

  a__:					str      							=     round((end_datetime - start_datetime).total_seconds() / 60.0       )

  a__:					Any      							=     start
  a__:					Dict      							=     end
  a__:					Optional[int]      							=     duration_in_min

  return job_info







def 						__a       (     _SCREAMING_SNAKE_CASE		,					_SCREAMING_SNAKE_CASE=None       )     ->Optional[int]:
  a__:					Tuple      							=     None
  if token is not None:
    a__:					List[str]      							=     {'Accept': 'application/vnd.github+json', 'Authorization': F'Bearer {token}'}

  a__:					int      							=     F'https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100'
  a__:					Union[str, Any]      							=     requests.get(_SCREAMING_SNAKE_CASE		,					headers=_SCREAMING_SNAKE_CASE       ).json()
  a__:					str      							=     {}

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

    for i in range(_SCREAMING_SNAKE_CASE       ):
      a__:					str      							=     requests.get(url + F'&page={i + 2}'		,					headers=_SCREAMING_SNAKE_CASE       ).json()
      job_time.update({job['name']: extract_time_from_single_job(_SCREAMING_SNAKE_CASE       ) 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']}")


