



'''simple docstring'''






import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests




def     snake_case_					(     lowerCAmelCase_		)->		Optional[int]:





       '''simple docstring'''


       _UpperCAmelCase  :						int			     = {}

       _UpperCAmelCase  :						Optional[Any]			     = job["""started_at"""]
       _UpperCAmelCase  :						str			     = job["""completed_at"""]

       _UpperCAmelCase  :						List[Any]			     = date_parser.parse(lowerCAmelCase_		)
       _UpperCAmelCase  :						Optional[Any]			     = date_parser.parse(lowerCAmelCase_		)

       _UpperCAmelCase  :						Union[str, Any]			     = round((end_datetime - start_datetime).total_seconds() / 6_0.0		)

       _UpperCAmelCase  :						List[Any]			     = start
       _UpperCAmelCase  :						Any			     = end
       _UpperCAmelCase  :						Union[str, Any]			     = duration_in_min

       return job_info




def     snake_case_					(     lowerCAmelCase_       ,   lowerCAmelCase_=None		)->		Any:





       '''simple docstring'''


       _UpperCAmelCase  :						Optional[Any]			     = None
       if token is not None:
              _UpperCAmelCase  :						List[str]			     = {"""Accept""": """application/vnd.github+json""", """Authorization""": F'''Bearer {token}'''}

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

       try:
              job_time.update({job["""name"""]: extract_time_from_single_job(lowerCAmelCase_		) for job in result["""jobs"""]}		)
              _UpperCAmelCase  :						str			     = math.ceil((result["""total_count"""] - 100) / 100		)

              for i in range(lowerCAmelCase_		):
                     _UpperCAmelCase  :						Dict			     = requests.get(url + F'''&page={i + 2}'''       ,   headers=lowerCAmelCase_		).json()
                     job_time.update({job["""name"""]: extract_time_from_single_job(lowerCAmelCase_		) 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__":
   A_							: int						 =	argparse.ArgumentParser()
   # Required parameters
   parser.add_argument("""--workflow_run_id""", type=str, required=True, help="""A GitHub Actions workflow run id.""")
   A_							: Optional[int]						 =	parser.parse_args()

   A_							: Any						 =	get_job_time(args.workflow_run_id)
   A_							: int						 =	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"]}""")








'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A_							: Optional[int]						 =	{"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A_							: str						 =	[
       """IBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """IBertForMaskedLM""",
       """IBertForMultipleChoice""",
       """IBertForQuestionAnswering""",
       """IBertForSequenceClassification""",
       """IBertForTokenClassification""",
       """IBertModel""",
       """IBertPreTrainedModel""",
   ]

if TYPE_CHECKING:
   from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_ibert import (
          IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          IBertForMaskedLM,
          IBertForMultipleChoice,
          IBertForQuestionAnswering,
          IBertForSequenceClassification,
          IBertForTokenClassification,
          IBertModel,
          IBertPreTrainedModel,
      )

else:
   import sys

   A_							: str						 =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



