


import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests




def    a   (							A__							)	-> List[str]:




      '''simple docstring'''

      SCREAMING_SNAKE_CASE__       :  List[Any]						     =		{}

      SCREAMING_SNAKE_CASE__       :  int						     =		job['''started_at''']
      SCREAMING_SNAKE_CASE__       :  Union[str, Any]						     =		job['''completed_at''']

      SCREAMING_SNAKE_CASE__       :  Dict						     =		date_parser.parse(A__							)
      SCREAMING_SNAKE_CASE__       :  Tuple						     =		date_parser.parse(A__							)

      SCREAMING_SNAKE_CASE__       :  Tuple						     =		round((end_datetime - start_datetime).total_seconds() / 6_0.0							)

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

      return job_info




def    a   (							A__      ,    A__=None							)	-> Dict:




      '''simple docstring'''

      SCREAMING_SNAKE_CASE__       :  Union[str, Any]						     =		None
      if token is not None:
            SCREAMING_SNAKE_CASE__       :  int						     =		{'''Accept''': '''application/vnd.github+json''', '''Authorization''': f"""Bearer {token}"""}

      SCREAMING_SNAKE_CASE__       :  Dict						     =		f"""https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"""
      SCREAMING_SNAKE_CASE__       :  List[Any]						     =		requests.get(A__      ,    headers=A__							).json()
      SCREAMING_SNAKE_CASE__       :  Optional[int]						     =		{}

      try:
            job_time.update({job['''name''']: extract_time_from_single_job(A__							) for job in result['''jobs''']}							)
            SCREAMING_SNAKE_CASE__       :  Optional[Any]						     =		math.ceil((result['''total_count'''] - 1_0_0) / 1_0_0							)

            for i in range(A__							):
                  SCREAMING_SNAKE_CASE__       :  int						     =		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__":
    a_ :Any  							=			argparse.ArgumentParser()
    # Required parameters
    parser.add_argument('--workflow_run_id', type=str, required=True, help='A GitHub Actions workflow run id.')
    a_ :Any  							=			parser.parse_args()

    a_ :str  							=			get_job_time(args.workflow_run_id)
    a_ :Optional[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']}''')













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCamelCase			:	List[Any]					    =	{
    """configuration_chinese_clip""": [
        """CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ChineseCLIPConfig""",
        """ChineseCLIPOnnxConfig""",
        """ChineseCLIPTextConfig""",
        """ChineseCLIPVisionConfig""",
    ],
    """processing_chinese_clip""": ["""ChineseCLIPProcessor"""],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase			:	Tuple					    =	["""ChineseCLIPFeatureExtractor"""]
    __lowerCamelCase			:	List[str]					    =	["""ChineseCLIPImageProcessor"""]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase			:	str					    =	[
        """CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """ChineseCLIPModel""",
        """ChineseCLIPPreTrainedModel""",
        """ChineseCLIPTextModel""",
        """ChineseCLIPVisionModel""",
    ]

if TYPE_CHECKING:
    from .configuration_chinese_clip import (
        CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
        ChineseCLIPConfig,
        ChineseCLIPOnnxConfig,
        ChineseCLIPTextConfig,
        ChineseCLIPVisionConfig,
    )
    from .processing_chinese_clip import ChineseCLIPProcessor

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_chinese_clip import (
            CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
            ChineseCLIPModel,
            ChineseCLIPPreTrainedModel,
            ChineseCLIPTextModel,
            ChineseCLIPVisionModel,
        )

else:
    import sys

    __lowerCamelCase			:	Any					    =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
