
import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__		):
      UpperCamelCase__    :   Union[str, Any]					=				{}

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

      UpperCamelCase__    :   List[str]					=				date_parser.parse(_UpperCAmelCase		)
      UpperCamelCase__    :   List[Any]					=				date_parser.parse(_UpperCAmelCase		)

      UpperCamelCase__    :   Optional[int]					=				round((end_datetime - start_datetime).total_seconds() / 60.0		)

      UpperCamelCase__    :   Dict					=				start
      UpperCamelCase__    :   Any					=				end
      UpperCamelCase__    :   Optional[Any]					=				duration_in_min

      return job_info


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__=None		):
      UpperCamelCase__    :   int					=				None
      if token is not None:
            UpperCamelCase__    :   Any					=				{'''Accept''': '''application/vnd.github+json''', '''Authorization''': f'''Bearer {token}'''}

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

      try:
            job_time.update({job['''name''']: extract_time_from_single_job(_UpperCAmelCase		) for job in result['''jobs''']}		)
            UpperCamelCase__    :   int					=				math.ceil((result['''total_count'''] - 1_0_0) / 1_0_0		)

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

    lowerCamelCase      =get_job_time(args.workflow_run_id)
    lowerCamelCase      =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


lowerCamelCase      ={
    "configuration_clipseg": [
        "CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "CLIPSegConfig",
        "CLIPSegTextConfig",
        "CLIPSegVisionConfig",
    ],
    "processing_clipseg": ["CLIPSegProcessor"],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST",
        "CLIPSegModel",
        "CLIPSegPreTrainedModel",
        "CLIPSegTextModel",
        "CLIPSegVisionModel",
        "CLIPSegForImageSegmentation",
    ]

if TYPE_CHECKING:
    from .configuration_clipseg import (
        CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
        CLIPSegConfig,
        CLIPSegTextConfig,
        CLIPSegVisionConfig,
    )
    from .processing_clipseg import CLIPSegProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_clipseg import (
            CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
            CLIPSegForImageSegmentation,
            CLIPSegModel,
            CLIPSegPreTrainedModel,
            CLIPSegTextModel,
            CLIPSegVisionModel,
        )

else:
    import sys

    lowerCamelCase      =_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


