

import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests







def       A_				(   _UpperCAmelCase   ):
						SCREAMING_SNAKE_CASE_:			Dict  		=	{}

						SCREAMING_SNAKE_CASE_:			List[str]  		=	job["started_at"]
						SCREAMING_SNAKE_CASE_:			Optional[int]  		=	job["completed_at"]

						SCREAMING_SNAKE_CASE_:			str  		=	date_parser.parse(_UpperCAmelCase   )
						SCREAMING_SNAKE_CASE_:			Optional[int]  		=	date_parser.parse(_UpperCAmelCase   )

						SCREAMING_SNAKE_CASE_:			Dict  		=	round((end_datetime - start_datetime).total_seconds() / 6_0.0   )

						SCREAMING_SNAKE_CASE_:			Optional[int]  		=	start
						SCREAMING_SNAKE_CASE_:			int  		=	end
						SCREAMING_SNAKE_CASE_:			str  		=	duration_in_min

						return job_info







def       A_				(   _UpperCAmelCase    ,     _UpperCAmelCase=None   ):
						SCREAMING_SNAKE_CASE_:			List[str]  		=	None
						if token is not None:
												SCREAMING_SNAKE_CASE_:			str  		=	{"Accept": "application/vnd.github+json", "Authorization": f"Bearer {token}"}

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

						try:
												job_time.update({job["name"]: extract_time_from_single_job(_UpperCAmelCase   ) for job in result["jobs"]}   )
												SCREAMING_SNAKE_CASE_:			List[Any]  		=	math.ceil((result["total_count"] - 1_00) / 1_00   )

												for i in range(_UpperCAmelCase   ):
																		SCREAMING_SNAKE_CASE_:			Tuple  		=	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							:  Optional[int]            =						argparse.ArgumentParser()
						# Required parameters
						parser.add_argument("""--workflow_run_id""", type=str, required=True, help="""A GitHub Actions workflow run id.""")
						lowerCAmelCase							:  Union[str, Any]            =						parser.parse_args()

						lowerCAmelCase							:  Any            =						get_job_time(args.workflow_run_id)
						lowerCAmelCase							:  Any            =						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							:  Optional[int]            =						{"""configuration_yolos""": ["""YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """YolosConfig""", """YolosOnnxConfig"""]}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  Any            =						["""YolosFeatureExtractor"""]
						lowerCAmelCase							:  Tuple            =						["""YolosImageProcessor"""]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  Any            =						[
						    """YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """YolosForObjectDetection""",
						    """YolosModel""",
						    """YolosPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_yolos import YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP, YolosConfig, YolosOnnxConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_yolos import YolosFeatureExtractor
												from .image_processing_yolos import YolosImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_yolos import (
												    YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST,
												    YolosForObjectDetection,
												    YolosModel,
												    YolosPreTrainedModel,
												)


else:
						import sys

						lowerCAmelCase							:  int            =						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






