




import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests


def 						lowerCamelCase__    (		_A							):







	'''simple docstring'''





	snake_case_		    =     {}

	snake_case_		    =     job["started_at"]
	snake_case_		    =     job["completed_at"]

	snake_case_		    =     date_parser.parse(__lowerCAmelCase							)
	snake_case_		    =     date_parser.parse(__lowerCAmelCase							)

	snake_case_		    =     round((end_datetime - start_datetime).total_seconds() / 60.0							)

	snake_case_		    =     start
	snake_case_		    =     end
	snake_case_		    =     duration_in_min

	return job_info


def 						lowerCamelCase__    (		_A     ,	_A=None							):







	'''simple docstring'''





	snake_case_		    =     None
	if token is not None:
		snake_case_		    =     {"Accept": "application/vnd.github+json", "Authorization": f"Bearer {token}"}

	snake_case_		    =     f"https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"
	snake_case_		    =     requests.get(__lowerCAmelCase     ,	headers=__lowerCAmelCase							).json()
	snake_case_		    =     {}

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

		for i in range(__lowerCAmelCase							):
			snake_case_		    =     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__":
		lowercase__				:     int 		=						argparse.ArgumentParser()
		# Required parameters
		parser.add_argument("--workflow_run_id", type=str, required=True, help="A GitHub Actions workflow run id.")
		lowercase__				:     List[Any] 		=						parser.parse_args()

		lowercase__				:     List[str] 		=						get_job_time(args.workflow_run_id)
		lowercase__				:     List[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']}''')


import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey

class    lowerCAmelCase__     :






		def __init__(		self		:							Any							,			SCREAMING_SNAKE_CASE__		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							int							,			SCREAMING_SNAKE_CASE__		:							int  )     ->							Dict:
						if dst_width < 0 or dst_height < 0:
										raise ValueError('''Destination width/height should be > 0'''  )

						__lowerCamelCase    					=	img
						__lowerCamelCase    					=	img.shape[1]
						__lowerCamelCase    					=	img.shape[0]
						__lowerCamelCase    					=	dst_width
						__lowerCamelCase    					=	dst_height

						__lowerCamelCase    					=	self.src_w / self.dst_w
						__lowerCamelCase    					=	self.src_h / self.dst_h

						__lowerCamelCase    					=	__lowerCamelCase    					=	(
						    np.ones((self.dst_h, self.dst_w, 3)							,			np.uinta  ) * 2_55
						)






		def  __A       (		self		:							List[Any]  )     ->							str:
						for i in range(self.dst_h  ):
										for j in range(self.dst_w  ):
														__lowerCamelCase    					=	self.img[self.get_y(SCREAMING_SNAKE_CASE__  )][self.get_x(SCREAMING_SNAKE_CASE__  )]






		def  __A       (		self		:							str							,			SCREAMING_SNAKE_CASE__		:							int  )     ->							int:
						return int(self.ratio_x * x  )







		def  __A       (		self		:							str							,			SCREAMING_SNAKE_CASE__		:							int  )     ->							int:
						return int(self.ratio_y * y  )


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE__							,    SCREAMING_SNAKE_CASE__   :			List[str]												=    800, 600
					SCREAMING_SNAKE_CASE__   :			int												=    imread("image_data/lena.jpg", 1)
					SCREAMING_SNAKE_CASE__   :			Union[str, Any]												=    NearestNeighbour(im, dst_w, dst_h)
					n.process()

					imshow(
					    F'Image resized from: {im.shape[1]}x{im.shape[0]} to {dst_w}x{dst_h}', n.output
					)
					waitKey(0)
					destroyAllWindows()



