



"""simple docstring"""

import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests




def __lowercase    (							_a					):
    snake_case_				:  Optional[Any]       =			{}

    snake_case_				:  Optional[Any]       =			job["""started_at"""]
    snake_case_				:  Tuple       =			job["""completed_at"""]

    snake_case_				:  Tuple       =			date_parser.parse(SCREAMING_SNAKE_CASE__					)
    snake_case_				:  Union[str, Any]       =			date_parser.parse(SCREAMING_SNAKE_CASE__					)

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

    snake_case_				:  int       =			start
    snake_case_				:  str       =			end
    snake_case_				:  Optional[Any]       =			duration_in_min

    return job_info




def __lowercase    (							_a	,    _a=None					):
    snake_case_				:  List[str]       =			None
    if token is not None:
        snake_case_				:  Optional[int]       =			{"""Accept""": """application/vnd.github+json""", """Authorization""": f"Bearer {token}"}

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

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

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

      lowercase__					:						Optional[Any]												=			get_job_time(args.workflow_run_id)
      lowercase__					:						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"""

import math
import sys

import cva
import numpy as np




def __lowercase    (							_a	,    _a					):
    # For applying gaussian function for each element in matrix.
    snake_case_				:  Dict       =			math.sqrt(_a					)
    snake_case_				:  Tuple       =			1 / (sigma * math.sqrt(2 * math.pi					))
    return cons * np.exp(-((img / sigma) ** 2) * 0.5					)




def __lowercase    (							_a	,    _a	,    _a	,    _a					):
    snake_case_				:  Optional[int]       =			kernel_size // 2
    return img[x - half : x + half + 1, y - half : y + half + 1]




def __lowercase    (							_a	,    _a					):
    # Creates a gaussian kernel of given dimension.
    snake_case_				:  Union[str, Any]       =			np.zeros((kernel_size, kernel_size)					)
    for i in range(0	,    _a					):
        for j in range(0	,    _a					):
            snake_case_				:  Union[str, Any]       =			math.sqrt(
                abs(i - kernel_size // 2					) ** 2 + abs(j - kernel_size // 2					) ** 2					)
    return vec_gaussian(_a	,    _a					)




def __lowercase    (							_a	,    _a	,    _a	,    _a	,    ):
    snake_case_				:  int       =			np.zeros(img.shape					)
    snake_case_				:  str       =			get_gauss_kernel(_a	,    _a					)
    snake_case_,			snake_case_				:  Any       =			img.shape
    for i in range(kernel_size // 2	,    size_x - kernel_size // 2					):
        for j in range(kernel_size // 2	,    size_y - kernel_size // 2					):
            snake_case_				:  List[Any]       =			get_slice(_a	,    _a	,    _a	,    _a					)
            snake_case_				:  Union[str, Any]       =			img_s - img_s[kernel_size // 2, kernel_size // 2]
            snake_case_				:  Optional[Any]       =			vec_gaussian(_a	,    _a					)
            snake_case_				:  Dict       =			np.multiply(_a	,    _a					)
            snake_case_				:  Dict       =			np.multiply(_a	,    _a					)
            snake_case_				:  List[Any]       =			np.sum(_a					) / np.sum(_a					)
            snake_case_				:  Dict       =			val
    return imga




def __lowercase    (							_a					):
    snake_case_				:  Optional[int]       =			args[1] if args[1:] else '''../image_data/lena.jpg'''
    snake_case_				:  int       =			float(args[2]					) if args[2:] else 1.0
    snake_case_				:  Dict       =			float(args[3]					) if args[3:] else 1.0
    if args[4:]:
        snake_case_				:  Optional[Any]       =			int(args[4]					)
        snake_case_				:  Union[str, Any]       =			kernel_size + abs(kernel_size % 2 - 1					)
    else:
        snake_case_				:  Union[str, Any]       =			5
    return filename, spatial_variance, intensity_variance, kernel_size


if __name__ == "__main__":
     lowercase__					,lowercase__					,lowercase__					,lowercase__					:						Tuple												=			parse_args(sys.argv)
     lowercase__					:						str												=			cva.imread(filename, 0)
     cva.imshow('''input image''', img)

     lowercase__					:						Tuple												=			img / 2_55
     lowercase__					:						Optional[int]												=			out.astype('''float32''')
     lowercase__					:						Union[str, Any]												=			bilateral_filter(out, spatial_variance, intensity_variance, kernel_size)
     lowercase__					:						List[str]												=			out * 2_55
     lowercase__					:						List[str]												=			np.uinta(out)
     cva.imshow('''output image''', out)
     cva.waitKey(0)
     cva.destroyAllWindows()





