


import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests

def 	lowerCAmelCase__			(      a__:		List[str]	)  ->		Tuple:


							'''simple docstring'''





							_UpperCAmelCase					=      {}

							_UpperCAmelCase					=      job['started_at']
							_UpperCAmelCase					=      job['completed_at']

							_UpperCAmelCase					=      date_parser.parse(a__	)
							_UpperCAmelCase					=      date_parser.parse(a__	)

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

							_UpperCAmelCase					=      start
							_UpperCAmelCase					=      end
							_UpperCAmelCase					=      duration_in_min

							return job_info

def 	lowerCAmelCase__			(      a__:		List[str]      ,  a__:		Optional[Any]=None	)  ->		List[str]:


							'''simple docstring'''





							_UpperCAmelCase					=      None
							if token is not None:
														_UpperCAmelCase					=      {'Accept': 'application/vnd.github+json', 'Authorization': F'''Bearer {token}'''}

							_UpperCAmelCase					=      F'''https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100'''
							_UpperCAmelCase					=      requests.get(a__      ,  headers=a__	).json()
							_UpperCAmelCase					=      {}

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

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

		lowerCAmelCase__  :List[str]             =							get_job_time(args.workflow_run_id)
		lowerCAmelCase__  :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_flax_available,
    is_torch_available,
    is_vision_available,
)


lowerCAmelCase__  :Tuple             =							{'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BeitConfig''', '''BeitOnnxConfig''']}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :List[Any]             =							['''BeitFeatureExtractor''']
		lowerCAmelCase__  :Optional[Any]             =							['''BeitImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :int             =							[
		    '''BEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''BeitForImageClassification''',
		    '''BeitForMaskedImageModeling''',
		    '''BeitForSemanticSegmentation''',
		    '''BeitModel''',
		    '''BeitPreTrainedModel''',
		]


try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :Tuple             =							[
		    '''FlaxBeitForImageClassification''',
		    '''FlaxBeitForMaskedImageModeling''',
		    '''FlaxBeitModel''',
		    '''FlaxBeitPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_beit import BeitFeatureExtractor
				from .image_processing_beit import BeitImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_beit import (
				    BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BeitForImageClassification,
				    BeitForMaskedImageModeling,
				    BeitForSemanticSegmentation,
				    BeitModel,
				    BeitPreTrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_beit import (
				    FlaxBeitForImageClassification,
				    FlaxBeitForMaskedImageModeling,
				    FlaxBeitModel,
				    FlaxBeitPreTrainedModel,
				)


else:
		import sys

		lowerCAmelCase__  :Dict             =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
