





'''simple docstring'''



import argparse
import json
import subprocess




def 				_lowerCAmelCase  (			lowerCamelCase_     :					Optional[int]						,    lowerCamelCase_     :					Optional[Any]			):
			__lowercase			  =							[]

			__lowercase			  =							(
			    f"curl -H \"Accept: application/vnd.github+json\" -H \"Authorization: Bearer {token}\""
			    ''' https://api.github.com/repos/huggingface/transformers/actions/runners'''
			)
			__lowercase			  =							subprocess.run(a__						,    shell=a__						,    stdout=subprocess.PIPE			)
			__lowercase			  =							output.stdout.decode('''utf-8'''			)
			__lowercase			  =							json.loads(a__			)

			__lowercase			  =							status['''runners''']
			for runner in runners:
						if runner["name"] in target_runners:
									if runner["status"] == "offline":
												offline_runners.append(a__			)

    # save the result so we can report them on Slack
			with open('''offline_runners.txt'''						,    '''w'''			) as fp:
						fp.write(json.dumps(a__			)			)

			if len(a__			) > 0:
						__lowercase			  =							'''\n'''.join([x['''name'''] for x in offline_runners]			)
						raise ValueError(f"The following runners are offline:\n{failed}"			)


if __name__ == "__main__":




	def 				_lowerCAmelCase  (			lowerCamelCase_     :					Dict			):
				return values.split(''','''			)

	_SCREAMING_SNAKE_CASE   =      argparse.ArgumentParser()
	# Required parameters
	parser.add_argument(
	    '''--target_runners''',
	    default=None,
	    type=list_str,
	    required=True,
	    help='''Comma-separated list of runners to check status.''',
	)

	parser.add_argument(
	    '''--token''', default=None, type=str, required=True, help='''A token that has actions:read permission.'''
	)
	_SCREAMING_SNAKE_CASE   =      parser.parse_args()

	get_runner_status(args.target_runners, args.token)












'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_SCREAMING_SNAKE_CASE   =      {
    '''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
    '''tokenization_mvp''': ['''MvpTokenizer'''],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE   =      ['''MvpTokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE   =      [
	    '''MVP_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''MvpForCausalLM''',
	    '''MvpForConditionalGeneration''',
	    '''MvpForQuestionAnswering''',
	    '''MvpForSequenceClassification''',
	    '''MvpModel''',
	    '''MvpPreTrainedModel''',
	]

if TYPE_CHECKING:
	from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
	from .tokenization_mvp import MvpTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_mvp_fast import MvpTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_mvp import (
		    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MvpForCausalLM,
		    MvpForConditionalGeneration,
		    MvpForQuestionAnswering,
		    MvpForSequenceClassification,
		    MvpModel,
		    MvpPreTrainedModel,
		)

else:
	import sys

	_SCREAMING_SNAKE_CASE   =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





