



'''simple docstring'''




import argparse
import json
import subprocess



def    __lowerCamelCase						(      _lowercase			,       _lowercase	)   ->    Tuple:
							UpperCAmelCase  :	int							  =	[]

							UpperCAmelCase  :	Optional[Any]							  =	(
							    F'''curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {token}"'''
							    """ https://api.github.com/repos/huggingface/transformers/actions/runners"""
							)
							UpperCAmelCase  :	Optional[Any]							  =	subprocess.run(_lowercase			,       shell=_lowercase			,       stdout=subprocess.PIPE	)
							UpperCAmelCase  :	Dict							  =	output.stdout.decode("""utf-8"""	)
							UpperCAmelCase  :	Dict							  =	json.loads(_lowercase	)

							UpperCAmelCase  :	Any							  =	status["""runners"""]
							for runner in runners:
														if runner["name"] in target_runners:
																					if runner["status"] == "offline":
																												offline_runners.append(_lowercase	)

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

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


if __name__ == "__main__":



							def    __lowerCamelCase						(      _lowercase	)   ->    Any:
														return values.split(""","""	)

							a     :    str      						=					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."""
							)
							a     :    Union[str, Any]      						=					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


a     :    Any      						=					{
    """configuration_nezha""": ["""NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """NezhaConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a     :    Any      						=					[
							    """NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """NezhaForNextSentencePrediction""",
							    """NezhaForMaskedLM""",
							    """NezhaForPreTraining""",
							    """NezhaForMultipleChoice""",
							    """NezhaForQuestionAnswering""",
							    """NezhaForSequenceClassification""",
							    """NezhaForTokenClassification""",
							    """NezhaModel""",
							    """NezhaPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_nezha import NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP, NezhaConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_nezha import (
														    NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST,
														    NezhaForMaskedLM,
														    NezhaForMultipleChoice,
														    NezhaForNextSentencePrediction,
														    NezhaForPreTraining,
														    NezhaForQuestionAnswering,
														    NezhaForSequenceClassification,
														    NezhaForTokenClassification,
														    NezhaModel,
														    NezhaPreTrainedModel,
														)


else:
							import sys

							a     :    Union[str, Any]      						=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

