






'''simple docstring'''





import argparse
import json
import subprocess






def    lowerCamelCase_     (    lowercase__				,     lowercase__):
 lowerCamelCase__  =     []

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

 lowerCamelCase__  =     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:
  lowerCamelCase__  =     "\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__):
  return values.split(",")

 __A							:							Dict  							=		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							:							Optional[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,
    is_vision_available,
)


__A							:							Union[str, Any]  							=		{
    """configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LayoutLMv2Config"""],
    """processing_layoutlmv2""": ["""LayoutLMv2Processor"""],
    """tokenization_layoutlmv2""": ["""LayoutLMv2Tokenizer"""],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __A							:							Optional[Any]  							=		["""LayoutLMv2TokenizerFast"""]

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __A							:							List[Any]  							=		["""LayoutLMv2FeatureExtractor"""]
 __A							:							List[Any]  							=		["""LayoutLMv2ImageProcessor"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __A							:							Any  							=		[
     """LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """LayoutLMv2ForQuestionAnswering""",
     """LayoutLMv2ForSequenceClassification""",
     """LayoutLMv2ForTokenClassification""",
     """LayoutLMv2Layer""",
     """LayoutLMv2Model""",
     """LayoutLMv2PreTrainedModel""",
 ]

if TYPE_CHECKING:
 from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
 from .processing_layoutlmva import LayoutLMvaProcessor
 from .tokenization_layoutlmva import LayoutLMvaTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_layoutlmva import (
      LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
      LayoutLMvaForQuestionAnswering,
      LayoutLMvaForSequenceClassification,
      LayoutLMvaForTokenClassification,
      LayoutLMvaLayer,
      LayoutLMvaModel,
      LayoutLMvaPreTrainedModel,
  )
else:
 import sys

 __A							:							Tuple  							=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

