





from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase_					     =	logging.get_logger(__name__)

lowercase_					     =	{
    """facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/config.json""",
    # See all XGLM models at https://huggingface.co/models?filter=xglm
}
class        SCREAMING_SNAKE_CASE     (UpperCAmelCase   ):
   _UpperCamelCase					:	Optional[Any]				      = 'xglm'
   _UpperCamelCase					:	str				      = ['past_key_values']

   _UpperCamelCase					:	Union[str, Any]				      = {
       'num_attention_heads': 'attention_heads',
       'hidden_size': 'd_model',
       'num_hidden_layers': 'num_layers',
   }


   def __init__(					self    :       Any    ,  a    :       List[Any]=256_008    ,  a    :       List[str]=2_048    ,  a    :       List[str]=1_024    ,  a    :       int=4_096    ,  a    :       int=24    ,  a    :       List[str]=16    ,  a    :       Dict="gelu"    ,  a    :       Optional[int]=0.1    ,  a    :       Optional[Any]=0.1    ,  a    :       Optional[Any]=0.0    ,  a    :       int=0.0    ,  a    :       Optional[int]=0.02    ,  a    :       Union[str, Any]=True    ,  a    :       List[Any]=True    ,  a    :       Any=2    ,  a    :       Dict=1    ,  a    :       str=0    ,  a    :       Tuple=2    ,  **a    :       Optional[Any]    ,  )->     List[Any]:





     """simple docstring"""







     lowercase__			    =						vocab_size
     lowercase__			    =						max_position_embeddings
     lowercase__			    =						d_model
     lowercase__			    =						ffn_dim
     lowercase__			    =						num_layers
     lowercase__			    =						attention_heads
     lowercase__			    =						activation_function
     lowercase__			    =						dropout
     lowercase__			    =						attention_dropout
     lowercase__			    =						activation_dropout
     lowercase__			    =						layerdrop
     lowercase__			    =						init_std
     lowercase__			    =						scale_embedding  # scale factor will be sqrt(d_model) if True
     lowercase__			    =						use_cache

     super().__init__(
         pad_token_id=a    ,  bos_token_id=a    ,  eos_token_id=a    ,  decoder_start_token_id=a    ,  **a    ,  )











import argparse
import json
import subprocess




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)       ->     Optional[int]:
  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(_SCREAMING_SNAKE_CASE	,		shell=_SCREAMING_SNAKE_CASE	,		stdout=subprocess.PIPE	)
  lowercase__			    =						output.stdout.decode('utf-8'	)
  lowercase__			    =						json.loads(_SCREAMING_SNAKE_CASE	)

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

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

  if len(_SCREAMING_SNAKE_CASE	) > 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     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	)       ->     str:
        return values.split(','	)

      lowercase_					     =	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."""
      )
      lowercase_					     =	parser.parse_args()


      get_runner_status(args.target_runners, args.token)


