

import argparse
import json
import subprocess


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		str ,   _SCREAMING_SNAKE_CASE					:		Optional[int]       ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						[]

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

    SCREAMING_SNAKE_CASE_									=						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:
        SCREAMING_SNAKE_CASE_									=						'\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       ):





           """simple docstring"""


           return values.split(','       )

       UpperCamelCase__  :      Optional[Any]			=    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."
       )
       UpperCamelCase__  :      Optional[int]			=    parser.parse_args()





       get_runner_status(args.target_runners, args.token)





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


UpperCamelCase__  :      List[Any]			=    logging.get_logger(__name__)

UpperCamelCase__  :      List[str]			=    {
    "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/config.json",
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}



class       __snake_case  (    lowerCAmelCase__       ):
  __lowerCAmelCase     :	Any						 =  'biogpt'

  def __init__(					self						,		_A=42384						,		_A=1024						,		_A=24						,		_A=16						,		_A=4096						,		_A="gelu"						,		_A=0.1						,		_A=0.1						,		_A=1024						,		_A=0.0_2						,		_A=1E-12						,		_A=True						,		_A=True						,		_A=0.0						,		_A=0.0						,		_A=1						,		_A=0						,		_A=2						,		**_A						,		):
      SCREAMING_SNAKE_CASE_									=						vocab_size
      SCREAMING_SNAKE_CASE_									=						max_position_embeddings
      SCREAMING_SNAKE_CASE_									=						hidden_size
      SCREAMING_SNAKE_CASE_									=						num_hidden_layers
      SCREAMING_SNAKE_CASE_									=						num_attention_heads
      SCREAMING_SNAKE_CASE_									=						intermediate_size
      SCREAMING_SNAKE_CASE_									=						hidden_act
      SCREAMING_SNAKE_CASE_									=						hidden_dropout_prob
      SCREAMING_SNAKE_CASE_									=						attention_probs_dropout_prob
      SCREAMING_SNAKE_CASE_									=						initializer_range
      SCREAMING_SNAKE_CASE_									=						layer_norm_eps
      SCREAMING_SNAKE_CASE_									=						scale_embedding
      SCREAMING_SNAKE_CASE_									=						use_cache
      SCREAMING_SNAKE_CASE_									=						layerdrop
      SCREAMING_SNAKE_CASE_									=						activation_dropout
      super().__init__(pad_token_id=_A						,		bos_token_id=_A						,		eos_token_id=_A						,		**_A)


