





from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging


if TYPE_CHECKING:
      from ...onnx.config import PatchingSpec
      from ...tokenization_utils_base import PreTrainedTokenizerBase


lowercase_					     =	logging.get_logger(__name__)

lowercase_					     =	{
    """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/config.json""",
    """allenai/longformer-large-4096""": """https://huggingface.co/allenai/longformer-large-4096/resolve/main/config.json""",
    """allenai/longformer-large-4096-finetuned-triviaqa""": (
        """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/config.json"""
    ),
    """allenai/longformer-base-4096-extra.pos.embd.only""": (
        """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/config.json"""
    ),
    """allenai/longformer-large-4096-extra.pos.embd.only""": (
        """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/config.json"""
    ),
}
class        SCREAMING_SNAKE_CASE     (UpperCAmelCase   ):
   _UpperCamelCase					:	List[Any]				      = 'longformer'


   def __init__(					self    :       Optional[int]    ,  a    :       Union[List[int], int] = 512    ,  a    :       int = 2    ,  a    :       int = 1    ,  a    :       int = 0    ,  a    :       int = 2    ,  a    :       int = 30_522    ,  a    :       int = 768    ,  a    :       int = 12    ,  a    :       int = 12    ,  a    :       int = 3_072    ,  a    :       str = "gelu"    ,  a    :       float = 0.1    ,  a    :       float = 0.1    ,  a    :       int = 512    ,  a    :       int = 2    ,  a    :       float = 0.02    ,  a    :       float = 1E-1_2    ,  a    :       bool = False    ,  **a    :       Optional[int]    ,  )->     Dict:





     """simple docstring"""







     super().__init__(pad_token_id=a    ,  **a )

     lowercase__			    =						attention_window
     lowercase__			    =						sep_token_id
     lowercase__			    =						bos_token_id
     lowercase__			    =						eos_token_id
     lowercase__			    =						vocab_size
     lowercase__			    =						hidden_size
     lowercase__			    =						num_hidden_layers
     lowercase__			    =						num_attention_heads
     lowercase__			    =						hidden_act
     lowercase__			    =						intermediate_size
     lowercase__			    =						hidden_dropout_prob
     lowercase__			    =						attention_probs_dropout_prob
     lowercase__			    =						max_position_embeddings
     lowercase__			    =						type_vocab_size
     lowercase__			    =						initializer_range
     lowercase__			    =						layer_norm_eps
     lowercase__			    =						onnx_export






class        SCREAMING_SNAKE_CASE     (UpperCAmelCase   ):


   def __init__(					self    :       Tuple    ,  a    :       "PretrainedConfig"    ,  a    :       str = "default"    ,  a    :       "List[PatchingSpec]" = None )->     List[str]:





     """simple docstring"""







     super().__init__(a    ,  a    ,  a )
     lowercase__			    =						True


   @property
   def  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     Mapping[str, Mapping[int, str]]:





     """simple docstring"""







     if self.task == "multiple-choice":
       lowercase__			    =						{0: 'batch', 1: 'choice', 2: 'sequence'}
     else:
       lowercase__			    =						{0: 'batch', 1: 'sequence'}
     return OrderedDict(
         [
             ('input_ids', dynamic_axis),
             ('attention_mask', dynamic_axis),
             ('global_attention_mask', dynamic_axis),
         ] )


   @property
   def  SCREAMING_SNAKE_CASE_							(					self    :       str )->     Mapping[str, Mapping[int, str]]:





     """simple docstring"""







     lowercase__			    =						super().outputs
     if self.task == "default":
       lowercase__			    =						{0: 'batch'}
     return outputs


   @property
   def  SCREAMING_SNAKE_CASE_							(					self    :       Tuple )->     float:





     """simple docstring"""







     return 1E-4


   @property
   def  SCREAMING_SNAKE_CASE_							(					self    :       Union[str, Any] )->     int:





     """simple docstring"""







     return max(super().default_onnx_opset    ,  14 )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Any    ,  a    :       "PreTrainedTokenizerBase"    ,  a    :       int = -1    ,  a    :       int = -1    ,  a    :       bool = False    ,  a    :       Optional[TensorType] = None    ,  )->     Mapping[str, Any]:





     """simple docstring"""







     lowercase__			    =						super().generate_dummy_inputs(
         preprocessor=a    ,  batch_size=a    ,  seq_length=a    ,  is_pair=a    ,  framework=a )
     import torch

     # for some reason, replacing this code by inputs["global_attention_mask"] = torch.randint(2, inputs["input_ids"].shape, dtype=torch.int64)
     # makes the export fail randomly
     lowercase__			    =						torch.zeros_like(inputs['input_ids'] )
     # make every second token global
     lowercase__			    =						1

     return inputs









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)


