"""simple docstring"""


from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase__  		=						logging.get_logger(__name__)

UpperCAmelCase__  		=						{
    """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/resolve/main/config.json""",
    """xlm-roberta-large""": """https://huggingface.co/xlm-roberta-large/resolve/main/config.json""",
    """xlm-roberta-large-finetuned-conll02-dutch""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json"""
    ),
    """xlm-roberta-large-finetuned-conll02-spanish""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json"""
    ),
    """xlm-roberta-large-finetuned-conll03-english""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json"""
    ),
    """xlm-roberta-large-finetuned-conll03-german""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json"""
    ),
}


class        a				(		lowerCAmelCase_   ):
    _snake_case     :  Any     							=							'xlm-roberta'


    def __init__(					self	:  str   ,				__lowerCAmelCase	:  Optional[Any]=3_0522   ,				__lowerCAmelCase	:  Tuple=768   ,				__lowerCAmelCase	:  Any=12   ,				__lowerCAmelCase	:  Optional[int]=12   ,				__lowerCAmelCase	:  Optional[Any]=3072   ,				__lowerCAmelCase	:  int="gelu"   ,				__lowerCAmelCase	:  Optional[Any]=0.1   ,				__lowerCAmelCase	:  str=0.1   ,				__lowerCAmelCase	:  List[Any]=512   ,				__lowerCAmelCase	:  Tuple=2   ,				__lowerCAmelCase	:  str=0.02   ,				__lowerCAmelCase	:  Tuple=1e-1_2   ,				__lowerCAmelCase	:  Tuple=1   ,				__lowerCAmelCase	:  Any=0   ,				__lowerCAmelCase	:  Optional[Any]=2   ,				__lowerCAmelCase	:  int="absolute"   ,				__lowerCAmelCase	:  Union[str, Any]=True   ,				__lowerCAmelCase	:  Tuple=None   ,				**__lowerCAmelCase	:  int   ,				):
      super().__init__(pad_token_id=__lowerCAmelCase   ,				bos_token_id=__lowerCAmelCase   ,				eos_token_id=__lowerCAmelCase   ,				**__lowerCAmelCase					)

      _UpperCAmelCase						 =      vocab_size
      _UpperCAmelCase						 =      hidden_size
      _UpperCAmelCase						 =      num_hidden_layers
      _UpperCAmelCase						 =      num_attention_heads
      _UpperCAmelCase						 =      hidden_act
      _UpperCAmelCase						 =      intermediate_size
      _UpperCAmelCase						 =      hidden_dropout_prob
      _UpperCAmelCase						 =      attention_probs_dropout_prob
      _UpperCAmelCase						 =      max_position_embeddings
      _UpperCAmelCase						 =      type_vocab_size
      _UpperCAmelCase						 =      initializer_range
      _UpperCAmelCase						 =      layer_norm_eps
      _UpperCAmelCase						 =      position_embedding_type
      _UpperCAmelCase						 =      use_cache
      _UpperCAmelCase						 =      classifier_dropout



class        a				(		lowerCAmelCase_   ):


    @property
    def      lowerCAmelCase_  (					self	:  Union[str, Any]					):
      if self.task == "multiple-choice":
        _UpperCAmelCase						 =      {0: """batch""", 1: """choice""", 2: """sequence"""}
      else:
        _UpperCAmelCase						 =      {0: """batch""", 1: """sequence"""}
      return OrderedDict(
          [
              ("""input_ids""", dynamic_axis),
              ("""attention_mask""", dynamic_axis),
          ]					)

"""simple docstring"""


from __future__ import annotations

from random import choice






def     __UpperCAmelCase					(			lowercase		):







  """simple docstring"""
  return choice(lowercase		)






def     __UpperCAmelCase					(			lowercase   ,lowercase		):







  """simple docstring"""
  _UpperCAmelCase						 =      random_pivot(lowercase		)

  # partition based on pivot
  # linear time
  _UpperCAmelCase						 =      [e for e in lst if e < pivot]
  _UpperCAmelCase						 =      [e for e in lst if e > pivot]

  # if we get lucky, pivot might be the element we want.
  # we can easily see this:
  # small (elements smaller than k)
  # + pivot (kth element)
  # + big (elements larger than k)
  if len(lowercase		) == k - 1:
    return pivot
  # pivot is in elements bigger than k
  elif len(lowercase		) < k - 1:
    return kth_number(lowercase   ,k - len(lowercase		) - 1		)
  # pivot is in elements smaller than k
  else:
    return kth_number(lowercase   ,lowercase		)


if __name__ == "__main__":
    import doctest

    doctest.testmod()
