





'''simple docstring'''






from __future__ import annotations

from random import choice







def     UpperCamelCase_      (   A__ :       Dict ):
  '''simple docstring'''





  return choice(A__ )







def     UpperCamelCase_      (   A__ :       list[int]							,   A__ :       int ):
  '''simple docstring'''





  lowerCAmelCase_      :				List[Any]      =       random_pivot(A__ )

  # partition based on pivot
  # linear time
  lowerCAmelCase_      :				Union[str, Any]      =       [e for e in lst if e < pivot]
  lowerCAmelCase_      :				Union[str, Any]      =       [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(A__ ) == k - 1:
    return pivot
  # pivot is in elements bigger than k
  elif len(A__ ) < k - 1:
    return kth_number(A__							,   k - len(A__ ) - 1 )
  # pivot is in elements smaller than k
  else:
    return kth_number(A__							,   A__ )


if __name__ == "__main__":
  import doctest

  doctest.testmod()







'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A :  List[str]    							=				{
    "configuration_bigbird_pegasus": [
        "BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BigBirdPegasusConfig",
        "BigBirdPegasusOnnxConfig",
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A :  Union[str, Any]    							=				[
      "BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST",
      "BigBirdPegasusForCausalLM",
      "BigBirdPegasusForConditionalGeneration",
      "BigBirdPegasusForQuestionAnswering",
      "BigBirdPegasusForSequenceClassification",
      "BigBirdPegasusModel",
      "BigBirdPegasusPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_bigbird_pegasus import (
      BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
      BigBirdPegasusConfig,
      BigBirdPegasusOnnxConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_bigbird_pegasus import (
        BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
        BigBirdPegasusForCausalLM,
        BigBirdPegasusForConditionalGeneration,
        BigBirdPegasusForQuestionAnswering,
        BigBirdPegasusForSequenceClassification,
        BigBirdPegasusModel,
        BigBirdPegasusPreTrainedModel,
    )


else:
  import sys

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



