"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCAmelCase__  		=						{
    """configuration_roc_bert""": ["""ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RoCBertConfig"""],
    """tokenization_roc_bert""": ["""RoCBertTokenizer"""],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    pass

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCAmelCase__  		=						[
        """ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """RoCBertForCausalLM""",
        """RoCBertForMaskedLM""",
        """RoCBertForMultipleChoice""",
        """RoCBertForPreTraining""",
        """RoCBertForQuestionAnswering""",
        """RoCBertForSequenceClassification""",
        """RoCBertForTokenClassification""",
        """RoCBertLayer""",
        """RoCBertModel""",
        """RoCBertPreTrainedModel""",
        """load_tf_weights_in_roc_bert""",
    ]

if TYPE_CHECKING:
    from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
    from .tokenization_roc_bert import RoCBertTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        raise OptionalDependencyNotAvailable()

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_roc_bert import (
            ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            RoCBertForCausalLM,
            RoCBertForMaskedLM,
            RoCBertForMultipleChoice,
            RoCBertForPreTraining,
            RoCBertForQuestionAnswering,
            RoCBertForSequenceClassification,
            RoCBertForTokenClassification,
            RoCBertLayer,
            RoCBertModel,
            RoCBertPreTrainedModel,
            load_tf_weights_in_roc_bert,
        )


else:
    import sys

    UpperCAmelCase__  		=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

"""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()
