





'''simple docstring'''




from __future__ import annotations







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase       ,    _lowerCAmelCase    )->     int | float:
 if len(_lowerCAmelCase    ) == 0:
  raise ValueError('find_max() arg is an empty sequence'    )
 if (
     left >= len(_lowerCAmelCase    )
     or left < -len(_lowerCAmelCase    )
     or right >= len(_lowerCAmelCase    )
     or right < -len(_lowerCAmelCase    )
 ):
  raise IndexError('list index out of range'    )
 if left == right:
  return nums[left]
 __UpperCAmelCase					=   (left + right) >> 1  # the middle
 __UpperCAmelCase					=   find_max(_lowerCAmelCase       ,    _lowerCAmelCase       ,    _lowerCAmelCase    )  # find max in range[left, mid]
 __UpperCAmelCase					=   find_max(_lowerCAmelCase       ,    mid + 1       ,    _lowerCAmelCase    )  # find max in range[mid + 1, right]

 return left_max if left_max >= right_max else right_max


if __name__ == "__main__":
    import doctest

    doctest.testmod(verbose=True)












'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A:					List[str]							=				{
    """configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
    """tokenization_luke""": ["""LukeTokenizer"""],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _A:					Union[str, Any]							=				[
        """LUKE_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """LukeForEntityClassification""",
        """LukeForEntityPairClassification""",
        """LukeForEntitySpanClassification""",
        """LukeForMultipleChoice""",
        """LukeForQuestionAnswering""",
        """LukeForSequenceClassification""",
        """LukeForTokenClassification""",
        """LukeForMaskedLM""",
        """LukeModel""",
        """LukePreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
    from .tokenization_luke import LukeTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_luke import (
            LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
            LukeForEntityClassification,
            LukeForEntityPairClassification,
            LukeForEntitySpanClassification,
            LukeForMaskedLM,
            LukeForMultipleChoice,
            LukeForQuestionAnswering,
            LukeForSequenceClassification,
            LukeForTokenClassification,
            LukeModel,
            LukePreTrainedModel,
        )

else:
    import sys

    _A:					str							=				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





