






from __future__ import annotations





def 					snake_case	(  lowerCamelCase					,	lowerCamelCase       ):




	'''simple docstring'''







	__lowercase   							=	sorted(numsa + numsa       )
	__lowercase							,    __lowercase   							=	divmod(len(lowerCamelCase       )					,	2       )
	if mod == 1:
		return all_numbers[div]
	else:
		return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						__UpperCamelCase   :   Optional[int]      =    [float(x) for x in input("""Enter the elements of first array: """).split()]
						__UpperCamelCase   :   Optional[int]      =    [float(x) for x in input("""Enter the elements of second array: """).split()]
						print(F'''The median of two arrays is: {median_of_two_arrays(array_a, array_a)}''')



'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase     :							Tuple       						=     {
    'configuration_luke': ['LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LukeConfig'],
    'tokenization_luke': ['LukeTokenizer'],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase     :							int       						=     [
          '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

      lowercase     :							Dict       						=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




