



"""simple docstring"""


from typing import TYPE_CHECKING

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


__A      :							List[Any]   =      {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__A      :							Optional[int]   =      ["GLPNFeatureExtractor"]
					__A      :							str   =      ["GLPNImageProcessor"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__A      :							Optional[Any]   =      [
					    "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "GLPNForDepthEstimation",
					    "GLPNLayer",
					    "GLPNModel",
					    "GLPNPreTrainedModel",
					]


if TYPE_CHECKING:
					from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_glpn import GLPNFeatureExtractor
										from .image_processing_glpn import GLPNImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_glpn import (
										    GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GLPNForDepthEstimation,
										    GLPNLayer,
										    GLPNModel,
										    GLPNPreTrainedModel,
										)


else:
					import sys

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









from __future__ import annotations





def 		__A		(	__lowerCamelCase							,			__lowerCamelCase    )      ->       float:
	a										=							sorted(numsa + numsa    )
	a				, a										=							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					:       Tuple    					=      [float(x) for x in input("Enter the elements of first array: ").split()]
		__UpperCamelCase					:       List[Any]    					=      [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)}')

