


'''simple docstring'''






from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__UpperCAmelCase       =							logging.get_logger(__name__)

__UpperCAmelCase       =							{
    '''facebook/levit-128S''': '''https://huggingface.co/facebook/levit-128S/resolve/main/config.json''',
    # See all LeViT models at https://huggingface.co/models?filter=levit
}




class 		a__    (							a__  ):





							'''simple docstring'''






							lowercase__      :       int     						=				"levit"







							def __init__(		self ,   lowerCamelCase_=2_24 ,   lowerCamelCase_=3 ,   lowerCamelCase_=3 ,   lowerCamelCase_=2 ,   lowerCamelCase_=1 ,   lowerCamelCase_=16 ,   lowerCamelCase_=[1_28, 2_56, 3_84] ,   lowerCamelCase_=[4, 8, 12] ,   lowerCamelCase_=[4, 4, 4] ,   lowerCamelCase_=[16, 16, 16] ,   lowerCamelCase_=0 ,   lowerCamelCase_=[2, 2, 2] ,   lowerCamelCase_=[2, 2, 2] ,   lowerCamelCase_=0.02 ,   **lowerCamelCase_ ,   )	->							Union[str, Any]:
														super().__init__(**lowerCamelCase_       )
														lowerCAmelCase__	       =     image_size
														lowerCAmelCase__	       =     num_channels
														lowerCAmelCase__	       =     kernel_size
														lowerCAmelCase__	       =     stride
														lowerCAmelCase__	       =     padding
														lowerCAmelCase__	       =     hidden_sizes
														lowerCAmelCase__	       =     num_attention_heads
														lowerCAmelCase__	       =     depths
														lowerCAmelCase__	       =     key_dim
														lowerCAmelCase__	       =     drop_path_rate
														lowerCAmelCase__	       =     patch_size
														lowerCAmelCase__	       =     attention_ratio
														lowerCAmelCase__	       =     mlp_ratio
														lowerCAmelCase__	       =     initializer_range
														lowerCAmelCase__	       =     [
														    ['''Subsample''', key_dim[0], hidden_sizes[0] // key_dim[0], 4, 2, 2],
														    ['''Subsample''', key_dim[0], hidden_sizes[1] // key_dim[0], 4, 2, 2],
														]




class 		a__    (							a__  ):





							'''simple docstring'''






							lowercase__      :       Optional[Any]     						=				version.parse("1.11"  )







							@property
							def   __SCREAMING_SNAKE_CASE							(		self       )	->							Mapping[str, Mapping[int, str]]:
														return OrderedDict(
														    [
														        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
														    ]       )







							@property
							def   __SCREAMING_SNAKE_CASE							(		self       )	->							float:
														return 1e-4



'''simple docstring'''






from __future__ import annotations


def  _snake_case       (					A			,   A	)						->   float:
							lowerCAmelCase__	       =     sorted(numsa + numsa	)
							lowerCAmelCase__       , lowerCAmelCase__	       =     divmod(len(A	)			,   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       =							[float(x) for x in input('''Enter the elements of first array: ''').split()]
		__UpperCAmelCase       =							[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)}""")