




import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


UpperCAmelCase_		:					Tuple          =  logging.get_logger(__name__)




class 		__A   (      UpperCamelCase__      ):

						def __init__(		self :int     ,			*__snake_case :int     ,			**__snake_case :Optional[Any]			):
										'''simple docstring'''

										warnings.warn(
										    """The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
										    """ Please use SegformerImageProcessor instead."""     ,			__snake_case     ,			)
										super().__init__(*__snake_case     ,			**__snake_case			)










from collections.abc import Sequence




def 		lowerCAmelCase_ (						lowerCamelCase = None ):
				if nums is None or not nums:
								raise ValueError("""Input sequence should not be empty""" )

				__magic_name__						:						str										=nums[0]
				for i in range(1						,  len(lowerCamelCase ) ):
								__magic_name__						:						Any										=nums[i]
								__magic_name__						:						Dict										=max(lowerCamelCase						,  ans + num						,  lowerCamelCase )

				return ans


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							# Try on a sample input from the user
							UpperCAmelCase_		:					List[str]          =  int(input("Enter number of elements : ").strip())
							UpperCAmelCase_		:					Tuple          =  list(map(int, input("\nEnter the numbers : ").strip().split()))[:n]
							print(max_subsequence_sum(array))




