





import warnings

from ...utils import logging
from .image_processing_flava import FlavaImageProcessor


UpperCAmelCase_ 							=       logging.get_logger(__name__)
class      UpperCamelCase_						(					_lowerCamelCase   ):




					def __init__(						self			,  *lowerCAmelCase_			,  **lowerCAmelCase_					)						->							None:
										warnings.warn(
										    'The class FlavaFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
										    ' use FlavaImageProcessor instead.'			,  lowerCAmelCase_			,  )
										super().__init__(*lowerCAmelCase_			,  **lowerCAmelCase_					)










from collections.abc import Sequence





def   lowerCamelCase__       (       UpperCamelCase__     :    Sequence[float]    ,      UpperCamelCase__     :    bool = False  )     ->	float:



					'''simple docstring'''




					if not arr:
										return 0

					_snake_case													=			0 if allow_empty_subarrays else float('-inf'  )
					_snake_case													=			0.0
					for num in arr:
										_snake_case													=			max(0 if allow_empty_subarrays else num    ,      curr_sum + num  )
										_snake_case													=			max(UpperCamelCase__    ,      UpperCamelCase__  )

					return max_sum


if __name__ == "__main__":
					from doctest import testmod

					testmod()

					UpperCAmelCase_ 							=       [-2, 1, -3, 4, -1, 2, 1, -5, 4]
					print(F"{max_subarray_sum(nums) = }")



