

import sys

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  int )   ->       Tuple:
				_UpperCAmelCase       :		Union[str, Any] 		=    len(lowerCAmelCase )
				_UpperCAmelCase       :		Union[str, Any] 		=    [[0 for x in range(lowerCAmelCase )] for x in range(lowerCAmelCase )]
				_UpperCAmelCase       :		Any 		=    [[0 for x in range(lowerCAmelCase )] for x in range(lowerCAmelCase )]

				for chain_length in range(2  ,      lowerCAmelCase ):
								for a in range(1  ,      n - chain_length + 1 ):
												_UpperCAmelCase       :		str 		=    a + chain_length - 1

												_UpperCAmelCase       :		int 		=    sys.maxsize
												for c in range(lowerCAmelCase  ,      lowerCAmelCase ):
																_UpperCAmelCase       :		Optional[int] 		=    (
																    matrix[a][c] + matrix[c + 1][b] + array[a - 1] * array[c] * array[b]
																)
																if cost < matrix[a][b]:
																				_UpperCAmelCase       :		Dict 		=    cost
																				_UpperCAmelCase       :		Tuple 		=    c
				return matrix, sol

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  int  ,      lowerCAmelCase:  List[str]  ,      lowerCAmelCase:  Any )   ->       int:
				if i == j:
								print("A" + str(lowerCAmelCase )  ,      end=" " )
				else:
								print("("  ,      end=" " )
								print_optiomal_solution(lowerCAmelCase  ,      lowerCAmelCase  ,      optimal_solution[i][j] )
								print_optiomal_solution(lowerCAmelCase  ,      optimal_solution[i][j] + 1  ,      lowerCAmelCase )
								print(")"  ,      end=" " )

def 							__SCREAMING_SNAKE_CASE							(				)   ->       Any:
				_UpperCAmelCase       :		Tuple 		=    [30, 35, 15, 5, 10, 20, 25]
				_UpperCAmelCase       :		str 		=    len(lowerCAmelCase )
				# Size of matrix created from above array will be
				# 30*35 35*15 15*5 5*10 10*20 20*25
				_UpperCAmelCase		,							_UpperCAmelCase       :		Any 		=    matrix_chain_order(lowerCAmelCase )

				print("No. of Operation required: " + str(matrix[1][n - 1] ) )
				print_optiomal_solution(lowerCAmelCase  ,      1  ,      n - 1 )


if __name__ == "__main__":
					main()





import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


SCREAMING_SNAKE_CASE_        =      logging.get_logger(__name__)

class 				a  (	UpperCAmelCase				):


						def __init__(       self						,					*A_						,					**A_	):







										'''simple docstring'''


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


