"""simple docstring"""




def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							_enforce_args(UpperCamelCase__       ,    UpperCamelCase__				)
							if n == 0:
														return 0
							A__	     =							float('-inf'				)
							for i in range(1       ,    n + 1				):
														A__	     =							max(
														    UpperCamelCase__       ,    prices[i - 1] + naive_cut_rod_recursive(n - i       ,    UpperCamelCase__				)				)

							return max_revue






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							_enforce_args(UpperCamelCase__       ,    UpperCamelCase__				)
							A__	     =							[float('-inf'				) for _ in range(n + 1				)]
							return _top_down_cut_rod_recursive(UpperCamelCase__       ,    UpperCamelCase__       ,    UpperCamelCase__				)






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							if max_rev[n] >= 0:
														return max_rev[n]
							elif n == 0:
														return 0
							else:
														A__	     =							float('-inf'				)
														for i in range(1       ,    n + 1				):
																					A__	     =							max(
																					    UpperCamelCase__       ,    prices[i - 1] + _top_down_cut_rod_recursive(n - i       ,    UpperCamelCase__       ,    UpperCamelCase__				)       ,    )

														A__	     =							max_revenue

							return max_rev[n]






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							_enforce_args(UpperCamelCase__       ,    UpperCamelCase__				)

							# length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
							# length 0.
							A__	     =							[float('-inf'				) for _ in range(n + 1				)]
							A__	     =							0

							for i in range(1       ,    n + 1				):
														A__	     =							max_rev[i]
														for j in range(1       ,    i + 1				):
																					A__	     =							max(UpperCamelCase__       ,    prices[j - 1] + max_rev[i - j]				)

														A__	     =							max_revenue_i

							return max_rev[n]






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							if n < 0:
														A__	     =							F'''n must be greater than or equal to 0. Got n = {n}'''
														raise ValueError(UpperCamelCase__				)

							if n > len(UpperCamelCase__				):
														A__	     =							(
														    'Each integral piece of rod must have a corresponding price. '
														    F'''Got n = {n} but length of prices = {len(UpperCamelCase__				)}'''
														)
														raise ValueError(UpperCamelCase__				)






def   UpperCAmelCase					(	):






							"""simple docstring"""





							A__	     =							[6, 10, 12, 15, 20, 23]
							A__	     =							len(UpperCamelCase__				)

							# the best revenue comes from cutting the rod into 6 pieces, each
							# of length 1 resulting in a revenue of 6 * 6 = 36.
							A__	     =							36

							A__	     =							top_down_cut_rod(UpperCamelCase__       ,    UpperCamelCase__				)
							A__	     =							bottom_up_cut_rod(UpperCamelCase__       ,    UpperCamelCase__				)
							A__	     =							naive_cut_rod_recursive(UpperCamelCase__       ,    UpperCamelCase__				)

							assert expected_max_revenue == max_rev_top_down
							assert max_rev_top_down == max_rev_bottom_up
							assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
				main()






"""simple docstring"""




import warnings

from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor


__lowerCamelCase											=  logging.get_logger(__name__)
class     UpperCamelCase__(			__A ):





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





