





import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


__A				:    Dict       =   logging.get_logger(__name__)

class 	A_       (a_			):
	def __init__(    self							,					*_A							,					**_A		):






				'''simple docstring'''







				warnings.warn(
				    '''The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
				    ''' use GLPNImageProcessor instead.'''							,					_A							,					)
				super().__init__(*_A							,					**_A		)










from __future__ import annotations

from collections.abc import Callable





def 						__SCREAMING_SNAKE_CASE  (				UpperCamelCase__			,			UpperCamelCase__			,			UpperCamelCase__			,			UpperCamelCase__ = 100			,			)  ->				float:







			'''simple docstring'''

			UpperCAmelCase   		=				x_start
			UpperCAmelCase   		=				fnc(UpperCamelCase__ )
			UpperCAmelCase   		=				0.0
			for _ in range(UpperCamelCase__ ):
						# Approximates small segments of curve as linear and solve
						# for trapezoidal area
						UpperCAmelCase   		=				(x_end - x_start) / steps + xa
						UpperCAmelCase   		=				fnc(UpperCamelCase__ )
						area += abs(fxa + fxa ) * (xa - xa) / 2
						# Increment step
						UpperCAmelCase   		=				xa
						UpperCAmelCase   		=				fxa
			return area


if __name__ == "__main__":





				def 						__SCREAMING_SNAKE_CASE  (				UpperCamelCase__ )  ->				str:







							'''simple docstring'''

							return x**3 + x**2

				print("f(x) = x^3 + x^2")
				print("The area between the curve, x = -5, x = 5 and the x axis is:")
				__A				:    List[Any]       =   10
				while i <= 100_000:
								print(F'with {i} steps: {trapezoidal_area(f, -5, 5, i)}')
								i *= 10



