import math as m




def 				_snake_case     (       lowerCAmelCase							:       Any       ,			lowerCAmelCase							:       Tuple       ,			lowerCAmelCase							:       List[Any]=0.001     ):
		"""simple docstring"""







		return (f(a + h     ) - f(a - h     )) / (2 * h)




def 				_snake_case     (       lowerCAmelCase							:       Tuple       ,			lowerCAmelCase							:       Tuple=0       ,			lowerCAmelCase							:       Union[str, Any]=1_0_0       ,			lowerCAmelCase							:       List[str]=0.0001       ,			lowerCAmelCase							:       str=1E-6       ,			lowerCAmelCase							:       Optional[Any]=False     ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   xa  # set the initial guess
		SCREAMING_SNAKE_CASE_  :		int    				=   [a]
		SCREAMING_SNAKE_CASE_  :		Any    				=   abs(f(lowerCAmelCase     )     )
		SCREAMING_SNAKE_CASE_  :		Any    				=   lambda lowerCAmelCase     : calc_derivative(lowerCAmelCase       ,			lowerCAmelCase       ,			h=lowerCAmelCase     )  # noqa: E731  Derivative of f(x)
		for _ in range(lowerCAmelCase     ):
				if fa(lowerCAmelCase     ) == 0:
						raise ValueError("No converging solution found"     )
				SCREAMING_SNAKE_CASE_  :		List[Any]    				=   a - f(lowerCAmelCase     ) / fa(lowerCAmelCase     )  # Calculate the next estimate
				if logsteps:
						steps.append(lowerCAmelCase     )
				if error < maxerror:
						break
		else:
				raise ValueError("Iteration limit reached, no converging solution found"     )
		if logsteps:
				# If logstep is true, then log intermediate steps
				return a, error, steps
		return a, error


if __name__ == "__main__":
		from matplotlib import pyplot as plt

		__lowerCamelCase :     Any          =  lambda x: m.tanh(x) ** 2 - m.exp(3 * x)  # noqa: E731
		__lowerCamelCase       ,						__lowerCamelCase       ,						__lowerCamelCase :     Tuple          =  newton_raphson(
		    f, xa=10, maxiter=10_00, step=1E-6, logsteps=True
		)
		plt.plot([abs(f(x)) for x in steps])
		plt.xlabel('''step''')
		plt.ylabel('''error''')
		plt.show()
		print(f'''solution = {{{solution:f}}}, error = {{{error:f}}}''')

import warnings

from ...utils import logging
from .image_processing_vit import ViTImageProcessor


__lowerCamelCase :     Tuple          =  logging.get_logger(__name__)






class 		a__						( A__ ):

					def __init__(   self				:	List[Any],*_A				:	Union[str, Any],**_A				:	List[Any]   ):







							"""simple docstring"""






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