


import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


snake_case_  :	Tuple							  =							logging.get_logger(__name__)

class   A__							(						UpperCamelCase__     ):




						def __init__(				self    :					Optional[Any] ,			*_a    :					Optional[int] ,			**_a    :					Optional[Any]     )							->   None:


										"""simple docstring"""





										warnings.warn(
										    '''The class MobileNetV1FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
										    ''' Please use MobileNetV1ImageProcessor instead.''' ,			_a ,			)
										super().__init__(*_a ,			**_a     )



import math as m







def   lowerCamelCase(      a__		,a__		,a__=0.001):
				return (f(a + h) - f(a - h)) / (2 * h)







def   lowerCamelCase(      a__		,a__=0		,a__=100		,a__=0.0001		,a__=1e-6		,a__=False):
				_SCREAMING_SNAKE_CASE	     =xa  # set the initial guess
				_SCREAMING_SNAKE_CASE	     =[a]
				_SCREAMING_SNAKE_CASE	     =abs(f(a__))
				_SCREAMING_SNAKE_CASE	     =lambda a__: calc_derivative(a__		,a__		,h=a__)  # noqa: E731  Derivative of f(x)
				for _ in range(a__):
								if fa(a__) == 0:
												raise ValueError('''No converging solution found''')
								_SCREAMING_SNAKE_CASE	     =a - f(a__) / fa(a__)  # Calculate the next estimate
								if logsteps:
												steps.append(a__)
								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

							snake_case_  :	Tuple							  =							lambda x: m.tanh(x) ** 2 - m.exp(3 * x)  # noqa: E731
							snake_case_  , snake_case_  , snake_case_  :	str							  =							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}}}""")