from typing import List

import datasets
from datasets.tasks import ImageClassification

from ..folder_based_builder import folder_based_builder


lowerCAmelCase      :				Any     			=datasets.utils.logging.get_logger(__name__)




class 						__snake_case						(			folder_based_builder.FolderBasedBuilderConfig		):





      '''simple docstring'''






      _snake_case     		=							None
      _snake_case     		=							None





class 						__snake_case						(			folder_based_builder.FolderBasedBuilder		):





      '''simple docstring'''






      _snake_case     		=							datasets.Image()
      _snake_case     		=							'image'
      _snake_case     		=							ImageFolderConfig
      _snake_case     		=							42  # definition at the bottom of the script
      _snake_case     		=							ImageClassification(image_column='image'			,	label_column='label'		)





lowerCAmelCase      :				Optional[Any]     			=[
    '''.blp''',
    '''.bmp''',
    '''.dib''',
    '''.bufr''',
    '''.cur''',
    '''.pcx''',
    '''.dcx''',
    '''.dds''',
    '''.ps''',
    '''.eps''',
    '''.fit''',
    '''.fits''',
    '''.fli''',
    '''.flc''',
    '''.ftc''',
    '''.ftu''',
    '''.gbr''',
    '''.gif''',
    '''.grib''',
    '''.h5''',
    '''.hdf''',
    '''.png''',
    '''.apng''',
    '''.jp2''',
    '''.j2k''',
    '''.jpc''',
    '''.jpf''',
    '''.jpx''',
    '''.j2c''',
    '''.icns''',
    '''.ico''',
    '''.im''',
    '''.iim''',
    '''.tif''',
    '''.tiff''',
    '''.jfif''',
    '''.jpe''',
    '''.jpg''',
    '''.jpeg''',
    '''.mpg''',
    '''.mpeg''',
    '''.msp''',
    '''.pcd''',
    '''.pxr''',
    '''.pbm''',
    '''.pgm''',
    '''.ppm''',
    '''.pnm''',
    '''.psd''',
    '''.bw''',
    '''.rgb''',
    '''.rgba''',
    '''.sgi''',
    '''.ras''',
    '''.tga''',
    '''.icb''',
    '''.vda''',
    '''.vst''',
    '''.webp''',
    '''.wmf''',
    '''.emf''',
    '''.xbm''',
    '''.xpm''',
]
lowerCAmelCase      :				List[Any]     			=IMAGE_EXTENSIONS








"""simple docstring"""





import math as m


def   _snake_case    (    _snake_case					:      List[Any]			, _snake_case					:      Tuple			, _snake_case					:      Tuple=0.001      ):
      return (f(a + h      ) - f(a - h      )) / (2 * h)


def   _snake_case    (    _snake_case					:      int			, _snake_case					:      List[Any]=0			, _snake_case					:      Any=100			, _snake_case					:      Any=0.0001			, _snake_case					:      Optional[Any]=1E-6			, _snake_case					:      Any=False      ):
      lowerCAmelCase       :						Optional[Any]							= xa  # set the initial guess
      lowerCAmelCase       :						str							= [a]
      lowerCAmelCase       :						List[str]							= abs(f(_snake_case      )      )
      lowerCAmelCase       :						Dict							= lambda _snake_case      : calc_derivative(_snake_case			, _snake_case			, h=_snake_case      )  # noqa: E731  Derivative of f(x)
      for _ in range(_snake_case      ):
            if fa(_snake_case      ) == 0:
                  raise ValueError('''No converging solution found'''      )
            lowerCAmelCase       :						Tuple							= a - f(_snake_case      ) / fa(_snake_case      )  # Calculate the next estimate
            if logsteps:
                  steps.append(_snake_case      )
            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__		:  Any     					=					lambda x: m.tanh(x) ** 2 - m.exp(3 * x)  # noqa: E731
 snake_case__					,  snake_case__					,  snake_case__		:  List[str]     					=					newton_raphson(
     f, xa=10, maxiter=1_000, 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}}}""")


