




import math as m
def 		a_       (   __lowerCAmelCase      ,   __lowerCAmelCase      ,   __lowerCAmelCase=0.001							):
  return (f(a + h							) - f(a - h							)) / (2 * h)
def 		a_       (   __lowerCAmelCase      ,   __lowerCAmelCase=0      ,   __lowerCAmelCase=1_00      ,   __lowerCAmelCase=0.0_001      ,   __lowerCAmelCase=1E-6      ,   __lowerCAmelCase=False							):
  lowerCAmelCase__								=			xa  # set the initial guess
  lowerCAmelCase__								=			[a]
  lowerCAmelCase__								=			abs(f(__lowerCAmelCase							)							)
  lowerCAmelCase__								=			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'''							)
    lowerCAmelCase__								=			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

      __magic_name__     :     List[Any]  							=					lambda x: m.tanh(x) ** 2 - m.exp(3 * x)  # noqa: E731
      __magic_name__							,   __magic_name__							,   __magic_name__     :     Optional[int]  							=					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 os

from ...utils import logging
from .utils import DataProcessor, InputExample


__magic_name__     :     str  							=					logging.get_logger(__name__)





class 						SCREAMING_SNAKE_CASE__		(_a ):
     def __init__(	self  :		Any					,	__lowerCamelCase  :		Any					,	__lowerCamelCase  :		Optional[int]=None	):



       """simple docstring"""
       lowerCAmelCase__								=			language
       lowerCAmelCase__								=			train_language
     def 					A__			(	self  :		str					,	__lowerCamelCase  :		List[str]	):



       """simple docstring"""
       lowerCAmelCase__								=			self.language if self.train_language is None else self.train_language
       lowerCAmelCase__								=			self._read_tsv(os.path.join(__lowerCamelCase					,	F"""XNLI-MT-1.0/multinli/multinli.train.{lg}.tsv"""	)	)
       lowerCAmelCase__								=			[]
       for i, line in enumerate(__lowerCamelCase	):
         if i == 0:
           continue
         lowerCAmelCase__								=			F"""train-{i}"""
         lowerCAmelCase__								=			line[0]
         lowerCAmelCase__								=			line[1]
         lowerCAmelCase__								=			'''contradiction''' if line[2] == '''contradictory''' else line[2]
         if not isinstance(__lowerCamelCase					,	__lowerCamelCase	):
           raise ValueError(F"""Training input {text_a} is not a string"""	)
         if not isinstance(__lowerCamelCase					,	__lowerCamelCase	):
           raise ValueError(F"""Training input {text_b} is not a string"""	)
         if not isinstance(__lowerCamelCase					,	__lowerCamelCase	):
           raise ValueError(F"""Training label {label} is not a string"""	)
         examples.append(InputExample(guid=__lowerCamelCase					,	text_a=__lowerCamelCase					,	text_b=__lowerCamelCase					,	label=__lowerCamelCase	)	)
       return examples
     def 					A__			(	self  :		Dict					,	__lowerCamelCase  :		Union[str, Any]	):



       """simple docstring"""
       lowerCAmelCase__								=			self._read_tsv(os.path.join(__lowerCamelCase					,	'''XNLI-1.0/xnli.test.tsv'''	)	)
       lowerCAmelCase__								=			[]
       for i, line in enumerate(__lowerCamelCase	):
         if i == 0:
           continue
         lowerCAmelCase__								=			line[0]
         if language != self.language:
           continue
         lowerCAmelCase__								=			F"""test-{i}"""
         lowerCAmelCase__								=			line[6]
         lowerCAmelCase__								=			line[7]
         lowerCAmelCase__								=			line[1]
         if not isinstance(__lowerCamelCase					,	__lowerCamelCase	):
           raise ValueError(F"""Training input {text_a} is not a string"""	)
         if not isinstance(__lowerCamelCase					,	__lowerCamelCase	):
           raise ValueError(F"""Training input {text_b} is not a string"""	)
         if not isinstance(__lowerCamelCase					,	__lowerCamelCase	):
           raise ValueError(F"""Training label {label} is not a string"""	)
         examples.append(InputExample(guid=__lowerCamelCase					,	text_a=__lowerCamelCase					,	text_b=__lowerCamelCase					,	label=__lowerCamelCase	)	)
       return examples



     def 					A__			(	self  :		List[str]	):



       """simple docstring"""
       return ["contradiction", "entailment", "neutral"]



__magic_name__     :     Tuple  							=					{
    """xnli""": XnliProcessor,
}

__magic_name__     :     List[Any]  							=					{
    """xnli""": """classification""",
}

__magic_name__     :     str  							=					{
    """xnli""": 3,
}

