


"""simple docstring"""






from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403
def       A_   (   _lowerCAmelCase     :					str,     _lowerCAmelCase     :					complex,     _lowerCAmelCase     :					str = "x",     _lowerCAmelCase     :					float = 10**-10,     _lowerCAmelCase     :					int = 1,     ):






     """simple docstring"""

     _a    	=				symbols(_lowerCAmelCase       )
     _a    	=				lambdify(_lowerCAmelCase,     _lowerCAmelCase       )
     _a    	=				lambdify(_lowerCAmelCase,     diff(_lowerCAmelCase,     _lowerCAmelCase       )       )

     _a    	=				starting_point

     while True:
          if diff_function(_lowerCAmelCase       ) != 0:
               _a    	=				prev_guess - multiplicity * func(_lowerCAmelCase       ) / diff_function(
                   _lowerCAmelCase       )
          else:
               raise ZeroDivisionError('''Could not find root'''       ) from None

          # Precision is checked by comparing the difference of consecutive guesses
          if abs(next_guess - prev_guess       ) < precision:
               return next_guess

          _a    	=				next_guess


# Let's Execute
if __name__ == "__main__":
   # Find root of trigonometric function
   # Find value of pi
   print(f'The root of sin(x) = 0 is {newton_raphson("sin(x)", 2)}')

   # Find root of polynomial
   # Find fourth Root of 5
   print(f'The root of x**4 - 5 = 0 is {newton_raphson("x**4 -5", 0.4 +5j)}')

   # Find value of e
   print(
       '''The root of log(y) - 1 = 0 is ''',
       f'{newton_raphson("log(y) - 1", 2, variable="y")}',
   )

   # Exponential Roots
   print(
       '''The root of exp(x) - 1 = 0 is''',
       f'{newton_raphson("exp(x) - 1", 10, precision=0.005)}',
   )

   # Find root of cos(x)
   print(f'The root of cos(x) = 0 is {newton_raphson("cos(x)", 0)}')









"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__snake_case		=       {
    '''configuration_lxmert''': ['''LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LxmertConfig'''],
    '''tokenization_lxmert''': ['''LxmertTokenizer'''],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __snake_case		=       ['''LxmertTokenizerFast''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __snake_case		=       [
       '''LxmertEncoder''',
       '''LxmertForPreTraining''',
       '''LxmertForQuestionAnswering''',
       '''LxmertModel''',
       '''LxmertPreTrainedModel''',
       '''LxmertVisualFeatureEncoder''',
       '''LxmertXLayer''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __snake_case		=       [
       '''TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFLxmertForPreTraining''',
       '''TFLxmertMainLayer''',
       '''TFLxmertModel''',
       '''TFLxmertPreTrainedModel''',
       '''TFLxmertVisualFeatureEncoder''',
   ]


if TYPE_CHECKING:
   from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
   from .tokenization_lxmert import LxmertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_lxmert_fast import LxmertTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_lxmert import (
          LxmertEncoder,
          LxmertForPreTraining,
          LxmertForQuestionAnswering,
          LxmertModel,
          LxmertPreTrainedModel,
          LxmertVisualFeatureEncoder,
          LxmertXLayer,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_lxmert import (
          TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFLxmertForPreTraining,
          TFLxmertMainLayer,
          TFLxmertModel,
          TFLxmertPreTrainedModel,
          TFLxmertVisualFeatureEncoder,
      )

else:
   import sys

   __snake_case		=       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)