





from __future__ import annotations

from decimal import Decimal
from math import *  # noqa: F403

from sympy import diff





def      lowerCAmelCase_ (       __a	,    __a	,    __a = 10**-10		)     ->		float:







  """simple docstring"""





  lowerCamelCase__:      str			  =a
  while True:
    lowerCamelCase__:      Optional[Any]			  =Decimal(__a		) - (
        Decimal(eval(__a		)		) / Decimal(eval(str(diff(__a		)		)		)		)  # noqa: S307
    )
    # This number dictates the accuracy of the answer
    if abs(eval(__a		)		) < precision:  # noqa: S307
      return float(__a		)


# 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
     print(f'The root of x**2 - 5*x + 2 = 0 is {newton_raphson("x**2 - 5*x + 2", 0.4)}')
     # Find Square Root of 5
     print(f'The root of log(x) - 1 = 0 is {newton_raphson("log(x) - 1", 2)}')
     # Exponential Roots
     print(f'The root of exp(x) - 1 = 0 is {newton_raphson("exp(x) - 1", 0)}')








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A									=				{"configuration_ibert": ["IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "IBertConfig", "IBertOnnxConfig"]}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __A									=				[
         "IBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "IBertForMaskedLM",
         "IBertForMultipleChoice",
         "IBertForQuestionAnswering",
         "IBertForSequenceClassification",
         "IBertForTokenClassification",
         "IBertModel",
         "IBertPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_ibert import (
              IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              IBertForMaskedLM,
              IBertForMultipleChoice,
              IBertForQuestionAnswering,
              IBertForSequenceClassification,
              IBertForTokenClassification,
              IBertModel,
              IBertPreTrainedModel,
          )

else:
     import sys

     __A									=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

