





'''simple docstring'''




from __future__ import annotations

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

from sympy import diff







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase       ,    _lowerCAmelCase = 10**-10    )->     float:
 __UpperCAmelCase					=   a
 while True:
  __UpperCAmelCase					=   Decimal(_lowerCAmelCase    ) - (
      Decimal(eval(_lowerCAmelCase    )    ) / Decimal(eval(str(diff(_lowerCAmelCase    )    )    )    )  # noqa: S307
  )
  # This number dictates the accuracy of the answer
  if abs(eval(_lowerCAmelCase    )    ) < precision:  # noqa: S307
   return float(_lowerCAmelCase    )


# 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)}""")












'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A:					List[str]							=				{
    """configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
    """tokenization_luke""": ["""LukeTokenizer"""],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _A:					Union[str, Any]							=				[
        """LUKE_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """LukeForEntityClassification""",
        """LukeForEntityPairClassification""",
        """LukeForEntitySpanClassification""",
        """LukeForMultipleChoice""",
        """LukeForQuestionAnswering""",
        """LukeForSequenceClassification""",
        """LukeForTokenClassification""",
        """LukeForMaskedLM""",
        """LukeModel""",
        """LukePreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
    from .tokenization_luke import LukeTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_luke import (
            LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
            LukeForEntityClassification,
            LukeForEntityPairClassification,
            LukeForEntitySpanClassification,
            LukeForMaskedLM,
            LukeForMultipleChoice,
            LukeForQuestionAnswering,
            LukeForSequenceClassification,
            LukeForTokenClassification,
            LukeModel,
            LukePreTrainedModel,
        )

else:
    import sys

    _A:					str							=				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





