





from __future__ import annotations

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

from sympy import diff







def  _SCREAMING_SNAKE_CASE				(   a					,						a					,						a = 10**-10  )      ->      float:
					__A	:						Tuple       =				a
					while True:
										__A	:						List[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_tokenizers_available, is_torch_available


UpperCAmelCase						:   Any			  =     {
    '''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
    '''tokenization_mvp''': ['''MvpTokenizer'''],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase						:   int			  =     ['''MvpTokenizerFast''']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase						:   str			  =     [
				    '''MVP_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''MvpForCausalLM''',
				    '''MvpForConditionalGeneration''',
				    '''MvpForQuestionAnswering''',
				    '''MvpForSequenceClassification''',
				    '''MvpModel''',
				    '''MvpPreTrainedModel''',
				]

if TYPE_CHECKING:
				from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
				from .tokenization_mvp import MvpTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_mvp_fast import MvpTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_mvp import (
								    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MvpForCausalLM,
								    MvpForConditionalGeneration,
								    MvpForQuestionAnswering,
								    MvpForSequenceClassification,
								    MvpModel,
								    MvpPreTrainedModel,
								)

else:
				import sys

				UpperCAmelCase						:   List[str]			  =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




