






from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403

def    UpperCamelCase						(	_A,   _A,   _A = "x",   _A = 10**-10,   _A = 1,   ):






						"""simple docstring"""







						__magic_name__      :       int       						= symbols(_A			)
						__magic_name__      :       Tuple       						= lambdify(_A,   _A			)
						__magic_name__      :       Dict       						= lambdify(_A,   diff(_A,   _A			)			)

						__magic_name__      :       Any       						= starting_point

						while True:
												if diff_function(_A			) != 0:
																		__magic_name__      :       Any       						= prev_guess - multiplicity * func(_A			) / diff_function(
																		    _A			)
												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

												__magic_name__      :       Optional[Any]       						= 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=0.0_05)}""",
		)

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








import os
from pathlib import Path

def    UpperCamelCase						(	):






						"""simple docstring"""







						from torch.utils.cpp_extension import load

						__magic_name__      :       Dict       						= Path(_A			).resolve().parent.parent.parent / """kernels""" / """deformable_detr"""
						__magic_name__      :       Optional[int]       						= [
						    root / filename
						    for filename in [
						        """vision.cpp""",
						        os.path.join("""cpu""",   """ms_deform_attn_cpu.cpp"""			),
						        os.path.join("""cuda""",   """ms_deform_attn_cuda.cu"""			),
						    ]
						]

						load(
						    """MultiScaleDeformableAttention""",   _A,   with_cuda=_A,   extra_include_paths=[str(_A			)],   extra_cflags=["""-DWITH_CUDA=1"""],   extra_cuda_cflags=[
						        """-DCUDA_HAS_FP16=1""",
						        """-D__CUDA_NO_HALF_OPERATORS__""",
						        """-D__CUDA_NO_HALF_CONVERSIONS__""",
						        """-D__CUDA_NO_HALF2_OPERATORS__""",
						    ],   )

						import MultiScaleDeformableAttention as MSDA

						return MSDA
