






"""simple docstring"""



from __future__ import annotations

import math
from collections.abc import Callable

def 			_snake_case    (					lowerCamelCase__     :   Callable[[int | float], int | float]    ,						lowerCamelCase__     :   int | float    ,						lowerCamelCase__     :   int | float    ,						lowerCamelCase__     :   int = 100    ,						)    ->     float:
							lowerCamelCase_	:							Any									=x_start
							lowerCamelCase_	:							str									=fnc(_UpperCamelCase  )
							lowerCamelCase_	:							List[Any]									=0.0

							for _ in range(_UpperCamelCase  ):
														# Approximates curve as a sequence of linear lines and sums their length
														lowerCamelCase_	:							List[Any]									=(x_end - x_start) / steps + xa
														lowerCamelCase_	:							Any									=fnc(_UpperCamelCase  )
														length += math.hypot(xa - xa    ,						fxa - fxa  )

														# Increment step
														lowerCamelCase_	:							int									=xa
														lowerCamelCase_	:							Union[str, Any]									=fxa

							return length


if __name__ == "__main__":

			def 			_snake_case    (					lowerCamelCase__     :   Any  )    ->     Optional[Any]:
										return math.sin(10 * x  )

			print('f(x) = sin(10 * x)')
			print('The length of the curve from x = -10 to x = 10 is:')
			A__	:    Tuple			 = 10
			while i <= 100_000:
						print(f'With {i} steps: {line_length(f, -10, 10, i)}')
						i *= 10











"""simple docstring"""



import torch

def 			_snake_case    (					)    ->     Union[str, Any]:
							if torch.cuda.is_available():
														lowerCamelCase_	:							int									=torch.cuda.device_count()
							else:
														lowerCamelCase_	:							List[str]									=0
							print(F"""Successfully ran on {num_gpus} GPUs"""  )


if __name__ == "__main__":
						main()



