

import gc
import threading
import time

import psutil
import torch

class 				__UpperCamelCase				:







	def __init__(   self: List[Any]      ):

						'''simple docstring'''





						__magic_name__							=    psutil.Process()
						__magic_name__							=    False







	def 	_SCREAMING_SNAKE_CASE							(   self: int      ):

						'''simple docstring'''





						__magic_name__							=    -1

						while True:
											__magic_name__							=    max(self.process.memory_info().rss  , self.cpu_memory_peak      )

											# can't sleep or will not catch the peak right (this comment is here on purpose)
											if not self.peak_monitoring:
																break







	def 	_SCREAMING_SNAKE_CASE							(   self: str      ):

						'''simple docstring'''





						__magic_name__							=    True
						__magic_name__							=    threading.Thread(target=self.peak_monitor      )
						__magic_name__							=    True
						self.thread.start()







	def 	_SCREAMING_SNAKE_CASE							(   self: str      ):

						'''simple docstring'''





						__magic_name__							=    False
						self.thread.join()
						return self.cpu_memory_peak




A__						=							PeakCPUMemory()




def 					_lowercase     (				)				->	List[str]:




					'''simple docstring'''







					__magic_name__							=    {'time': time.time()}

					gc.collect()
					torch.cuda.empty_cache()

					# CPU mem
					__magic_name__							=    psutil.Process().memory_info().rss
					cpu_peak_tracker.start()

					# GPU mem
					for i in range(torch.cuda.device_count()				):
										__magic_name__							=    torch.cuda.memory_allocated(a_				)
					torch.cuda.reset_peak_memory_stats()

					return measures




def 					_lowercase     (				a_				:					Dict				)				->	Optional[Any]:




					'''simple docstring'''







					__magic_name__							=    {'time': time.time() - start_measures['time']}

					gc.collect()
					torch.cuda.empty_cache()

					# CPU mem
					__magic_name__							=    (psutil.Process().memory_info().rss - start_measures['cpu']) / 2**2_0
					__magic_name__							=    (cpu_peak_tracker.stop() - start_measures['cpu']) / 2**2_0

					# GPU mem
					for i in range(torch.cuda.device_count()				):
										__magic_name__							=    (torch.cuda.memory_allocated(a_				) - start_measures[str(a_				)]) / 2**2_0
										__magic_name__							=    (torch.cuda.max_memory_allocated(a_				) - start_measures[str(a_				)]) / 2**2_0

					return measures




def 					_lowercase     (				a_				:					Optional[Any]					,a_				:					Dict				)				->	Any:




					'''simple docstring'''







					print(F'{description}:'				)
					print(F'- Time: {measures["time"]:.2f}s'				)
					for i in range(torch.cuda.device_count()				):
										print(F'- GPU {i} allocated: {measures[str(a_				)]:.2f}MiB'				)
										__magic_name__							=    measures[F'{i}-peak']
										print(F'- GPU {i} peak: {peak:.2f}MiB'				)
					print(F'- CPU RAM allocated: {measures["cpu"]:.2f}MiB'				)
					print(F'- CPU RAM peak: {measures["cpu-peak"]:.2f}MiB'				)







from math import factorial, radians




def 					_lowercase     (				a_				:					float					,a_				:					int = 1_8					,a_				:					int = 1_0				)				->	float:




					'''simple docstring'''







					__magic_name__							=    angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)

					# Converting from degrees to radians
					__magic_name__							=    radians(a_				)

					__magic_name__							=    angle_in_radians
					__magic_name__							=    3
					__magic_name__							=    -1

					for _ in range(a_				):
										result += (b * (angle_in_radians**a)) / factorial(a_				)

										__magic_name__							=    -b  # One positive term and the next will be negative and so on...
										a += 2  # Increased by 2 for every term.

					return round(a_					,a_				)


if __name__ == "__main__":
						__import__("doctest").testmod()




