




"""simple docstring"""




import gc
import threading
import time

import psutil
import torch

class   UpperCAmelCase_    :
		def __init__(						self       )						->       str:
					__lowercase			:  List[Any]								=       psutil.Process()
					__lowercase			:  Any								=       False
		def 	_lowerCamelCase							(						self       )						->       Union[str, Any]:
					__lowercase			:  Optional[Any]								=       -1

					while True:
								__lowercase			:  List[str]								=       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 	_lowerCamelCase							(						self       )						->       Optional[Any]:
					__lowercase			:  List[Any]								=       True
					__lowercase			:  List[Any]								=       threading.Thread(target=self.peak_monitor       )
					__lowercase			:  Optional[int]								=       True
					self.thread.start()
		def 	_lowerCamelCase							(						self       )						->       Optional[Any]:
					__lowercase			:  Union[str, Any]								=       False
					self.thread.join()
					return self.cpu_memory_peak


a_        =       PeakCPUMemory()







def      __UpperCAmelCase     ( ):
			# Time
			__lowercase			:  Union[str, Any]								=       {'''time''': time.time()}

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

			# CPU mem
			__lowercase			:  List[Any]								=       psutil.Process().memory_info().rss
			cpu_peak_tracker.start()

			# GPU mem
			for i in range(torch.cuda.device_count()	):
						__lowercase			:  List[str]								=       torch.cuda.memory_allocated(__UpperCamelCase	)
			torch.cuda.reset_peak_memory_stats()

			return measures







def      __UpperCAmelCase     ( __UpperCamelCase	):
			# Time
			__lowercase			:  List[Any]								=       {'''time''': time.time() - start_measures['''time''']}

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

			# CPU mem
			__lowercase			:  Union[str, Any]								=       (psutil.Process().memory_info().rss - start_measures['''cpu''']) / 2**20
			__lowercase			:  Dict								=       (cpu_peak_tracker.stop() - start_measures['''cpu''']) / 2**20

			# GPU mem
			for i in range(torch.cuda.device_count()	):
						__lowercase			:  str								=       (torch.cuda.memory_allocated(__UpperCamelCase	) - start_measures[str(__UpperCamelCase	)]) / 2**20
						__lowercase			:  Optional[int]								=       (torch.cuda.max_memory_allocated(__UpperCamelCase	) - start_measures[str(__UpperCamelCase	)]) / 2**20

			return measures







def      __UpperCAmelCase     ( __UpperCamelCase	,				__UpperCamelCase	):
			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(__UpperCamelCase	)]:.2f}MiB"""	)
						__lowercase			:  Dict								=       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"""	)











'''simple docstring'''
def 		__SCREAMING_SNAKE_CASE       (	_UpperCamelCase = 100				):


   """simple docstring"""




   lowercase_						:     Dict							     =  n * (n + 1) * (2 * n + 1) / 6
   lowercase_						:     int							     =  (n * (n + 1) / 2) ** 2
   return int(square_of_sum - sum_of_squares				)


if __name__ == "__main__":
 print(f"""{solution() = }""")




