"""simple docstring"""



from __future__ import annotations

def    _A(		lowerCAmelCase       ):
							A__					:    Optional[int]														= [0] * len(snake_case_       )
							for i in range(1 ,     len(snake_case_       )       ):
														A__					:    List[Any]														= duration_times[i - 1] + waiting_times[i - 1]
							return waiting_times

def    _A(		lowerCAmelCase ,     lowerCAmelCase       ):
							return [
							    duration_time + waiting_times[i]
							    for i, duration_time in enumerate(snake_case_       )
							]

def    _A(		lowerCAmelCase       ):
							return sum(snake_case_       ) / len(snake_case_       )

def    _A(		lowerCAmelCase       ):
							return sum(snake_case_       ) / len(snake_case_       )


if __name__ == "__main__":
	# process id's
	_UpperCamelCase         =		[1, 2, 3]

	# ensure that we actually have processes
	if len(processes) == 0:
		print("Zero amount of processes")
		raise SystemExit(0)

	# duration time of all processes
	_UpperCamelCase         =		[19, 8, 9]

	# ensure we can match each id to a duration time
	if len(duration_times) != len(processes):
		print("Unable to match all id's with their duration time")
		raise SystemExit(0)

	# get the waiting times and the turnaround times
	_UpperCamelCase         =		calculate_waiting_times(duration_times)
	_UpperCamelCase         =		calculate_turnaround_times(duration_times, waiting_times)

	# get the average times
	_UpperCamelCase         =		calculate_average_waiting_time(waiting_times)
	_UpperCamelCase         =		calculate_average_turnaround_time(turnaround_times)

	# print all the results
	print("Process ID\tDuration Time\tWaiting Time\tTurnaround Time")
	for i, process in enumerate(processes):
		print(
		    F'{process}\t\t{duration_times[i]}\t\t{waiting_times[i]}\t\t'
		    F'{turnaround_times[i]}'
		)
	print(F'Average waiting time = {average_waiting_time}')
	print(F'Average turn around time = {average_turnaround_time}')






"""simple docstring"""



import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_multi_gpu,
    require_single_gpu,
    test_sync,
)
from accelerate.utils import patch_environment
class 	__UpperCAmelCase						(unittest.TestCase    ):







			'''simple docstring'''





			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										A__					:    Optional[int]														= inspect.getfile(accelerate.test_utils       )
										A__					:    Tuple														= os.path.sep.join(mod_file.split(os.path.sep       )[:-1] + ["""scripts""", """test_sync.py"""]       )





			@require_cpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										debug_launcher(test_sync.main      ,			num_processes=1       )





			@require_cpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										debug_launcher(test_sync.main       )





			@require_single_gpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										test_sync.main()





			@require_multi_gpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										print(F'''Found {torch.cuda.device_count()} devices.'''       )
										A__					:    List[str]														= ["""torchrun""", F'''--nproc_per_node={torch.cuda.device_count()}''', self.test_file_path]
										with patch_environment(omp_num_threads=1       ):
																	execute_subprocess_async(snake_case_      ,			env=os.environ.copy()       )





