code: 
  
  
  
  
  
  from __future__ import annotations
  def   _A (	SCREAMING_SNAKE_CASE  :     str		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    a__			:      Dict            =[0] * len(lowercase_		)
    for i in range(1 , len(lowercase_		)		):
      a__			:      Union[str, Any]            =duration_times[i - 1] + waiting_times[i - 1]
    return waiting_times
  def   _A (	SCREAMING_SNAKE_CASE  :     Optional[Any] , SCREAMING_SNAKE_CASE  :     Union[str, Any]		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    return [
        duration_time + waiting_times[i]
        for i, duration_time in enumerate(lowercase_		)
    ]
  def   _A (	SCREAMING_SNAKE_CASE  :     Union[str, Any]		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    return sum(lowercase_		) / len(lowercase_		)
  def   _A (	SCREAMING_SNAKE_CASE  :     str		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    return sum(lowercase_		) / len(lowercase_		)
  
  
  if __name__ == "__main__":
         # process id's
         UpperCAmelCase			:			int	  = [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			:			Optional[Any]	  = [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			:			List[Any]	  = calculate_waiting_times(duration_times)
         UpperCAmelCase			:			int	  = calculate_turnaround_times(duration_times, waiting_times)
  
         # get the average times
         UpperCAmelCase			:			str	  = calculate_average_waiting_time(waiting_times)
         UpperCAmelCase			:			int	  = 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}""")
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  
  import importlib
  import sys
  from argparse import REMAINDER, ArgumentParser
  from pathlib import Path
  
  import torch_xla.distributed.xla_multiprocessing as xmp
  def   _A (	):
  
  
  
  
  
    """simple docstring"""
  
  
  
    a__			:      Optional[int]            =ArgumentParser(
        description=(
            "PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes"
        )		)
  
    # Optional arguments for the launch helper
    parser.add_argument("--num_cores" , type=SCREAMING_SNAKE_CASE , default=1 , help="Number of TPU cores to use (1 or 8)."		)
  
    # positional
    parser.add_argument(
        "training_script" , type=SCREAMING_SNAKE_CASE , help=(
            "The full path to the single TPU training "
            "program/script to be launched in parallel, "
            "followed by all the arguments for the "
            "training script"
        ) , )
  
    # rest from the training program
    parser.add_argument("training_script_args" , nargs=SCREAMING_SNAKE_CASE		)
  
    return parser.parse_args()
  def   _A (	):
  
  
  
  
  
    """simple docstring"""
  
  
  
    a__			:      Optional[Any]            =parse_args()
  
    # Import training_script as a module.
    a__			:      Tuple            =Path(args.training_script		)
    sys.path.append(str(script_fpath.parent.resolve()		)		)
    a__			:      Tuple            =script_fpath.stem
    a__			:      Any            =importlib.import_module(SCREAMING_SNAKE_CASE		)
  
    # Patch sys.argv
    a__			:      List[str]            =[args.training_script] + args.training_script_args + ["--tpu_num_cores", str(args.num_cores		)]
  
    xmp.spawn(mod._mp_fn , args=() , nprocs=args.num_cores		)
  
  
  if __name__ == "__main__":
       main()
  
  
  
  
  
  
  