





'''simple docstring'''




from __future__ import annotations

from statistics import mean
def 	UpperCAmelCase_							(					__lowercase							:      list[int]			,     __lowercase							:      list[int]			,     __lowercase							:      int       )		->       list[int]:


     '''simple docstring'''



     _UpperCAmelCase     							=   [0] * no_of_processes
     _UpperCAmelCase     							=   [0] * no_of_processes

     # Initialize remaining_time to waiting_time.

     for i in range(__lowercase       ):
          _UpperCAmelCase     							=   burst_time[i]
     _UpperCAmelCase     							=   []

     _UpperCAmelCase     							=   0
     _UpperCAmelCase     							=   0

     # When processes are not completed,
     # A process whose arrival time has passed \
     # and has remaining execution time is put into the ready_process.
     # The shortest process in the ready_process, target_process is executed.

     while completed != no_of_processes:
          _UpperCAmelCase     							=   []
          _UpperCAmelCase     							=   -1

          for i in range(__lowercase       ):
               if (arrival_time[i] <= total_time) and (remaining_time[i] > 0):
                    ready_process.append(__lowercase       )

          if len(__lowercase       ) > 0:
               _UpperCAmelCase     							=   ready_process[0]
               for i in ready_process:
                    if remaining_time[i] < remaining_time[target_process]:
                         _UpperCAmelCase     							=   i
               total_time += burst_time[target_process]
               completed += 1
               _UpperCAmelCase     							=   0
               _UpperCAmelCase     							=   (
                   total_time - arrival_time[target_process] - burst_time[target_process]
               )
          else:
               total_time += 1

     return waiting_time
def 	UpperCAmelCase_							(					__lowercase							:      list[int]			,     __lowercase							:      int			,     __lowercase							:      list[int]       )		->       list[int]:


     '''simple docstring'''



     _UpperCAmelCase     							=   [0] * no_of_processes
     for i in range(__lowercase       ):
          _UpperCAmelCase     							=   burst_time[i] + waiting_time[i]
     return turn_around_time


if __name__ == "__main__":
  print('''[TEST CASE 01]''')

  __SCREAMING_SNAKE_CASE     :Dict       =				4
  __SCREAMING_SNAKE_CASE     :int       =				[2, 5, 3, 7]
  __SCREAMING_SNAKE_CASE     :List[Any]       =				[0, 0, 0, 0]
  __SCREAMING_SNAKE_CASE     :Tuple       =				calculate_waitingtime(arrival_time, burst_time, no_of_processes)
  __SCREAMING_SNAKE_CASE     :Any       =				calculate_turnaroundtime(
      burst_time, no_of_processes, waiting_time
  )

  # Printing the Result
  print('''PID\tBurst Time\tArrival Time\tWaiting Time\tTurnaround Time''')
  for i, process_id in enumerate(list(range(1, 5))):
    print(
        F"{process_id}\t{burst_time[i]}\t\t\t{arrival_time[i]}\t\t\t\t"
        F"{waiting_time[i]}\t\t\t\t{turn_around_time[i]}"
    )
  print(F"\nAverage waiting time = {mean(waiting_time):.5f}")
  print(F"Average turnaround time = {mean(turn_around_time):.5f}")











'''simple docstring'''




from ..utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_scipy_available,
    is_torch_available,
    is_torchsde_available,
)


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_pt_objects import *  # noqa F403
else:
  from .scheduling_consistency_models import CMStochasticIterativeScheduler
  from .scheduling_ddim import DDIMScheduler
  from .scheduling_ddim_inverse import DDIMInverseScheduler
  from .scheduling_ddim_parallel import DDIMParallelScheduler
  from .scheduling_ddpm import DDPMScheduler
  from .scheduling_ddpm_parallel import DDPMParallelScheduler
  from .scheduling_deis_multistep import DEISMultistepScheduler
  from .scheduling_dpmsolver_multistep import DPMSolverMultistepScheduler
  from .scheduling_dpmsolver_multistep_inverse import DPMSolverMultistepInverseScheduler
  from .scheduling_dpmsolver_singlestep import DPMSolverSinglestepScheduler
  from .scheduling_euler_ancestral_discrete import EulerAncestralDiscreteScheduler
  from .scheduling_euler_discrete import EulerDiscreteScheduler
  from .scheduling_heun_discrete import HeunDiscreteScheduler
  from .scheduling_ipndm import IPNDMScheduler
  from .scheduling_k_dpm_2_ancestral_discrete import KDPMaAncestralDiscreteScheduler
  from .scheduling_k_dpm_2_discrete import KDPMaDiscreteScheduler
  from .scheduling_karras_ve import KarrasVeScheduler
  from .scheduling_pndm import PNDMScheduler
  from .scheduling_repaint import RePaintScheduler
  from .scheduling_sde_ve import ScoreSdeVeScheduler
  from .scheduling_sde_vp import ScoreSdeVpScheduler
  from .scheduling_unclip import UnCLIPScheduler
  from .scheduling_unipc_multistep import UniPCMultistepScheduler
  from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin
  from .scheduling_vq_diffusion import VQDiffusionScheduler

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_flax_objects import *  # noqa F403
else:
  from .scheduling_ddim_flax import FlaxDDIMScheduler
  from .scheduling_ddpm_flax import FlaxDDPMScheduler
  from .scheduling_dpmsolver_multistep_flax import FlaxDPMSolverMultistepScheduler
  from .scheduling_karras_ve_flax import FlaxKarrasVeScheduler
  from .scheduling_lms_discrete_flax import FlaxLMSDiscreteScheduler
  from .scheduling_pndm_flax import FlaxPNDMScheduler
  from .scheduling_sde_ve_flax import FlaxScoreSdeVeScheduler
  from .scheduling_utils_flax import (
      FlaxKarrasDiffusionSchedulers,
      FlaxSchedulerMixin,
      FlaxSchedulerOutput,
      broadcast_to_shape_from_left,
  )


try:
  if not (is_torch_available() and is_scipy_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_torch_and_scipy_objects import *  # noqa F403
else:
  from .scheduling_lms_discrete import LMSDiscreteScheduler

try:
  if not (is_torch_available() and is_torchsde_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_torch_and_torchsde_objects import *  # noqa F403
else:
  from .scheduling_dpmsolver_sde import DPMSolverSDEScheduler




