'''simple docstring'''
from collections import deque






class 			__lowercase		:







     """simple docstring"""






     def __init__(		self     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	List[str]		    =  process_name  # process name
         __UpperCamelCase	:	Union[str, Any]		    =  arrival_time  # arrival time of the process
         # completion time of finished process or last interrupted time
         __UpperCamelCase	:	Dict		    =  arrival_time
         __UpperCamelCase	:	Union[str, Any]		    =  burst_time  # remaining burst time
         __UpperCamelCase	:	Optional[int]		    =  0  # total time of the process wait in ready queue
         __UpperCamelCase	:	Union[str, Any]		    =  0  # time from arrival time to completion time






class 			__lowercase		:







     """simple docstring"""






     def __init__(		self     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			):
         # total number of mlfq's queues
         __UpperCamelCase	:	Dict		    =  number_of_queues
         # time slice of queues that round robin algorithm applied
         __UpperCamelCase	:	str		    =  time_slices
         # unfinished process is in this ready_queue
         __UpperCamelCase	:	List[str]		    =  queue
         # current time
         __UpperCamelCase	:	Union[str, Any]		    =  current_time
         # finished process is in this sequence queue
         __UpperCamelCase	:	deque[Process]		    =  deque()







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[Any]		    =  []
         for i in range(len(self.finish_queue    )    ):
             sequence.append(self.finish_queue[i].process_name    )
         return sequence







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	Any		    =  []
         for i in range(len(_lowerCamelCase    )    ):
             waiting_times.append(queue[i].waiting_time    )
         return waiting_times







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	int		    =  []
         for i in range(len(_lowerCamelCase    )    ):
             turnaround_times.append(queue[i].turnaround_time    )
         return turnaround_times







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	str		    =  []
         for i in range(len(_lowerCamelCase    )    ):
             completion_times.append(queue[i].stop_time    )
         return completion_times







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         return [q.burst_time for q in queue]







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         process.waiting_time += self.current_time - process.stop_time
         return process.waiting_time







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	deque[Process]		    =  deque()  # sequence deque of finished process
         while len(_lowerCamelCase    ) != 0:
             __UpperCamelCase	:	Any		    =  ready_queue.popleft()  # current process

             # if process's arrival time is later than current time, update current time
             if self.current_time < cp.arrival_time:
                 self.current_time += cp.arrival_time

             # update waiting time of current process
             self.update_waiting_time(_lowerCamelCase    )
             # update current time
             self.current_time += cp.burst_time
             # finish the process and set the process's burst-time 0
             __UpperCamelCase	:	str		    =  0
             # set the process's turnaround time because it is finished
             __UpperCamelCase	:	Dict		    =  self.current_time - cp.arrival_time
             # set the completion time
             __UpperCamelCase	:	Optional[int]		    =  self.current_time
             # add the process to queue that has finished queue
             finished.append(_lowerCamelCase    )

         self.finish_queue.extend(_lowerCamelCase    )  # add finished process to finish queue
         # FCFS will finish all remaining processes
         return finished







     def lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	deque[Process]		    =  deque()  # sequence deque of terminated process
         # just for 1 cycle and unfinished processes will go back to queue
         for _ in range(len(_lowerCamelCase    )    ):
             __UpperCamelCase	:	Union[str, Any]		    =  ready_queue.popleft()  # current process

             # if process's arrival time is later than current time, update current time
             if self.current_time < cp.arrival_time:
                 self.current_time += cp.arrival_time

             # update waiting time of unfinished processes
             self.update_waiting_time(_lowerCamelCase    )
             # if the burst time of process is bigger than time-slice
             if cp.burst_time > time_slice:
                 # use CPU for only time-slice
                 self.current_time += time_slice
                 # update remaining burst time
                 cp.burst_time -= time_slice
                 # update end point time
                 __UpperCamelCase	:	Any		    =  self.current_time
                 # locate the process behind the queue because it is not finished
                 ready_queue.append(_lowerCamelCase    )
             else:
                 # use CPU for remaining burst time
                 self.current_time += cp.burst_time
                 # set burst time 0 because the process is finished
                 __UpperCamelCase	:	str		    =  0
                 # set the finish time
                 __UpperCamelCase	:	Optional[Any]		    =  self.current_time
                 # update the process' turnaround time because it is finished
                 __UpperCamelCase	:	int		    =  self.current_time - cp.arrival_time
                 # add the process to queue that has finished queue
                 finished.append(_lowerCamelCase    )

         self.finish_queue.extend(_lowerCamelCase    )  # add finished process to finish queue
         # return finished processes queue and remaining processes queue
         return finished, ready_queue







     def lowerCAmelCase     (		self    ):

         #  all queues except last one have round_robin algorithm
         for i in range(self.number_of_queues - 1    ):
             __UpperCamelCase    ,					__UpperCamelCase	:	Optional[Any]		    =  self.round_robin(
                 self.ready_queue     ,			self.time_slices[i]    )
         #  the last queue has first_come_first_served algorithm
         self.first_come_first_served(self.ready_queue    )

         return self.finish_queue


if __name__ == "__main__":
  import doctest

  a=  Process('''P1''', 0, 5_3)
  a=  Process('''P2''', 0, 1_7)
  a=  Process('''P3''', 0, 6_8)
  a=  Process('''P4''', 0, 2_4)
  a=  3
  a=  [1_7, 2_5]
  a=  deque([Pa, Pa, Pa, Pa])

  if len(time_slices) != number_of_queues - 1:
    raise SystemExit(0)

  doctest.testmod(extraglobs={'''queue''': deque([Pa, Pa, Pa, Pa])})

  a=  Process('''P1''', 0, 5_3)
  a=  Process('''P2''', 0, 1_7)
  a=  Process('''P3''', 0, 6_8)
  a=  Process('''P4''', 0, 2_4)
  a=  3
  a=  [1_7, 2_5]
  a=  deque([Pa, Pa, Pa, Pa])
  a=  MLFQ(number_of_queues, time_slices, queue, 0)
  a=  mlfq.multi_level_feedback_queue()

  # print total waiting times of processes(P1, P2, P3, P4)
  print(
      F"""waiting time:\
        \t\t\t{MLFQ.calculate_waiting_time(mlfq, [Pa, Pa, Pa, Pa])}"""
  )
  # print completion times of processes(P1, P2, P3, P4)
  print(
      F"""completion time:\
        \t\t{MLFQ.calculate_completion_time(mlfq, [Pa, Pa, Pa, Pa])}"""
  )
  # print total turnaround times of processes(P1, P2, P3, P4)
  print(
      F"""turnaround time:\
        \t\t{MLFQ.calculate_turnaround_time(mlfq, [Pa, Pa, Pa, Pa])}"""
  )
  # print sequence of finished processes
  print(
      F"""sequence of finished processes:\
        {mlfq.calculate_sequence_of_finish_queue()}"""
  )




'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


a=  {
    '''configuration_bridgetower''': [
        '''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BridgeTowerConfig''',
        '''BridgeTowerTextConfig''',
        '''BridgeTowerVisionConfig''',
    ],
    '''processing_bridgetower''': ['''BridgeTowerProcessor'''],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a=  ['''BridgeTowerImageProcessor''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a=  [
      '''BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''BridgeTowerForContrastiveLearning''',
      '''BridgeTowerForImageAndTextRetrieval''',
      '''BridgeTowerForMaskedLM''',
      '''BridgeTowerModel''',
      '''BridgeTowerPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_bridgetower import (
      BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      BridgeTowerConfig,
      BridgeTowerTextConfig,
      BridgeTowerVisionConfig,
  )
  from .processing_bridgetower import BridgeTowerProcessor

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_bridgetower import BridgeTowerImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_bridgetower import (
        BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST,
        BridgeTowerForContrastiveLearning,
        BridgeTowerForImageAndTextRetrieval,
        BridgeTowerForMaskedLM,
        BridgeTowerModel,
        BridgeTowerPreTrainedModel,
    )


else:
  import sys

  a=  _LazyModule(__name__, globals()['''__file__'''], _import_structure)



