


'''simple docstring'''

from collections import deque


class 						__SCREAMING_SNAKE_CASE					:






     def __init__(			self     ,							__UpperCamelCase     ,							__UpperCamelCase     ,							__UpperCamelCase		)       ->    Dict:
          _a						=		process_name  # process name
          _a						=		arrival_time  # arrival time of the process
          # completion time of finished process or last interrupted time
          _a						=		arrival_time
          _a						=		burst_time  # remaining burst time
          _a						=		0  # total time of the process wait in ready queue
          _a						=		0  # time from arrival time to completion time







class 						__SCREAMING_SNAKE_CASE					:






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






     def  a_					(			self		)       ->    str:
          _a						=		[]
          for i in range(len(self.finish_queue		)		):
               sequence.append(self.finish_queue[i].process_name		)
          return sequence






     def  a_					(			self     ,							__UpperCamelCase		)       ->    Any:
          _a						=		[]
          for i in range(len(_UpperCAmelCase		)		):
               waiting_times.append(queue[i].waiting_time		)
          return waiting_times






     def  a_					(			self     ,							__UpperCamelCase		)       ->    int:
          _a						=		[]
          for i in range(len(_UpperCAmelCase		)		):
               turnaround_times.append(queue[i].turnaround_time		)
          return turnaround_times






     def  a_					(			self     ,							__UpperCamelCase		)       ->    Optional[Any]:
          _a						=		[]
          for i in range(len(_UpperCAmelCase		)		):
               completion_times.append(queue[i].stop_time		)
          return completion_times






     def  a_					(			self     ,							__UpperCamelCase		)       ->    str:
          return [q.burst_time for q in queue]






     def  a_					(			self     ,							__UpperCamelCase		)       ->    int:
          process.waiting_time += self.current_time - process.stop_time
          return process.waiting_time






     def  a_					(			self     ,							__UpperCamelCase		)       ->    Dict:
          _a						=		deque()  # sequence deque of finished process
          while len(_UpperCAmelCase		) != 0:
               _a						=		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(_UpperCAmelCase		)
               # update current time
               self.current_time += cp.burst_time
               # finish the process and set the process's burst-time 0
               _a						=		0
               # set the process's turnaround time because it is finished
               _a						=		self.current_time - cp.arrival_time
               # set the completion time
               _a						=		self.current_time
               # add the process to queue that has finished queue
               finished.append(_UpperCAmelCase		)

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






     def  a_					(			self     ,							__UpperCamelCase     ,							__UpperCamelCase		)       ->    str:
          _a						=		deque()  # sequence deque of terminated process
          # just for 1 cycle and unfinished processes will go back to queue
          for _ in range(len(_UpperCAmelCase		)		):
               _a						=		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(_UpperCAmelCase		)
               # 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
                    _a						=		self.current_time
                    # locate the process behind the queue because it is not finished
                    ready_queue.append(_UpperCAmelCase		)
               else:
                    # use CPU for remaining burst time
                    self.current_time += cp.burst_time
                    # set burst time 0 because the process is finished
                    _a						=		0
                    # set the finish time
                    _a						=		self.current_time
                    # update the process' turnaround time because it is finished
                    _a						=		self.current_time - cp.arrival_time
                    # add the process to queue that has finished queue
                    finished.append(_UpperCAmelCase		)

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






     def  a_					(			self		)       ->    Optional[Any]:

          #  all queues except last one have round_robin algorithm
          for i in range(self.number_of_queues - 1		):
               _a						=		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

   lowercase__				     =		Process("P1", 0, 53)
   lowercase__				     =		Process("P2", 0, 17)
   lowercase__				     =		Process("P3", 0, 68)
   lowercase__				     =		Process("P4", 0, 24)
   lowercase__				     =		3
   lowercase__				     =		[17, 25]
   lowercase__				     =		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])})

   lowercase__				     =		Process("P1", 0, 53)
   lowercase__				     =		Process("P2", 0, 17)
   lowercase__				     =		Process("P3", 0, 68)
   lowercase__				     =		Process("P4", 0, 24)
   lowercase__				     =		3
   lowercase__				     =		[17, 25]
   lowercase__				     =		deque([Pa, Pa, Pa, Pa])
   lowercase__				     =		MLFQ(number_of_queues, time_slices, queue, 0)
   lowercase__				     =		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'''

import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase__				     =		logging.get_logger(__name__)





class 						__SCREAMING_SNAKE_CASE					(      lowerCamelCase__ ):
     UpperCAmelCase 					=				'''encoder-decoder'''
     UpperCAmelCase 					=				True






     def __init__(			self     ,							**__UpperCamelCase		)       ->    List[Any]:
          super().__init__(**__UpperCamelCase		)
          assert (
              "encoder" in kwargs and "decoder" in kwargs
          ), "Config has to be initialized with encoder and decoder config"
          _a						=		kwargs.pop("encoder"		)
          _a						=		encoder_config.pop("model_type"		)
          _a						=		kwargs.pop("decoder"		)
          _a						=		decoder_config.pop("model_type"		)

          from ..auto.configuration_auto import AutoConfig

          _a						=		AutoConfig.for_model(__UpperCamelCase     ,							**__UpperCamelCase		)
          _a						=		AutoConfig.for_model(__UpperCamelCase     ,							**__UpperCamelCase		)
          _a						=		True






     @classmethod
     def  a_					(			cls     ,							__UpperCamelCase     ,							__UpperCamelCase     ,							**__UpperCamelCase		)       ->    PretrainedConfig:
          logger.info("Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"		)
          _a						=		True
          _a						=		True

          return cls(encoder=encoder_config.to_dict()     ,							decoder=decoder_config.to_dict()     ,							**__UpperCamelCase		)






     def  a_					(			self		)       ->    Any:
          _a						=		copy.deepcopy(self.__dict__		)
          _a						=		self.encoder.to_dict()
          _a						=		self.decoder.to_dict()
          _a						=		self.__class__.model_type
          return output

