






'''simple docstring'''



from collections import deque
class 							__SCREAMING_SNAKE_CASE       :




      def __init__(  self ,   lowerCamelCase ,   lowerCamelCase ,   lowerCamelCase      )							->None:



         '''simple docstring'''
         __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 ,   lowerCamelCase ,   lowerCamelCase ,   lowerCamelCase ,   lowerCamelCase ,   )							->None:



         '''simple docstring'''
         # 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  __UpperCamelCase							(  self      )							->list[str]:



         '''simple docstring'''
         __a				     =    []
         for i in range(len(self.finish_queue      )      ):
            sequence.append(self.finish_queue[i].process_name      )
         return sequence




      def  __UpperCamelCase							(  self ,   lowerCamelCase      )							->list[int]:



         '''simple docstring'''
         __a				     =    []
         for i in range(len(lowerCamelCase      )      ):
            waiting_times.append(queue[i].waiting_time      )
         return waiting_times




      def  __UpperCamelCase							(  self ,   lowerCamelCase      )							->list[int]:



         '''simple docstring'''
         __a				     =    []
         for i in range(len(lowerCamelCase      )      ):
            turnaround_times.append(queue[i].turnaround_time      )
         return turnaround_times




      def  __UpperCamelCase							(  self ,   lowerCamelCase      )							->list[int]:



         '''simple docstring'''
         __a				     =    []
         for i in range(len(lowerCamelCase      )      ):
            completion_times.append(queue[i].stop_time      )
         return completion_times




      def  __UpperCamelCase							(  self ,   lowerCamelCase      )							->list[int]:



         '''simple docstring'''
         return [q.burst_time for q in queue]




      def  __UpperCamelCase							(  self ,   lowerCamelCase      )							->int:



         '''simple docstring'''
         process.waiting_time += self.current_time - process.stop_time
         return process.waiting_time




      def  __UpperCamelCase							(  self ,   lowerCamelCase      )							->deque[Process]:



         '''simple docstring'''
         __a				     =    deque()  # sequence deque of finished process
         while len(lowerCamelCase      ) != 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(lowerCamelCase      )
            # 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(lowerCamelCase      )

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




      def  __UpperCamelCase							(  self ,   lowerCamelCase ,   lowerCamelCase      )							->tuple[deque[Process], deque[Process]]:



         '''simple docstring'''
         __a				     =    deque()  # sequence deque of terminated process
         # just for 1 cycle and unfinished processes will go back to queue
         for _ in range(len(lowerCamelCase      )      ):
            __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(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
               __a				     =    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
               __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(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  __UpperCamelCase							(  self      )							->deque[Process]:



         '''simple docstring'''

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

 __UpperCamelCase      :       str      			=      Process("""P1""", 0, 53)
 __UpperCamelCase      :       Union[str, Any]      			=      Process("""P2""", 0, 17)
 __UpperCamelCase      :       Union[str, Any]      			=      Process("""P3""", 0, 68)
 __UpperCamelCase      :       Optional[Any]      			=      Process("""P4""", 0, 24)
 __UpperCamelCase      :       int      			=      3
 __UpperCamelCase      :       Any      			=      [17, 25]
 __UpperCamelCase      :       Tuple      			=      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])})

 __UpperCamelCase      :       Optional[int]      			=      Process("""P1""", 0, 53)
 __UpperCamelCase      :       Union[str, Any]      			=      Process("""P2""", 0, 17)
 __UpperCamelCase      :       Union[str, Any]      			=      Process("""P3""", 0, 68)
 __UpperCamelCase      :       Optional[int]      			=      Process("""P4""", 0, 24)
 __UpperCamelCase      :       Optional[Any]      			=      3
 __UpperCamelCase      :       Union[str, Any]      			=      [17, 25]
 __UpperCamelCase      :       Optional[Any]      			=      deque([Pa, Pa, Pa, Pa])
 __UpperCamelCase      :       int      			=      MLFQ(number_of_queues, time_slices, queue, 0)
 __UpperCamelCase      :       Optional[Any]      			=      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


__UpperCamelCase      :       Tuple      			=      {
    """configuration_blip_2""": [
        """BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """Blip2Config""",
        """Blip2QFormerConfig""",
        """Blip2VisionConfig""",
    ],
    """processing_blip_2""": ["""Blip2Processor"""],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __UpperCamelCase      :       Optional[int]      			=      [
     """BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """Blip2Model""",
     """Blip2QFormerModel""",
     """Blip2PreTrainedModel""",
     """Blip2ForConditionalGeneration""",
     """Blip2VisionModel""",
 ]

if TYPE_CHECKING:
 from .configuration_blip_a import (
     BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP,
     BlipaConfig,
     BlipaQFormerConfig,
     BlipaVisionConfig,
 )
 from .processing_blip_a import BlipaProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_blip_a import (
      BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST,
      BlipaForConditionalGeneration,
      BlipaModel,
      BlipaPreTrainedModel,
      BlipaQFormerModel,
      BlipaVisionModel,
  )

else:
 import sys

 __UpperCamelCase      :       Dict      			=      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)