



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


class 	SCREAMING_SNAKE_CASE__					:
	"""simple docstring"""


	def __init__(		self       , A       , A       , A      )			->				None:
				A:   Any								= process_name  # process name
				A:   List[Any]								= arrival_time  # arrival time of the process
				# completion time of finished process or last interrupted time
				A:   List[str]								= arrival_time
				A:   str								= burst_time  # remaining burst time
				A:   int								= 0  # total time of the process wait in ready queue
				A:   Any								= 0  # time from arrival time to completion time







class 	SCREAMING_SNAKE_CASE__					:
	"""simple docstring"""


	def __init__(		self       , A       , A       , A       , A       , )			->				None:
				# total number of mlfq's queues
				A:   Optional[int]								= number_of_queues
				# time slice of queues that round robin algorithm applied
				A:   Optional[int]								= time_slices
				# unfinished process is in this ready_queue
				A:   Union[str, Any]								= queue
				# current time
				A:   Union[str, Any]								= current_time
				# finished process is in this sequence queue
				A:   Optional[Any]								= deque()


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


	def   a__			(		self       , A      )			->				list[int]:
				A:   Any								= []
				for i in range(len(UpperCamelCase__      )      ):
							waiting_times.append(queue[i].waiting_time      )
				return waiting_times


	def   a__			(		self       , A      )			->				list[int]:
				A:   Any								= []
				for i in range(len(UpperCamelCase__      )      ):
							turnaround_times.append(queue[i].turnaround_time      )
				return turnaround_times


	def   a__			(		self       , A      )			->				list[int]:
				A:   Union[str, Any]								= []
				for i in range(len(UpperCamelCase__      )      ):
							completion_times.append(queue[i].stop_time      )
				return completion_times


	def   a__			(		self       , A      )			->				list[int]:
				return [q.burst_time for q in queue]


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


	def   a__			(		self       , A      )			->				deque[Process]:
				A:   str								= deque()  # sequence deque of finished process
				while len(UpperCamelCase__      ) != 0:
							A:   str								= 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:   int								= 0
							# set the process's turnaround time because it is finished
							A:   Optional[int]								= self.current_time - cp.arrival_time
							# set the completion time
							A:   str								= 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       , A       , A      )			->				tuple[deque[Process], deque[Process]]:
				A:   str								= deque()  # sequence deque of terminated process
				# just for 1 cycle and unfinished processes will go back to queue
				for _ in range(len(UpperCamelCase__      )      ):
							A:   Optional[int]								= 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:   Optional[int]								= 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:   Optional[int]								= 0
										# set the finish time
										A:   Dict								= self.current_time
										# update the process' turnaround time because it is finished
										A:   List[Any]								= 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      )			->				deque[Process]:

				#  all queues except last one have round_robin algorithm
				for i in range(self.number_of_queues - 1      ):
							A				,		A:   List[str]								= 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

					__SCREAMING_SNAKE_CASE			:   List[Any]							   =Process('P1', 0, 53)
					__SCREAMING_SNAKE_CASE			:   Any							   =Process('P2', 0, 17)
					__SCREAMING_SNAKE_CASE			:   Any							   =Process('P3', 0, 68)
					__SCREAMING_SNAKE_CASE			:   Union[str, Any]							   =Process('P4', 0, 24)
					__SCREAMING_SNAKE_CASE			:   Optional[Any]							   =3
					__SCREAMING_SNAKE_CASE			:   Dict							   =[17, 25]
					__SCREAMING_SNAKE_CASE			:   Dict							   =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])})

					__SCREAMING_SNAKE_CASE			:   Optional[int]							   =Process('P1', 0, 53)
					__SCREAMING_SNAKE_CASE			:   Tuple							   =Process('P2', 0, 17)
					__SCREAMING_SNAKE_CASE			:   Tuple							   =Process('P3', 0, 68)
					__SCREAMING_SNAKE_CASE			:   str							   =Process('P4', 0, 24)
					__SCREAMING_SNAKE_CASE			:   Union[str, Any]							   =3
					__SCREAMING_SNAKE_CASE			:   int							   =[17, 25]
					__SCREAMING_SNAKE_CASE			:   Optional[int]							   =deque([Pa, Pa, Pa, Pa])
					__SCREAMING_SNAKE_CASE			:   int							   =MLFQ(number_of_queues, time_slices, queue, 0)
					__SCREAMING_SNAKE_CASE			:   Tuple							   =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 . import (
    albert,
    align,
    altclip,
    audio_spectrogram_transformer,
    auto,
    autoformer,
    bark,
    bart,
    barthez,
    bartpho,
    beit,
    bert,
    bert_generation,
    bert_japanese,
    bertweet,
    big_bird,
    bigbird_pegasus,
    biogpt,
    bit,
    blenderbot,
    blenderbot_small,
    blip,
    blip_a,
    bloom,
    bridgetower,
    byta,
    camembert,
    canine,
    chinese_clip,
    clap,
    clip,
    clipseg,
    codegen,
    conditional_detr,
    convbert,
    convnext,
    convnextva,
    cpm,
    cpmant,
    ctrl,
    cvt,
    dataavec,
    deberta,
    deberta_va,
    decision_transformer,
    deformable_detr,
    deit,
    deprecated,
    deta,
    detr,
    dialogpt,
    dinat,
    distilbert,
    dit,
    donut,
    dpr,
    dpt,
    efficientformer,
    efficientnet,
    electra,
    encodec,
    encoder_decoder,
    ernie,
    ernie_m,
    esm,
    falcon,
    flaubert,
    flava,
    fnet,
    focalnet,
    fsmt,
    funnel,
    git,
    glpn,
    gpta,
    gpt_bigcode,
    gpt_neo,
    gpt_neox,
    gpt_neox_japanese,
    gpt_swa,
    gptj,
    gptsan_japanese,
    graphormer,
    groupvit,
    herbert,
    hubert,
    ibert,
    imagegpt,
    informer,
    instructblip,
    jukebox,
    layoutlm,
    layoutlmva,
    layoutlmva,
    layoutxlm,
    led,
    levit,
    lilt,
    llama,
    longformer,
    longta,
    luke,
    lxmert,
    mam_aaa,
    marian,
    markuplm,
    maskaformer,
    maskformer,
    mbart,
    mbartaa,
    mega,
    megatron_bert,
    megatron_gpta,
    mgp_str,
    mluke,
    mobilebert,
    mobilenet_va,
    mobilenet_va,
    mobilevit,
    mobilevitva,
    mpnet,
    mra,
    mta,
    musicgen,
    mvp,
    nat,
    nezha,
    nllb,
    nllb_moe,
    nystromformer,
    oneformer,
    open_llama,
    openai,
    opt,
    owlvit,
    pegasus,
    pegasus_x,
    perceiver,
    phobert,
    pixastruct,
    plbart,
    poolformer,
    prophetnet,
    qdqbert,
    rag,
    realm,
    reformer,
    regnet,
    rembert,
    resnet,
    roberta,
    roberta_prelayernorm,
    roc_bert,
    roformer,
    rwkv,
    sam,
    segformer,
    sew,
    sew_d,
    speech_encoder_decoder,
    speech_to_text,
    speech_to_text_a,
    speechta,
    splinter,
    squeezebert,
    swiftformer,
    swin,
    swinasr,
    swinva,
    switch_transformers,
    ta,
    table_transformer,
    tapas,
    time_series_transformer,
    timesformer,
    timm_backbone,
    transfo_xl,
    trocr,
    tvlt,
    umta,
    unispeech,
    unispeech_sat,
    upernet,
    videomae,
    vilt,
    vision_encoder_decoder,
    vision_text_dual_encoder,
    visual_bert,
    vit,
    vit_hybrid,
    vit_mae,
    vit_msn,
    vivit,
    wavaveca,
    wavaveca_conformer,
    wavaveca_phoneme,
    wavaveca_with_lm,
    wavlm,
    whisper,
    x_clip,
    xglm,
    xlm,
    xlm_prophetnet,
    xlm_roberta,
    xlm_roberta_xl,
    xlnet,
    xmod,
    yolos,
    yoso,
)



