
from collections import deque





class 	_lowerCAmelCase					:




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





class 	_lowerCAmelCase					:




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




				def      __a						(					self     )				->      Optional[Any]:
							lowerCAmelCase_						=	[]
							for i in range(len(self.finish_queue     )     ):
										sequence.append(self.finish_queue[i].process_name     )
							return sequence




				def      __a						(					self				,				_UpperCamelCase     )				->      int:
							lowerCAmelCase_						=	[]
							for i in range(len(_lowerCamelCase     )     ):
										waiting_times.append(queue[i].waiting_time     )
							return waiting_times




				def      __a						(					self				,				_UpperCamelCase     )				->      List[Any]:
							lowerCAmelCase_						=	[]
							for i in range(len(_lowerCamelCase     )     ):
										turnaround_times.append(queue[i].turnaround_time     )
							return turnaround_times




				def      __a						(					self				,				_UpperCamelCase     )				->      str:
							lowerCAmelCase_						=	[]
							for i in range(len(_lowerCamelCase     )     ):
										completion_times.append(queue[i].stop_time     )
							return completion_times




				def      __a						(					self				,				_UpperCamelCase     )				->      List[str]:
							return [q.burst_time for q in queue]




				def      __a						(					self				,				_UpperCamelCase     )				->      Any:
							process.waiting_time += self.current_time - process.stop_time
							return process.waiting_time




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

							#  all queues except last one have round_robin algorithm
							for i in range(self.number_of_queues - 1     ):
										lowerCAmelCase_	,  lowerCAmelCase_						=	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, 53)
			_A   =     Process("P2", 0, 17)
			_A   =     Process("P3", 0, 68)
			_A   =     Process("P4", 0, 24)
			_A   =     3
			_A   =     [17, 25]
			_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, 53)
			_A   =     Process("P2", 0, 17)
			_A   =     Process("P3", 0, 68)
			_A   =     Process("P4", 0, 24)
			_A   =     3
			_A   =     [17, 25]
			_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"""



import logging

from transformers.configuration_utils import PretrainedConfig


UpperCAmelCase__          = logging.getLogger(__name__)

class       lowerCAmelCase__				(						A_	):
     __a						=					"""masked_bert"""







     def __init__(							self			:			Union[str, Any]    ,      _lowerCamelCase			:			Any=30522    ,      _lowerCamelCase			:			Union[str, Any]=768    ,      _lowerCamelCase			:			Tuple=12    ,      _lowerCamelCase			:			Any=12    ,      _lowerCamelCase			:			str=3072    ,      _lowerCamelCase			:			str="gelu"    ,      _lowerCamelCase			:			int=0.1    ,      _lowerCamelCase			:			Optional[int]=0.1    ,      _lowerCamelCase			:			Dict=512    ,      _lowerCamelCase			:			List[Any]=2    ,      _lowerCamelCase			:			int=0.0_2    ,      _lowerCamelCase			:			Union[str, Any]=1e-12    ,      _lowerCamelCase			:			Union[str, Any]=0    ,      _lowerCamelCase			:			List[str]="topK"    ,      _lowerCamelCase			:			Optional[Any]="constant"    ,      _lowerCamelCase			:			Optional[Any]=0.0    ,      **_lowerCamelCase			:			str    ,      ):
       super().__init__(pad_token_id=_lowerCamelCase    ,      **_lowerCamelCase			)

       _snake_case					     =       vocab_size
       _snake_case					     =       hidden_size
       _snake_case					     =       num_hidden_layers
       _snake_case					     =       num_attention_heads
       _snake_case					     =       hidden_act
       _snake_case					     =       intermediate_size
       _snake_case					     =       hidden_dropout_prob
       _snake_case					     =       attention_probs_dropout_prob
       _snake_case					     =       max_position_embeddings
       _snake_case					     =       type_vocab_size
       _snake_case					     =       initializer_range
       _snake_case					     =       layer_norm_eps
       _snake_case					     =       pruning_method
       _snake_case					     =       mask_init
       _snake_case					     =       mask_scale



