
"""simple docstring"""


from collections import deque







class 				lowerCAmelCase_				:



						'''simple docstring'''


						def __init__( self     :      Optional[int]  ,A_     :      int  ,A_     :      Tuple  ,A_     :      Tuple      )     ->   None:
							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 				lowerCAmelCase_				:



						'''simple docstring'''


						def __init__( self     :      List[Any]  ,A_     :      Tuple  ,A_     :      List[Any]  ,A_     :      Optional[Any]  ,A_     :      Optional[Any]  ,)     ->   None:
							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 						_SCREAMING_SNAKE_CASE      ( self     :      Any      )     ->   list[str]:
							A						   =   []
							for i in range(len(self.finish_queue      )      ):
								sequence.append(self.finish_queue[i].process_name      )
							return sequence


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Union[str, Any]  ,A_     :      Optional[Any]      )     ->   list[int]:
							A						   =   []
							for i in range(len(lowercase__      )      ):
								waiting_times.append(queue[i].waiting_time      )
							return waiting_times


						def 						_SCREAMING_SNAKE_CASE      ( self     :      List[str]  ,A_     :      Any      )     ->   list[int]:
							A						   =   []
							for i in range(len(lowercase__      )      ):
								turnaround_times.append(queue[i].turnaround_time      )
							return turnaround_times


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Tuple  ,A_     :      Optional[Any]      )     ->   list[int]:
							A						   =   []
							for i in range(len(lowercase__      )      ):
								completion_times.append(queue[i].stop_time      )
							return completion_times


						def 						_SCREAMING_SNAKE_CASE      ( self     :      List[Any]  ,A_     :      str      )     ->   list[int]:
							return [q.burst_time for q in queue]


						def 						_SCREAMING_SNAKE_CASE      ( self     :      List[Any]  ,A_     :      Any      )     ->   int:
							process.waiting_time += self.current_time - process.stop_time
							return process.waiting_time


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Tuple  ,A_     :      Optional[int]      )     ->   deque[Process]:
							A						   =   deque()  # sequence deque of finished process
							while len(lowercase__      ) != 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(lowercase__      )
								# 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(lowercase__      )

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


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Any  ,A_     :      Any  ,A_     :      List[Any]      )     ->   tuple[deque[Process], deque[Process]]:
							A						   =   deque()  # sequence deque of terminated process
							# just for 1 cycle and unfinished processes will go back to queue
							for _ in range(len(lowercase__      )      ):
								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(lowercase__      )
								# 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(lowercase__      )
								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(lowercase__      )

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




						def 						_SCREAMING_SNAKE_CASE      ( self     :      Optional[int]      )     ->   deque[Process]:





							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"""


from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowercase							   =				logging.get_logger(__name__)

_lowercase							   =				{
    '''hustvl/yolos-small''': '''https://huggingface.co/hustvl/yolos-small/resolve/main/config.json''',
    # See all YOLOS models at https://huggingface.co/models?filter=yolos
}







class 				lowerCAmelCase_				(      _lowercase    ):



						'''simple docstring'''


						_lowerCamelCase:    List[str]      =    '''yolos'''


						def __init__( self     :      Dict  ,A_     :      Optional[Any]=768  ,A_     :      int=12  ,A_     :      List[str]=12  ,A_     :      str=3072  ,A_     :      Tuple="gelu"  ,A_     :      Dict=0.0  ,A_     :      List[Any]=0.0  ,A_     :      Any=0.02  ,A_     :      str=1e-12  ,A_     :      List[Any]=[512, 864]  ,A_     :      Union[str, Any]=16  ,A_     :      List[str]=3  ,A_     :      Optional[int]=True  ,A_     :      Tuple=100  ,A_     :      str=True  ,A_     :      Optional[Any]=False  ,A_     :      Any=1  ,A_     :      Optional[Any]=5  ,A_     :      Optional[Any]=2  ,A_     :      Optional[int]=5  ,A_     :      List[Any]=2  ,A_     :      Union[str, Any]=0.1  ,**A_     :      Tuple  ,)     ->   Any:
							super().__init__(**A_      )

							A						   =   hidden_size
							A						   =   num_hidden_layers
							A						   =   num_attention_heads
							A						   =   intermediate_size
							A						   =   hidden_act
							A						   =   hidden_dropout_prob
							A						   =   attention_probs_dropout_prob
							A						   =   initializer_range
							A						   =   layer_norm_eps
							A						   =   image_size
							A						   =   patch_size
							A						   =   num_channels
							A						   =   qkv_bias
							A						   =   num_detection_tokens
							A						   =   use_mid_position_embeddings
							A						   =   auxiliary_loss
							# Hungarian matcher
							A						   =   class_cost
							A						   =   bbox_cost
							A						   =   giou_cost
							# Loss coefficients
							A						   =   bbox_loss_coefficient
							A						   =   giou_loss_coefficient
							A						   =   eos_coefficient







class 				lowerCAmelCase_				(      _lowercase    ):



						'''simple docstring'''


						_lowerCamelCase:    Any      =    version.parse('''1.11'''    )


						@property
						def 						_SCREAMING_SNAKE_CASE      ( self     :      Optional[int]      )     ->   Mapping[str, Mapping[int, str]]:
							return OrderedDict(
							    [
							        ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
							    ]      )


						@property
						def 						_SCREAMING_SNAKE_CASE      ( self     :      Any      )     ->   float:
							return 1e-4




						@property
						def 						_SCREAMING_SNAKE_CASE      ( self     :      Tuple      )     ->   int:
							return 12