



'''simple docstring'''

from collections import deque



class 		lowerCamelCase__      :




					'''simple docstring'''



					def __init__(  self				:	Any     ,  UpperCamelCase_				:	str     ,  UpperCamelCase_				:	int     ,  UpperCamelCase_				:	int					)  ->       None:



						'''simple docstring'''





						_lowercase					:       Dict       =		process_name  # process name
						_lowercase					:       Dict       =		arrival_time  # arrival time of the process
						# completion time of finished process or last interrupted time
						_lowercase					:       Optional[Any]       =		arrival_time
						_lowercase					:       int       =		burst_time  # remaining burst time
						_lowercase					:       Optional[Any]       =		0  # total time of the process wait in ready queue
						_lowercase					:       Dict       =		0  # time from arrival time to completion time






class 		lowerCamelCase__      :




					'''simple docstring'''



					def __init__(  self				:	List[str]     ,  UpperCamelCase_				:	int     ,  UpperCamelCase_				:	list[int]     ,  UpperCamelCase_				:	deque[Process]     ,  UpperCamelCase_				:	int     ,  )  ->       None:



						'''simple docstring'''





						_lowercase					:       List[str]       =		number_of_queues
						# time slice of queues that round robin algorithm applied
						_lowercase					:       Optional[Any]       =		time_slices
						# unfinished process is in this ready_queue
						_lowercase					:       List[str]       =		queue
						# current time
						_lowercase					:       List[Any]       =		current_time
						# finished process is in this sequence queue
						_lowercase					:       deque[Process]       =		deque()




					def 						__UpperCAmelCase     (  self				:	List[str]					)  ->       list[str]:



						'''simple docstring'''





						_lowercase					:       Tuple       =		[]
						for i in range(len(self.finish_queue					)					):
							sequence.append(self.finish_queue[i].process_name					)
						return sequence




					def 						__UpperCAmelCase     (  self				:	Any     ,  UpperCamelCase_				:	list[Process]					)  ->       list[int]:



						'''simple docstring'''





						_lowercase					:       Optional[int]       =		[]
						for i in range(len(UpperCamelCase_					)					):
							waiting_times.append(queue[i].waiting_time					)
						return waiting_times




					def 						__UpperCAmelCase     (  self				:	List[Any]     ,  UpperCamelCase_				:	list[Process]					)  ->       list[int]:



						'''simple docstring'''





						_lowercase					:       Optional[Any]       =		[]
						for i in range(len(UpperCamelCase_					)					):
							turnaround_times.append(queue[i].turnaround_time					)
						return turnaround_times




					def 						__UpperCAmelCase     (  self				:	Optional[Any]     ,  UpperCamelCase_				:	list[Process]					)  ->       list[int]:



						'''simple docstring'''





						_lowercase					:       Optional[Any]       =		[]
						for i in range(len(UpperCamelCase_					)					):
							completion_times.append(queue[i].stop_time					)
						return completion_times




					def 						__UpperCAmelCase     (  self				:	Tuple     ,  UpperCamelCase_				:	deque[Process]					)  ->       list[int]:



						'''simple docstring'''





						return [q.burst_time for q in queue]




					def 						__UpperCAmelCase     (  self				:	Optional[Any]     ,  UpperCamelCase_				:	Process					)  ->       int:



						'''simple docstring'''





						process.waiting_time += self.current_time - process.stop_time
						return process.waiting_time




					def 						__UpperCAmelCase     (  self				:	List[Any]     ,  UpperCamelCase_				:	deque[Process]					)  ->       deque[Process]:



						'''simple docstring'''





						_lowercase					:       deque[Process]       =		deque()  # sequence deque of finished process
						while len(UpperCamelCase_					) != 0:
							_lowercase					:       Dict       =		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
							_lowercase					:       Any       =		0
							# set the process's turnaround time because it is finished
							_lowercase					:       Optional[Any]       =		self.current_time - cp.arrival_time
							# set the completion time
							_lowercase					:       Union[str, Any]       =		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 						__UpperCAmelCase     (  self				:	Optional[Any]     ,  UpperCamelCase_				:	deque[Process]     ,  UpperCamelCase_				:	int					)  ->       tuple[deque[Process], deque[Process]]:



						'''simple docstring'''





						_lowercase					:       deque[Process]       =		deque()  # sequence deque of terminated process
						# just for 1 cycle and unfinished processes will go back to queue
						for _ in range(len(UpperCamelCase_					)					):
							_lowercase					:       Any       =		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
								_lowercase					:       List[str]       =		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
								_lowercase					:       Dict       =		0
								# set the finish time
								_lowercase					:       Union[str, Any]       =		self.current_time
								# update the process' turnaround time because it is finished
								_lowercase					:       str       =		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 						__UpperCAmelCase     (  self				:	Optional[int]					)  ->       deque[Process]:



						'''simple docstring'''





						for i in range(self.number_of_queues - 1					):
							_lowercase					:       List[Any]       =		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				:    Any     						=				Process('''P1''', 0, 5_3)
		_A				:    List[Any]     						=				Process('''P2''', 0, 1_7)
		_A				:    Dict     						=				Process('''P3''', 0, 6_8)
		_A				:    str     						=				Process('''P4''', 0, 2_4)
		_A				:    List[str]     						=				3
		_A				:    Optional[Any]     						=				[1_7, 2_5]
		_A				:    Any     						=				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				:    List[Any]     						=				Process('''P1''', 0, 5_3)
		_A				:    Any     						=				Process('''P2''', 0, 1_7)
		_A				:    int     						=				Process('''P3''', 0, 6_8)
		_A				:    Any     						=				Process('''P4''', 0, 2_4)
		_A				:    List[Any]     						=				3
		_A				:    List[Any]     						=				[1_7, 2_5]
		_A				:    List[str]     						=				deque([Pa, Pa, Pa, Pa])
		_A				:    Union[str, Any]     						=				MLFQ(number_of_queues, time_slices, queue, 0)
		_A				:    str     						=				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 unittest

from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow


if is_flax_available():
		import jax.numpy as jnp

		from transformers import FlaxXLMRobertaModel



@require_sentencepiece
@require_tokenizers
@require_flax
class 		lowerCamelCase__      (						unittest.TestCase     ):




					'''simple docstring'''



					@slow
					def 						__UpperCAmelCase     (  self				:	int					)  ->       Union[str, Any]:



						'''simple docstring'''





						_lowercase					:       List[Any]       =		FlaxXLMRobertaModel.from_pretrained('xlm-roberta-base'					)
						_lowercase					:       str       =		AutoTokenizer.from_pretrained('xlm-roberta-base'					)
						_lowercase					:       List[Any]       =		'The dog is cute and lives in the garden house'
						_lowercase					:       Optional[int]       =		jnp.array([tokenizer.encode(UpperCamelCase_					)]					)

						_lowercase					:       int       =		(1, 12, 768)  # batch_size, sequence_length, embedding_vector_dim
						_lowercase					:       Tuple       =		jnp.array(
						    [[-0.01_01, 0.12_18, -0.08_03, 0.08_01, 0.13_27, 0.07_76, -0.12_15, 0.23_83, 0.33_38, 0.31_06, 0.03_00, 0.02_52]]					)

						_lowercase					:       List[str]       =		model(UpperCamelCase_					)['last_hidden_state']
						self.assertEqual(output.shape     ,  UpperCamelCase_					)
						# compare the actual values for a slice of last dim
						self.assertTrue(jnp.allclose(output[:, :, -1]     ,  UpperCamelCase_     ,  atol=1E-3					)					)
