





"""simple docstring"""






from collections import deque




class 				__lowercase			:







					'''simple docstring'''




					def __init__(						self	,			_UpperCAmelCase	,			_UpperCAmelCase	,			_UpperCAmelCase     ):
									__a :						int			       =  process_name  # process name
									__a :						str			       =  arrival_time  # arrival time of the process
									# completion time of finished process or last interrupted time
									__a :						List[Any]			       =  arrival_time
									__a :						Dict			       =  burst_time  # remaining burst time
									__a :						List[Any]			       =  0  # total time of the process wait in ready queue
									__a :						Any			       =  0  # time from arrival time to completion time






class 				__lowercase			:







					'''simple docstring'''




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







					def  _lowerCamelCase		(						self     ):
									__a :						List[Any]			       =  []
									for i in range(len(self.finish_queue     )     ):
													sequence.append(self.finish_queue[i].process_name     )
									return sequence







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase     ):
									__a :						Optional[Any]			       =  []
									for i in range(len(_UpperCAmelCase     )     ):
													waiting_times.append(queue[i].waiting_time     )
									return waiting_times







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase     ):
									__a :						Dict			       =  []
									for i in range(len(_UpperCAmelCase     )     ):
													turnaround_times.append(queue[i].turnaround_time     )
									return turnaround_times







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase     ):
									__a :						int			       =  []
									for i in range(len(_UpperCAmelCase     )     ):
													completion_times.append(queue[i].stop_time     )
									return completion_times







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase     ):
									return [q.burst_time for q in queue]







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase     ):
									process.waiting_time += self.current_time - process.stop_time
									return process.waiting_time







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase     ):
									__a :						deque[Process]			       =  deque()  # sequence deque of finished process
									while len(_UpperCAmelCase     ) != 0:
													__a :						List[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 :						str			       =  self.current_time - cp.arrival_time
													# set the completion time
													__a :						List[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  _lowerCamelCase		(						self	,			_UpperCAmelCase	,			_UpperCAmelCase     ):
									__a :						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     )     ):
													__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 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 :						Tuple			       =  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[Any]			       =  0
																	# set the finish time
																	__a :						Optional[int]			       =  self.current_time
																	# update the process' turnaround time because it is finished
																	__a :						Dict			       =  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  _lowerCamelCase		(						self     ):

									#  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

		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 json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 				__lowercase			(			_UpperCamelCase   ,      unittest.TestCase							):







					'''simple docstring'''




					__lowerCAmelCase  =  OpenAIGPTTokenizer
					__lowerCAmelCase  =  OpenAIGPTTokenizerFast
					__lowerCAmelCase  =  True
					__lowerCAmelCase  =  False







					def  _lowerCamelCase		(						self     ):
									super().setUp()

									# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
									__a :						List[str]			       =  [
									    '''l''',
									    '''o''',
									    '''w''',
									    '''e''',
									    '''r''',
									    '''s''',
									    '''t''',
									    '''i''',
									    '''d''',
									    '''n''',
									    '''w</w>''',
									    '''r</w>''',
									    '''t</w>''',
									    '''lo''',
									    '''low''',
									    '''er</w>''',
									    '''low</w>''',
									    '''lowest</w>''',
									    '''newer</w>''',
									    '''wider</w>''',
									    '''<unk>''',
									]
									__a :						str			       =  dict(zip(_UpperCAmelCase	,			range(len(_UpperCAmelCase     )     )     )     )
									__a :						List[Any]			       =  ['''#version: 0.2''', '''l o''', '''lo w''', '''e r</w>''', '''''']

									__a :						Union[str, Any]			       =  os.path.join(self.tmpdirname	,			VOCAB_FILES_NAMES['''vocab_file''']     )
									__a :						Dict			       =  os.path.join(self.tmpdirname	,			VOCAB_FILES_NAMES['''merges_file''']     )
									with open(self.vocab_file	,			'''w'''     ) as fp:
													fp.write(json.dumps(_UpperCAmelCase     )     )
									with open(self.merges_file	,			'''w'''     ) as fp:
													fp.write('''\n'''.join(_UpperCAmelCase     )     )







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase     ):
									return "lower newer", "lower newer"







					def  _lowerCamelCase		(						self     ):
									__a :						Tuple			       =  OpenAIGPTTokenizer(self.vocab_file	,			self.merges_file     )

									__a :						Tuple			       =  '''lower'''
									__a :						Union[str, Any]			       =  ['''low''', '''er</w>''']
									__a :						str			       =  tokenizer.tokenize(_UpperCAmelCase     )
									self.assertListEqual(_UpperCAmelCase	,			_UpperCAmelCase     )

									__a :						List[Any]			       =  tokens + ['''<unk>''']
									__a :						Tuple			       =  [14, 15, 20]
									self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase     )	,			_UpperCAmelCase     )







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase=15     ):
									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""     ):
																	__a :						Any			       =  self.rust_tokenizer_class.from_pretrained(_UpperCAmelCase	,			**_UpperCAmelCase     )

																	# Simple input
																	__a :						str			       =  '''This is a simple input'''
																	__a :						Dict			       =  ['''This is a simple input 1''', '''This is a simple input 2''']
																	__a :						List[Any]			       =  ('''This is a simple input''', '''This is a pair''')
																	__a :						Optional[Any]			       =  [
																	    ('''This is a simple input 1''', '''This is a simple input 2'''),
																	    ('''This is a simple pair 1''', '''This is a simple pair 2'''),
																	]

																	# Simple input tests
																	self.assertRaises(_UpperCAmelCase	,			tokenizer_r.encode	,			_UpperCAmelCase	,			max_length=_UpperCAmelCase	,			padding='''max_length'''     )

																	# Simple input
																	self.assertRaises(_UpperCAmelCase	,			tokenizer_r.encode_plus	,			_UpperCAmelCase	,			max_length=_UpperCAmelCase	,			padding='''max_length'''     )

																	# Simple input
																	self.assertRaises(
																	    _UpperCAmelCase	,			tokenizer_r.batch_encode_plus	,			_UpperCAmelCase	,			max_length=_UpperCAmelCase	,			padding='''max_length'''	,			)

																	# Pair input
																	self.assertRaises(_UpperCAmelCase	,			tokenizer_r.encode	,			_UpperCAmelCase	,			max_length=_UpperCAmelCase	,			padding='''max_length'''     )

																	# Pair input
																	self.assertRaises(_UpperCAmelCase	,			tokenizer_r.encode_plus	,			_UpperCAmelCase	,			max_length=_UpperCAmelCase	,			padding='''max_length'''     )

																	# Pair input
																	self.assertRaises(
																	    _UpperCAmelCase	,			tokenizer_r.batch_encode_plus	,			_UpperCAmelCase	,			max_length=_UpperCAmelCase	,			padding='''max_length'''	,			)







					def  _lowerCamelCase		(						self     ):
									pass






@require_ftfy
@require_spacy
@require_tokenizers
class 				__lowercase			(			_UpperCamelCase							):







					'''simple docstring'''




					pass