





"""simple docstring"""



from collections import deque






class 						__snake_case   :





 """simple docstring"""


 def __init__(       self   ,		__lowerCamelCase   ,		__lowerCamelCase   ,		__lowerCamelCase    ):



     '''simple docstring'''




     __A       :		Dict							=	process_name  # process name
     __A       :		Dict							=	arrival_time  # arrival time of the process
     # completion time of finished process or last interrupted time
     __A       :		Optional[Any]							=	arrival_time
     __A       :		List[Any]							=	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 						__snake_case   :





 """simple docstring"""


 def __init__(       self   ,		__lowerCamelCase   ,		__lowerCamelCase   ,		__lowerCamelCase   ,		__lowerCamelCase   ,		):



     '''simple docstring'''




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

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




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

 def    UpperCamelCase__(       self   ,		__lowerCamelCase    ):



     '''simple docstring'''




     __A       :		List[str]							=	[]
     for i in range(len(__lowerCamelCase    )    ):
         waiting_times.append(queue[i].waiting_time    )
     return waiting_times

 def    UpperCamelCase__(       self   ,		__lowerCamelCase    ):



     '''simple docstring'''




     __A       :		int							=	[]
     for i in range(len(__lowerCamelCase    )    ):
         turnaround_times.append(queue[i].turnaround_time    )
     return turnaround_times

 def    UpperCamelCase__(       self   ,		__lowerCamelCase    ):



     '''simple docstring'''




     __A       :		str							=	[]
     for i in range(len(__lowerCamelCase    )    ):
         completion_times.append(queue[i].stop_time    )
     return completion_times

 def    UpperCamelCase__(       self   ,		__lowerCamelCase    ):



     '''simple docstring'''




     return [q.burst_time for q in queue]

 def    UpperCamelCase__(       self   ,		__lowerCamelCase    ):



     '''simple docstring'''




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

 def    UpperCamelCase__(       self   ,		__lowerCamelCase    ):



     '''simple docstring'''




     __A       :		deque[Process]							=	deque()  # sequence deque of finished process
     while len(__lowerCamelCase    ) != 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(__lowerCamelCase    )
         # update current time
         self.current_time += cp.burst_time
         # finish the process and set the process's burst-time 0
         __A       :		Any							=	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       :		Any							=	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    UpperCamelCase__(       self   ,		__lowerCamelCase   ,		__lowerCamelCase    ):



     '''simple docstring'''




     __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(__lowerCamelCase    )    ):
         __A       :		Union[str, 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(__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
             __A       :		Union[str, Any]							=	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
             __A       :		List[Any]							=	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(__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    UpperCamelCase__(       self    ):



     '''simple docstring'''




     for i in range(self.number_of_queues - 1    ):
         __A					,			__A       :		Union[str, 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_					=     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 unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
       from transformers import AutoModelForSeqaSeqLM, AutoTokenizer






@require_torch
@require_sentencepiece
@require_tokenizers
class 						__snake_case   (						unittest.TestCase	):





 """simple docstring"""


 @slow
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		Any							=	AutoModelForSeqaSeqLM.from_pretrained('''google/mt5-small'''   ,		return_dict=__lowerCamelCase    ).to(__lowerCamelCase    )
     __A       :		Optional[Any]							=	AutoTokenizer.from_pretrained('''google/mt5-small'''    )

     __A       :		Optional[int]							=	tokenizer('''Hello there'''   ,		return_tensors='''pt'''    ).input_ids
     __A       :		str							=	tokenizer('''Hi I am'''   ,		return_tensors='''pt'''    ).input_ids

     __A       :		Any							=	model(input_ids.to(__lowerCamelCase    )   ,		labels=labels.to(__lowerCamelCase    )    ).loss
     __A       :		Tuple							=	-(labels.shape[-1] * loss.item())

     __A       :		int							=	-8_4.9_1_2_7
     self.assertTrue(abs(mtf_score - EXPECTED_SCORE    ) < 1e-4    )




