"""simple docstring"""
from collections import deque




class        __snake_case	:



      def __init__(						self   ,      lowercase   ,      lowercase   ,      lowercase)     ->      None:





        '''simple docstring'''





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







class        __snake_case	:



      def __init__(						self   ,      lowercase   ,      lowercase   ,      lowercase   ,      lowercase   ,      )     ->      None:





        '''simple docstring'''





        a__:					Union[str, Any]      							=     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__:					Dict      							=     current_time
        # finished process is in this sequence queue
        a__:					deque[Process]      							=     deque()



      def   lowerCamelCase_       (						self)     ->      list[str]:





        '''simple docstring'''





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



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      list[int]:





        '''simple docstring'''





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



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      list[int]:





        '''simple docstring'''





        a__:					Any      							=     []
        for i in range(len(lowercase)):
          turnaround_times.append(queue[i].turnaround_time)
        return turnaround_times



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      list[int]:





        '''simple docstring'''





        a__:					Optional[int]      							=     []
        for i in range(len(lowercase)):
          completion_times.append(queue[i].stop_time)
        return completion_times



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      list[int]:





        '''simple docstring'''





        return [q.burst_time for q in queue]



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      int:





        '''simple docstring'''





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



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      deque[Process]:





        '''simple docstring'''





        a__:					deque[Process]      							=     deque()  # sequence deque of finished process
        while len(lowercase) != 0:
          a__:					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(lowercase)
          # update current time
          self.current_time += cp.burst_time
          # finish the process and set the process's burst-time 0
          a__:					List[Any]      							=     0
          # set the process's turnaround time because it is finished
          a__:					List[Any]      							=     self.current_time - cp.arrival_time
          # set the completion time
          a__:					Optional[Any]      							=     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   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase)     ->      tuple[deque[Process], deque[Process]]:





        '''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(lowercase)):
          a__:					Optional[int]      							=     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__:					List[str]      							=     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__:					Optional[int]      							=     0
            # set the finish time
            a__:					int      							=     self.current_time
            # update the process' turnaround time because it is finished
            a__:					int      							=     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   lowerCamelCase_       (						self)     ->      deque[Process]:





        '''simple docstring'''





        for i in range(self.number_of_queues - 1):
          a__:					Optional[int]      							=     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"""
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer


lowercase__ 	=     {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

lowercase__ 	=     {
    'vocab_file': {
        'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/vocab.txt',
    },
    'tokenizer_file': {
        'unc-nlp/lxmert-base-uncased': (
            'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/tokenizer.json'
        ),
    },
}

lowercase__ 	=     {
    'unc-nlp/lxmert-base-uncased': 512,
}

lowercase__ 	=     {
    'unc-nlp/lxmert-base-uncased': {'do_lower_case': True},
}




class        __snake_case	(					__lowerCAmelCase    ):
      a__				=		VOCAB_FILES_NAMES
      a__				=		PRETRAINED_VOCAB_FILES_MAP
      a__				=		PRETRAINED_INIT_CONFIGURATION
      a__				=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a__				=		LxmertTokenizer



      def __init__(						self   ,      lowercase=None   ,      lowercase=None   ,      lowercase=True   ,      lowercase="[UNK]"   ,      lowercase="[SEP]"   ,      lowercase="[PAD]"   ,      lowercase="[CLS]"   ,      lowercase="[MASK]"   ,      lowercase=True   ,      lowercase=None   ,      **lowercase   ,      )     ->      Dict:





        '''simple docstring'''





        super().__init__(
            lowercase   ,      tokenizer_file=lowercase   ,      do_lower_case=lowercase   ,      unk_token=lowercase   ,      sep_token=lowercase   ,      pad_token=lowercase   ,      cls_token=lowercase   ,      mask_token=lowercase   ,      tokenize_chinese_chars=lowercase   ,      strip_accents=lowercase   ,      **lowercase   ,      )

        a__:					Dict      							=     json.loads(self.backend_tokenizer.normalizer.__getstate__())
        if (
            normalizer_state.get('lowercase'   ,      lowercase) != do_lower_case
            or normalizer_state.get('strip_accents'   ,      lowercase) != strip_accents
            or normalizer_state.get('handle_chinese_chars'   ,      lowercase) != tokenize_chinese_chars
        ):
          a__:					int      							=     getattr(lowercase   ,      normalizer_state.pop('type'))
          a__:					Dict      							=     do_lower_case
          a__:					Dict      							=     strip_accents
          a__:					Optional[int]      							=     tokenize_chinese_chars
          a__:					List[Any]      							=     normalizer_class(**lowercase)

        a__:					Optional[int]      							=     do_lower_case



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase=None)     ->      Tuple:





        '''simple docstring'''





        a__:					Optional[Any]      							=     [self.cls_token_id] + token_ids_a + [self.sep_token_id]

        if token_ids_a:
          output += token_ids_a + [self.sep_token_id]

        return output



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = None)     ->      List[int]:





        '''simple docstring'''





        a__:					List[Any]      							=     [self.sep_token_id]
        a__:					List[Any]      							=     [self.cls_token_id]
        if token_ids_a is None:
          return len(cls + token_ids_a + sep) * [0]
        return len(cls + token_ids_a + sep) * [0] + len(token_ids_a + sep) * [1]



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = None)     ->      Tuple[str]:





        '''simple docstring'''





        a__:					List[Any]      							=     self._tokenizer.model.save(lowercase   ,      name=lowercase)
        return tuple(lowercase)


