





from __future__ import annotations

from statistics import mean





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE							)       ->   list[int]:




    """simple docstring"""




    _A    =       2
    _A    =       list(_SCREAMING_SNAKE_CASE							)
    _A    =       [0] * len(_SCREAMING_SNAKE_CASE							)
    _A    =       0
    while True:
        _A    =       True
        for i, burst_time in enumerate(_SCREAMING_SNAKE_CASE							):
            if rem_burst_times[i] > 0:
                _A    =       False
                if rem_burst_times[i] > quantum:
                    t += quantum
                    rem_burst_times[i] -= quantum
                else:
                    t += rem_burst_times[i]
                    _A    =       t - burst_time
                    _A    =       0
        if done is True:
            return waiting_times





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   list[int]:




    """simple docstring"""




    return [burst + waiting for burst, waiting in zip(_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)]


if __name__ == "__main__":
 __A       : Optional[int]						    = [3, 5, 7]
 __A       : List[str]						    = calculate_waiting_times(burst_times)
 __A       : Union[str, Any]						    = calculate_turn_around_times(burst_times, waiting_times)
 print("Process ID \tBurst Time \tWaiting Time \tTurnaround Time")
 for i, burst_time in enumerate(burst_times):
  print(
      f"  {i + 1}\t\t  {burst_time}\t\t  {waiting_times[i]}\t\t  "
      f"{turn_around_times[i]}"
  )
 print(f"\nAverage waiting time = {mean(waiting_times):.5f}")
 print(f"Average turn around time = {mean(turn_around_times):.5f}")












from transformers import SqueezeBertTokenizer, SqueezeBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest







@require_tokenizers
class     lowerCamelCase(	__snake_case  ):
     '''simple docstring'''


     __magic_name__        = SqueezeBertTokenizer
     __magic_name__        = SqueezeBertTokenizerFast
     __magic_name__        = True




     def 					lowerCAmelCase__		(						self							,    **snake_case_       ):
         return SqueezeBertTokenizerFast.from_pretrained(self.tmpdirname							,    **snake_case_       )




     @slow
     def 					lowerCAmelCase__		(						self       ):
         _A    =       SqueezeBertTokenizer.from_pretrained('squeezebert/squeezebert-mnli-headless'       )

         _A    =       tokenizer.encode('sequence builders'							,    add_special_tokens=snake_case_       )
         _A    =       tokenizer.encode('multi-sequence build'							,    add_special_tokens=snake_case_       )

         _A    =       tokenizer.build_inputs_with_special_tokens(snake_case_       )
         _A    =       tokenizer.build_inputs_with_special_tokens(snake_case_							,    snake_case_       )

         assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
         assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
             tokenizer.sep_token_id
         ]





