






"""simple docstring"""







from __future__ import annotations

from statistics import mean





def 						lowercase__(A						)				->list[int]:




						"""simple docstring"""



						lowercase__				:      Optional[int]=       2
						lowercase__				:      Dict=       list(A						)
						lowercase__				:      Any=       [0] * len(A						)
						lowercase__				:      Optional[Any]=       0
						while True:
												lowercase__				:      str=       True
												for i, burst_time in enumerate(A						):
																		if rem_burst_times[i] > 0:
																								lowercase__				:      Union[str, Any]=       False
																								if rem_burst_times[i] > quantum:
																														t += quantum
																														rem_burst_times[i] -= quantum
																								else:
																														t += rem_burst_times[i]
																														lowercase__				:      int=       t - burst_time
																														lowercase__				:      Dict=       0
												if done is True:
																		return waiting_times





def 						lowercase__(A					,		A						)				->list[int]:




						"""simple docstring"""



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


if __name__ == "__main__":
			a :				Union[str, Any]      					=		[3, 5, 7]
			a :				Any      					=		calculate_waiting_times(burst_times)
			a :				Dict      					=		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}""")












'''simple docstring'''


import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
				from .tokenization_reformer import ReformerTokenizer
else:
				_snake_case      :      int   							=		None


_snake_case      :      Union[str, Any]   							=		logging.get_logger(__name__)


_snake_case      :      Union[str, Any]   							=		'▁'

_snake_case      :      Any   							=		{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

_snake_case      :      List[str]   							=		{
    'vocab_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
        )
    },
    'tokenizer_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'
        )
    },
}

_snake_case      :      Union[str, Any]   							=		{
    'google/reformer-crime-and-punishment': 524288,
}

class 			A    (		_a    ):
							lowercase_							=				VOCAB_FILES_NAMES
							lowercase_							=				PRETRAINED_VOCAB_FILES_MAP
							lowercase_							=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_							=				['input_ids', 'attention_mask']
							lowercase_							=				ReformerTokenizer







							def __init__(  self       :  Any							,			lowerCAmelCase_       :  int=None							,			lowerCAmelCase_       :  Optional[Any]=None							,			lowerCAmelCase_       :  List[str]="</s>"							,			lowerCAmelCase_       :  Any="<unk>"							,			lowerCAmelCase_       :  List[str]=[]							,			**lowerCAmelCase_       :  List[Any]							,			)			->							Dict:


														"""simple docstring"""


														super().__init__(
														    lowerCAmelCase_							,			tokenizer_file=lowerCAmelCase_							,			eos_token=lowerCAmelCase_							,			unk_token=lowerCAmelCase_							,			additional_special_tokens=lowerCAmelCase_							,			**lowerCAmelCase_							,			)

														_a	     =				vocab_file
														_a	     =				False if not self.vocab_file else True







							def    __lowerCAmelCase			(  self       :  List[Any]							,			lowerCAmelCase_       :  str							,			lowerCAmelCase_       :  Optional[str] = None					)			->							Tuple[str]:


														"""simple docstring"""


														if not self.can_save_slow_tokenizer:
																					raise ValueError(
																					    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
																					    '''tokenizer.'''					)

														if not os.path.isdir(lowerCAmelCase_					):
																					logger.error(F'Vocabulary path ({save_directory}) should be a directory'					)
																					return
														_a	     =				os.path.join(
														    lowerCAmelCase_							,			(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']					)

														if os.path.abspath(self.vocab_file					) != os.path.abspath(lowerCAmelCase_					):
																					copyfile(self.vocab_file							,			lowerCAmelCase_					)

														return (out_vocab_file,)

