



"""simple docstring"""







from __future__ import annotations

import pandas as pd

def   lowerCAmelCase__			(     lowerCamelCase__				,      lowerCamelCase__				,      lowerCamelCase__			) ->							list[int]:
							A         =					[0] * no_of_processes
							A         =					[0] * no_of_processes
							# Copy the burst time into remaining_time[]
							for i in range(lowerCamelCase__			):
														A         =					burst_time[i]

							A         =					0
							A         =					0
							A         =					999999999
							A         =					0
							A         =					False

							# Process until all processes are completed
							while complete != no_of_processes:
														for j in range(lowerCamelCase__			):
																					if arrival_time[j] <= increment_time and remaining_time[j] > 0:
																												if remaining_time[j] < minm:
																																			A         =					remaining_time[j]
																																			A         =					j
																																			A         =					True

														if not check:
																					increment_time += 1
																					continue
														remaining_time[short] -= 1

														A         =					remaining_time[short]
														if minm == 0:
																					A         =					999999999

														if remaining_time[short] == 0:
																					complete += 1
																					A         =					False

																					# Find finish time of current process
																					A         =					increment_time + 1

																					# Calculate waiting time
																					A         =					finish_time - arrival_time[short]
																					A         =					finar - burst_time[short]

																					if waiting_time[short] < 0:
																												A         =					0

        # Increment time
														increment_time += 1
							return waiting_time

def   lowerCAmelCase__			(     lowerCamelCase__				,      lowerCamelCase__				,      lowerCamelCase__			) ->							list[int]:
							A         =					[0] * no_of_processes
							for i in range(lowerCamelCase__			):
														A         =					burst_time[i] + waiting_time[i]
							return turn_around_time

def   lowerCAmelCase__			(     lowerCamelCase__				,      lowerCamelCase__				,      lowerCamelCase__			) ->							None:
							A         =					0
							A         =					0
							for i in range(lowerCamelCase__			):
														A         =					total_waiting_time + waiting_time[i]
														A         =					total_turn_around_time + turn_around_time[i]
							print(f"""Average waiting time = {total_waiting_time / no_of_processes:.5f}"""			)
							print('Average turn around time ='				,      total_turn_around_time / no_of_processes			)


if __name__ == "__main__":
							print('Enter how many process you want to analyze')
							A    =			int(input())
							A    =			[0] * no_of_processes
							A    =			[0] * no_of_processes
							A    =			list(range(1, no_of_processes + 1))

							for i in range(no_of_processes):
														print('Enter the arrival time and burst time for process:--' + str(i + 1))
														A    ,				A    =			map(int, input().split())

							A    =			calculate_waitingtime(arrival_time, burst_time, no_of_processes)

							A    =			burst_time
							A    =			no_of_processes
							A    =			waiting_time
							A    =			calculate_turnaroundtime(bt, n, wt)

							calculate_average_times(waiting_time, turn_around_time, no_of_processes)

							A    =			pd.DataFrame(
							    list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
							    columns=[
							        'Process',
							        'BurstTime',
							        'ArrivalTime',
							        'WaitingTime',
							        'TurnAroundTime',
							    ],
							)

							# Printing the dataFrame
							pd.set_option('display.max_rows', fcfs.shape[0] + 1)
							print(fcfs)








"""simple docstring"""







import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class      UpperCAmelCase__		(      UpperCamelCase   ,unittest.TestCase     ):
		lowerCAmelCase_       :	Tuple 							=     LayoutLMTokenizer
		lowerCAmelCase_       :	Any 							=     LayoutLMTokenizerFast
		lowerCAmelCase_       :	Optional[int] 							=     True
		lowerCAmelCase_       :	List[Any] 							=     True



		def 					A_		( self  :    Optional[Any]				)			->						Optional[Any]:






									'''simple docstring'''

									super().setUp()

									A         =					[
									    '[UNK]',
									    '[CLS]',
									    '[SEP]',
									    'want',
									    '##want',
									    '##ed',
									    'wa',
									    'un',
									    'runn',
									    '##ing',
									    ',',
									    'low',
									    'lowest',
									]
									A         =					os.path.join(self.tmpdirname      ,							VOCAB_FILES_NAMES['vocab_file']				)
									with open(self.vocab_file      ,							'w'      ,							encoding='utf-8'				) as vocab_writer:
																vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]				)				)



		def 					A_		( self  :    str      ,							**snake_case  :    Tuple				)			->						Union[str, Any]:






									'''simple docstring'''

									return LayoutLMTokenizer.from_pretrained(self.tmpdirname      ,							**snake_case				)



		def 					A_		( self  :    List[str]      ,							snake_case  :    int				)			->						List[Any]:






									'''simple docstring'''

									A         =					'UNwant\u00E9d,running'
									A         =					'unwanted, running'
									return input_text, output_text



		def 					A_		( self  :    Tuple				)			->						Optional[int]:






									'''simple docstring'''

									A         =					self.tokenizer_class(self.vocab_file				)

									A         =					tokenizer.tokenize('UNwant\u00E9d,running'				)
									self.assertListEqual(snake_case      ,							['un', '##want', '##ed', ',', 'runn', '##ing']				)
									self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case				)      ,							[7, 4, 5, 10, 8, 9]				)



		def 					A_		( self  :    Any				)			->						List[Any]:






									'''simple docstring'''

									pass



