
import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin







class     lowercase		( SCREAMING_SNAKE_CASE__	,  unittest.TestCase		):
							lowercase_	:	List[str]	 =BioGptTokenizer
							lowercase_	:	Tuple	 =False




							def 			A__				(    self):
												super().setUp()

												# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
												lowercase						     =						[
												    '''l''',
												    '''o''',
												    '''w''',
												    '''e''',
												    '''r''',
												    '''s''',
												    '''t''',
												    '''i''',
												    '''d''',
												    '''n''',
												    '''w</w>''',
												    '''r</w>''',
												    '''t</w>''',
												    '''lo''',
												    '''low''',
												    '''er</w>''',
												    '''low</w>''',
												    '''lowest</w>''',
												    '''newer</w>''',
												    '''wider</w>''',
												    '''<unk>''',
												]
												lowercase						     =						dict(zip(A__       ,range(len(A__))))
												lowercase						     =						['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

												lowercase						     =						os.path.join(self.tmpdirname       ,VOCAB_FILES_NAMES['''vocab_file'''])
												lowercase						     =						os.path.join(self.tmpdirname       ,VOCAB_FILES_NAMES['''merges_file'''])
												with open(self.vocab_file       ,'''w''') as fp:
																	fp.write(json.dumps(A__))
												with open(self.merges_file       ,'''w''') as fp:
																	fp.write('''\n'''.join(A__))




							def 			A__				(    self       ,A__):
												lowercase						     =						'''lower newer'''
												lowercase						     =						'''lower newer'''
												return input_text, output_text




							def 			A__				(    self):
												lowercase						     =						BioGptTokenizer(self.vocab_file       ,self.merges_file)

												lowercase						     =						'''lower'''
												lowercase						     =						['''low''', '''er</w>''']
												lowercase						     =						tokenizer.tokenize(A__)
												self.assertListEqual(A__       ,A__)

												lowercase						     =						tokens + ['''<unk>''']
												lowercase						     =						[1_4, 1_5, 2_0]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(A__)       ,A__)





							@slow
							def 			A__				(    self):
												lowercase						     =						BioGptTokenizer.from_pretrained('''microsoft/biogpt''')

												lowercase						     =						tokenizer.encode('''sequence builders'''       ,add_special_tokens=A__)
												lowercase						     =						tokenizer.encode('''multi-sequence build'''       ,add_special_tokens=A__)

												lowercase						     =						tokenizer.build_inputs_with_special_tokens(A__)
												lowercase						     =						tokenizer.build_inputs_with_special_tokens(A__       ,A__)

												self.assertTrue(encoded_sentence == [2] + text)
												self.assertTrue(encoded_pair == [2] + text + [2] + text_a)




from statistics import mean

import numpy as np



def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						0
					# Number of processes finished
					lowercase						     =						0
					# Displays the finished process.
					# If it is 0, the performance is completed if it is 1, before the performance.
					lowercase						     =						[0] * no_of_process
					# List to include calculation results
					lowercase						     =						[0] * no_of_process

					# Sort by arrival time.
					lowercase						     =						[burst_time[i] for i in np.argsort(lowerCAmelCase__		)]
					lowercase						     =						[process_name[i] for i in np.argsort(lowerCAmelCase__		)]
					arrival_time.sort()

					while no_of_process > finished_process_count:
										lowercase						     =						0
										while finished_process[i] == 1:
															i += 1
										if current_time < arrival_time[i]:
															lowercase						     =						arrival_time[i]

										lowercase						     =						0
										# Index showing the location of the process being performed
										lowercase						     =						0
										# Saves the current response ratio.
										lowercase						     =						0
										for i in range(0			,      lowerCAmelCase__		):
															if finished_process[i] == 0 and arrival_time[i] <= current_time:
																				lowercase						     =						(burst_time[i] + (current_time - arrival_time[i])) / burst_time[
																				    i
																				]
															if response_ratio < temp:
																				lowercase						     =						temp
																				lowercase						     =						i

        # Calculate the turn around time
										lowercase						     =						current_time + burst_time[loc] - arrival_time[loc]
										current_time += burst_time[loc]
										# Indicates that the process has been performed.
										lowercase						     =						1
										# Increase finished_process_count by 1
										finished_process_count += 1

					return turn_around_time



def 	UpperCamelCase   (							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						[0] * no_of_process
					for i in range(0			,      lowerCAmelCase__		):
										lowercase						     =						turn_around_time[i] - burst_time[i]
					return waiting_time


if __name__ == "__main__":
							lowercase__		:Dict			  =   5
							lowercase__		:str			  =   ["A", "B", "C", "D", "E"]
							lowercase__		:Optional[int]			  =   [1, 2, 3, 4, 5]
							lowercase__		:List[Any]			  =   [1, 2, 3, 4, 5]

							lowercase__		:List[str]			  =   calculate_turn_around_time(
							    process_name, arrival_time, burst_time, no_of_process
							)
							lowercase__		:List[Any]			  =   calculate_waiting_time(
							    process_name, turn_around_time, burst_time, no_of_process
							)

							print("Process name \tArrival time \tBurst time \tTurn around time \tWaiting time")
							for i in range(0, no_of_process):
														print(
														    F'{process_name[i]}\t\t{arrival_time[i]}\t\t{burst_time[i]}\t\t'
														    F'{turn_around_time[i]}\t\t\t{waiting_time[i]}'
														)

							print(F'average waiting time : {mean(waiting_time):.5f}')
							print(F'average turn around time : {mean(turn_around_time):.5f}')




