





"""simple docstring"""



import json
import os
import shutil
import tempfile
from unittest import TestCase

from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.configuration_dpr import DPRConfig
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
from transformers.utils import is_datasets_available, is_faiss_available, is_torch_available


if is_torch_available() and is_datasets_available() and is_faiss_available():
       from transformers.models.rag.configuration_rag import RagConfig
       from transformers.models.rag.tokenization_rag import RagTokenizer






@require_faiss
@require_torch
class 						__snake_case   (						lowercase_	):





 """simple docstring"""


 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		List[str]							=	tempfile.mkdtemp()
     __A       :		Optional[int]							=	8

     # DPR tok
     __A       :		int							=	[
         """[UNK]""",
         """[CLS]""",
         """[SEP]""",
         """[PAD]""",
         """[MASK]""",
         """want""",
         """##want""",
         """##ed""",
         """wa""",
         """un""",
         """runn""",
         """##ing""",
         """,""",
         """low""",
         """lowest""",
     ]
     __A       :		List[Any]							=	os.path.join(self.tmpdirname   ,		'''dpr_tokenizer'''    )
     os.makedirs(lowerCamelCase_   ,		exist_ok=lowerCamelCase_    )
     __A       :		str							=	os.path.join(lowerCamelCase_   ,		DPR_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]    )    )

     # BART tok
     __A       :		List[str]							=	[
         """l""",
         """o""",
         """w""",
         """e""",
         """r""",
         """s""",
         """t""",
         """i""",
         """d""",
         """n""",
         """\u0120""",
         """\u0120l""",
         """\u0120n""",
         """\u0120lo""",
         """\u0120low""",
         """er""",
         """\u0120lowest""",
         """\u0120newer""",
         """\u0120wider""",
         """<unk>""",
     ]
     __A       :		Tuple							=	dict(zip(lowerCamelCase_   ,		range(len(lowerCamelCase_    )    )    )    )
     __A       :		Optional[int]							=	["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
     __A       :		Optional[Any]							=	{"""unk_token""": """<unk>"""}

     __A       :		List[str]							=	os.path.join(self.tmpdirname   ,		'''bart_tokenizer'''    )
     os.makedirs(lowerCamelCase_   ,		exist_ok=lowerCamelCase_    )
     __A       :		Dict							=	os.path.join(lowerCamelCase_   ,		BART_VOCAB_FILES_NAMES['''vocab_file''']    )
     __A       :		Any							=	os.path.join(lowerCamelCase_   ,		BART_VOCAB_FILES_NAMES['''merges_file''']    )
     with open(self.vocab_file   ,		'''w'''   ,		encoding='''utf-8'''    ) as fp:
         fp.write(json.dumps(lowerCamelCase_    ) + '''\n'''    )
     with open(self.merges_file   ,		'''w'''   ,		encoding='''utf-8'''    ) as fp:
         fp.write('''\n'''.join(lowerCamelCase_    )    )

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     return DPRQuestionEncoderTokenizer.from_pretrained(os.path.join(self.tmpdirname   ,		'''dpr_tokenizer'''    )    )

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     return BartTokenizer.from_pretrained(os.path.join(self.tmpdirname   ,		'''bart_tokenizer'''    )    )

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     shutil.rmtree(self.tmpdirname    )

 @require_tokenizers
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		Tuple							=	os.path.join(self.tmpdirname   ,		'''rag_tokenizer'''    )
     __A       :		int							=	RagConfig(question_encoder=DPRConfig().to_dict()   ,		generator=BartConfig().to_dict()    )
     __A       :		Optional[Any]							=	RagTokenizer(question_encoder=self.get_dpr_tokenizer()   ,		generator=self.get_bart_tokenizer()    )
     rag_config.save_pretrained(lowerCamelCase_    )
     rag_tokenizer.save_pretrained(lowerCamelCase_    )
     __A       :		Optional[Any]							=	RagTokenizer.from_pretrained(lowerCamelCase_   ,		config=lowerCamelCase_    )
     self.assertIsInstance(new_rag_tokenizer.question_encoder   ,		lowerCamelCase_    )
     self.assertEqual(new_rag_tokenizer.question_encoder.get_vocab()   ,		rag_tokenizer.question_encoder.get_vocab()    )
     self.assertIsInstance(new_rag_tokenizer.generator   ,		lowerCamelCase_    )
     self.assertEqual(new_rag_tokenizer.generator.get_vocab()   ,		rag_tokenizer.generator.get_vocab()    )

 @slow
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		List[Any]							=	RagTokenizer.from_pretrained('''facebook/rag-token-nq'''    )
     __A       :		List[str]							=	[
         """who got the first nobel prize in physics""",
         """when is the next deadpool movie being released""",
         """which mode is used for short wave broadcast service""",
         """who is the owner of reading football club""",
         """when is the next scandal episode coming out""",
         """when is the last time the philadelphia won the superbowl""",
         """what is the most current adobe flash player version""",
         """how many episodes are there in dragon ball z""",
         """what is the first step in the evolution of the eye""",
         """where is gall bladder situated in human body""",
         """what is the main mineral in lithium batteries""",
         """who is the president of usa right now""",
         """where do the greasers live in the outsiders""",
         """panda is a national animal of which country""",
         """what is the name of manchester united stadium""",
     ]
     __A       :		Tuple							=	tokenizer(lowerCamelCase_    )
     self.assertIsNotNone(lowerCamelCase_    )







 @slow
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		int							=	RagTokenizer.from_pretrained('''facebook/rag-sequence-nq'''    )
     __A       :		List[str]							=	[
         """who got the first nobel prize in physics""",
         """when is the next deadpool movie being released""",
         """which mode is used for short wave broadcast service""",
         """who is the owner of reading football club""",
         """when is the next scandal episode coming out""",
         """when is the last time the philadelphia won the superbowl""",
         """what is the most current adobe flash player version""",
         """how many episodes are there in dragon ball z""",
         """what is the first step in the evolution of the eye""",
         """where is gall bladder situated in human body""",
         """what is the main mineral in lithium batteries""",
         """who is the president of usa right now""",
         """where do the greasers live in the outsiders""",
         """panda is a national animal of which country""",
         """what is the name of manchester united stadium""",
     ]
     __A       :		str							=	tokenizer(lowerCamelCase_    )
     self.assertIsNotNone(lowerCamelCase_    )











'''simple docstring'''




from __future__ import annotations

from statistics import mean



def 		__A		(  lowerCamelCase_			,			lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				List[Any]		=			[0] * no_of_processes
		SCREAMING_SNAKE_CASE :				int		=			[0] * no_of_processes

		# Initialize remaining_time to waiting_time.

		for i in range(lowerCamelCase_	):
				SCREAMING_SNAKE_CASE :				Optional[int]		=			burst_time[i]
		SCREAMING_SNAKE_CASE :				list[int]		=			[]

		SCREAMING_SNAKE_CASE :				List[str]		=			0
		SCREAMING_SNAKE_CASE :				List[Any]		=			0

		# When processes are not completed,
		# A process whose arrival time has passed \
		# and has remaining execution time is put into the ready_process.
		# The shortest process in the ready_process, target_process is executed.

		while completed != no_of_processes:
				SCREAMING_SNAKE_CASE :				Optional[int]		=			[]
				SCREAMING_SNAKE_CASE :				Any		=			-1

				for i in range(lowerCamelCase_	):
						if (arrival_time[i] <= total_time) and (remaining_time[i] > 0):
								ready_process.append(lowerCamelCase_	)

				if len(lowerCamelCase_	) > 0:
						SCREAMING_SNAKE_CASE :				Union[str, Any]		=			ready_process[0]
						for i in ready_process:
								if remaining_time[i] < remaining_time[target_process]:
										SCREAMING_SNAKE_CASE :				Any		=			i
						total_time += burst_time[target_process]
						completed += 1
						SCREAMING_SNAKE_CASE :				Any		=			0
						SCREAMING_SNAKE_CASE :				Optional[int]		=			(
						    total_time - arrival_time[target_process] - burst_time[target_process]
						)
				else:
						total_time += 1

		return waiting_time



def 		__A		(  lowerCamelCase_			,			lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				Any		=			[0] * no_of_processes
		for i in range(lowerCamelCase_	):
				SCREAMING_SNAKE_CASE :				Union[str, Any]		=			burst_time[i] + waiting_time[i]
		return turn_around_time


if __name__ == "__main__":
							print("""[TEST CASE 01]""")

							__UpperCAmelCase            =       4
							__UpperCAmelCase            =       [2, 5, 3, 7]
							__UpperCAmelCase            =       [0, 0, 0, 0]
							__UpperCAmelCase            =       calculate_waitingtime(arrival_time, burst_time, no_of_processes)
							__UpperCAmelCase            =       calculate_turnaroundtime(
							    burst_time, no_of_processes, waiting_time
							)

							# Printing the Result
							print("""PID\tBurst Time\tArrival Time\tWaiting Time\tTurnaround Time""")
							for i, process_id in enumerate(list(range(1, 5))):
														print(
														    f'''{process_id}\t{burst_time[i]}\t\t\t{arrival_time[i]}\t\t\t\t'''
														    f'''{waiting_time[i]}\t\t\t\t{turn_around_time[i]}'''
														)
							print(f'''\nAverage waiting time = {mean(waiting_time):.5f}''')
							print(f'''Average turnaround time = {mean(turn_around_time):.5f}''')



