'''simple docstring'''


import unittest
from pathlib import Path
from shutil import copyfile

from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCAmelCase	:       Union[str, Any]						       =	get_tests_dir("fixtures/test_sentencepiece.model")

if is_sentencepiece_available():
		import sentencepiece as sp


__lowerCAmelCase	:       str						       =	5
__lowerCAmelCase	:       Union[str, Any]						       =	10






@require_sentencepiece
@require_tokenizers
class 						A   (   UpperCAmelCase       ,	unittest.TestCase   ):
							a_        =      SpeechaTextTokenizer
							a_        =      False
							a_        =      True





							def       snake_case__						(      self				:							Tuple	)							->	List[Any]:
								super().setUp()

								__UpperCAmelCase							=			sp.SentencePieceProcessor()
								spm_model.Load(__a	)
								__UpperCAmelCase							=			['''<s>''', '''<pad>''', '''</s>''', '''<unk>''']

								vocab += [spm_model.IdToPiece(id_	) for id_ in range(len(__a	)	)]
								__UpperCAmelCase							=			dict(zip(__a     ,		range(len(__a	)	)	)	)

								__UpperCAmelCase							=			Path(self.tmpdirname	)
								save_json(__a     ,		save_dir / VOCAB_FILES_NAMES['''vocab_file''']	)
								if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
									copyfile(__a     ,		save_dir / VOCAB_FILES_NAMES['''spm_file''']	)

								__UpperCAmelCase							=			SpeechaTextTokenizer.from_pretrained(self.tmpdirname	)
								tokenizer.save_pretrained(self.tmpdirname	)





							def       snake_case__						(      self				:							List[str]	)							->	Optional[int]:
								__UpperCAmelCase							=			'''<pad>'''
								__UpperCAmelCase							=			1

								self.assertEqual(self.get_tokenizer()._convert_token_to_id(__a	)     ,		__a	)
								self.assertEqual(self.get_tokenizer()._convert_id_to_token(__a	)     ,		__a	)





							def       snake_case__						(      self				:							List[Any]	)							->	Dict:
								__UpperCAmelCase							=			list(self.get_tokenizer().get_vocab().keys()	)

								self.assertEqual(vocab_keys[0]     ,		'''<s>'''	)
								self.assertEqual(vocab_keys[1]     ,		'''<pad>'''	)
								self.assertEqual(vocab_keys[-1]     ,		'''j'''	)
								self.assertEqual(len(__a	)     ,		1_0_0_1	)





							def       snake_case__						(      self				:							List[Any]	)							->	List[str]:
								self.assertEqual(self.get_tokenizer().vocab_size     ,		1_0_0_1	)





							def       snake_case__						(      self				:							Tuple	)							->	Optional[Any]:
								__UpperCAmelCase							=			SpeechaTextTokenizer.from_pretrained(self.tmpdirname	)

								__UpperCAmelCase							=			tokenizer.tokenize('''This is a test'''	)
								self.assertListEqual(__a     ,		['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']	)

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(__a	)     ,		[2_8_9, 5_0, 1_4, 1_7_4, 3_8_6]     ,		)

								__UpperCAmelCase							=			tokenizer.tokenize('''I was born in 92000, and this is falsé.'''	)
								self.assertListEqual(
								    __a     ,		[SPIECE_UNDERLINE + '''I''', SPIECE_UNDERLINE + '''was''', SPIECE_UNDERLINE + '''b''', '''or''', '''n''', SPIECE_UNDERLINE + '''in''', SPIECE_UNDERLINE + '''''', '''9''', '''2''', '''0''', '''0''', '''0''', ''',''', SPIECE_UNDERLINE + '''and''', SPIECE_UNDERLINE + '''this''', SPIECE_UNDERLINE + '''is''', SPIECE_UNDERLINE + '''f''', '''al''', '''s''', '''é''', '''.''']     ,		)
								__UpperCAmelCase							=			tokenizer.convert_tokens_to_ids(__a	)
								self.assertListEqual(__a     ,		[1_2, 2_5, 8_8, 5_9, 2_8, 2_3, 1_1, 4, 6_0_6, 3_5_1, 3_5_1, 3_5_1, 7, 1_6, 7_0, 5_0, 7_6, 8_4, 1_0, 4, 8]	)

								__UpperCAmelCase							=			tokenizer.convert_ids_to_tokens(__a	)
								self.assertListEqual(
								    __a     ,		[SPIECE_UNDERLINE + '''I''', SPIECE_UNDERLINE + '''was''', SPIECE_UNDERLINE + '''b''', '''or''', '''n''', SPIECE_UNDERLINE + '''in''', SPIECE_UNDERLINE + '''''', '''<unk>''', '''2''', '''0''', '''0''', '''0''', ''',''', SPIECE_UNDERLINE + '''and''', SPIECE_UNDERLINE + '''this''', SPIECE_UNDERLINE + '''is''', SPIECE_UNDERLINE + '''f''', '''al''', '''s''', '''<unk>''', '''.''']     ,		)






							@slow
							def       snake_case__						(      self				:							Tuple	)							->	Optional[int]:
								# fmt: off
								__UpperCAmelCase							=			{'''input_ids''': [[3_7_9_1, 7_9_7, 3_1, 1_1, 6_4, 7_9_7, 3_1, 2_4_2_9, 4_3_3, 1_2, 1_1_7_6, 1_2, 2_0, 7_8_6, 9_1_5, 1_4_2, 2_4_1_3, 2_4_0, 3_7, 3_2_3_8, 7_9_7, 3_1, 1_1, 3_5, 9_3, 9_1_5, 1_4_2, 2_4_1_3, 2_4_0, 3_7, 5_5_4_0, 5_6_7, 1_2_7_6, 9_3, 3_7, 6_1_0, 4_0, 6_2, 4_5_5, 6_5_7, 1_0_4_2, 1_2_3, 7_8_0, 1_7_7, 3_7, 3_0_9, 2_4_1, 1_2_9_8, 5_1_4, 2_0, 2_9_2, 2_7_3_7, 1_1_4, 2_4_6_9, 2_4_1, 8_5, 6_4, 3_0_2, 5_4_8, 5_2_8, 4_2_3, 4, 5_0_9, 4_0_6, 4_2_3, 3_7, 6_0_1, 4, 7_7_7, 3_0_2, 5_4_8, 5_2_8, 4_2_3, 2_8_4, 4, 3_3_8_8, 5_1_1, 4_5_9, 4, 3_5_5_5, 4_0, 3_2_1, 3_0_2, 7_0_5, 4, 3_3_8_8, 5_1_1, 5_8_3, 3_2_6, 5, 5, 5, 6_2, 3_3_1_0, 5_6_0, 1_7_7, 2_6_8_0, 2_1_7, 1_5_0_8, 3_2, 3_1, 8_5_3, 4_1_8, 6_4, 5_8_3, 5_1_1, 1_6_0_5, 6_2, 3_5, 9_3, 5_6_0, 1_7_7, 2_6_8_0, 2_1_7, 1_5_0_8, 1_5_2_1, 6_4, 5_8_3, 5_1_1, 5_1_9, 6_2, 2_0, 1_5_1_5, 7_6_4, 2_0, 1_4_9, 2_6_1, 5_6_2_5, 7_9_7_2, 2_0, 5_5_4_0, 5_6_7, 1_2_7_6, 9_3, 3_9_2_5, 1_6_7_5, 1_1, 1_5, 8_0_2, 7_9_7_2, 5_7_6, 2_1_7, 1_5_0_8, 1_1, 3_5, 9_3, 1_2_5_3, 2_4_4_1, 1_5, 2_8_9, 6_5_2, 3_1, 4_1_6, 3_2_1, 3_8_4_2, 1_1_5, 4_0, 9_1_1, 8, 4_7_6, 6_1_9, 4, 3_8_0, 1_4_2, 4_2_3, 3_3_5, 2_4_0, 3_5, 9_3, 2_6_4, 8, 1_1, 3_3_5, 5_6_9, 4_2_0, 1_6_3, 5, 2], [2_6_0, 5_4_8, 5_2_8, 4_2_3, 2_0, 4_5_1, 2_0, 2_6_8_1, 1_1_5_3, 3_4_3_4, 2_0, 5_5_4_0, 3_7, 5_6_7, 1_2_6, 1_2_5_3, 2_4_4_1, 3_3_7_6, 4_4_9, 2_1_0, 4_3_1, 1_5_6_3, 1_7_7, 7_6_7, 5_5_4_0, 1_1, 1_2_0_3, 4_7_2, 1_1, 2_9_5_3, 6_8_5, 2_8_5, 3_6_4, 7_0_6, 1_1_5_3, 2_0, 6_7_9_9, 2_0, 2_8_6_9, 2_0, 4_4_6_4, 1_2_6, 4_0, 2_4_2_9, 2_0, 1_0_4_0, 8_6_6, 2_6_6_4, 4_1_8, 2_0, 3_1_8, 2_0, 1_7_2_6, 1_8_6, 2_0, 2_6_5, 5_2_2, 3_5, 9_3, 2_1_9_1, 4_6_3_4, 2_0, 1_0_4_0, 1_2, 6_7_9_9, 1_5, 2_2_8, 2_3_5_6, 1_4_2, 3_1, 1_1, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [2_5_7_5, 2_6_6_6, 6_8_4, 1_5_8_2, 1_1_7_6, 1_2, 6_2_7, 1_4_9, 6_1_9, 2_0, 4_9_0_2, 5_6_3, 1_1, 2_0, 1_4_9, 2_6_1, 3_4_2_0, 2_3_5_6, 1_7_4, 1_4_2, 4_7_1_4, 1_3_1, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
								# fmt: on

								self.tokenizer_integration_test_util(
								    expected_encoding=__a     ,		model_name='''facebook/s2t-small-mustc-en-de-st'''     ,		revision='''a14f04cf0776c02f62a8cb800cf7909e15ea23ad'''     ,		)






@require_sentencepiece
class 						A   (   unittest.TestCase   ):
							a_        =      '''valhalla/s2t_mustc_multilinguial_medium'''

							a_        =      '''C\'est trop cool'''
							a_        =      '''Esto es genial'''





							@classmethod
							def       snake_case__						(      cls				:							Any	)							->	List[Any]:
								__UpperCAmelCase							=			SpeechaTextTokenizer.from_pretrained(cls.checkpoint_name	)
								return cls





							def       snake_case__						(      self				:							List[Any]	)							->	List[str]:
								self.assertEqual(self.tokenizer.lang_code_to_id['''pt''']     ,		4	)
								self.assertEqual(self.tokenizer.lang_code_to_id['''ru''']     ,		6	)
								self.assertEqual(self.tokenizer.lang_code_to_id['''it''']     ,		9	)
								self.assertEqual(self.tokenizer.lang_code_to_id['''de''']     ,		1_1	)





							def       snake_case__						(      self				:							Tuple	)							->	Tuple:
								self.assertEqual(self.tokenizer.vocab_size     ,		1_0_0_0_0	)





							def       snake_case__						(      self				:							int	)							->	Dict:
								self.assertIn(__a     ,		self.tokenizer.all_special_ids	)
								__UpperCAmelCase							=			[ES_CODE, 4, 1_6_0_1, 4_7, 7_6_4_7, 2]
								__UpperCAmelCase							=			self.tokenizer.decode(__a     ,		skip_special_tokens=__a	)
								__UpperCAmelCase							=			self.tokenizer.decode(generated_ids[1:]     ,		skip_special_tokens=__a	)
								self.assertEqual(__a     ,		__a	)
								self.assertNotIn(self.tokenizer.eos_token     ,		__a	)





							def       snake_case__						(      self				:							Optional[Any]	)							->	Optional[int]:
								__UpperCAmelCase							=			'''fr'''
								__UpperCAmelCase							=			self.tokenizer(self.french_text	).input_ids
								self.assertEqual(encoded[0]     ,		__a	)
								self.assertEqual(encoded[-1]     ,		self.tokenizer.eos_token_id	)






							def       snake_case__						(      self				:							Any	)							->	Tuple:
								__UpperCAmelCase							=			'''fr'''
								self.assertListEqual(self.tokenizer.prefix_tokens     ,		[FR_CODE]	)

								__UpperCAmelCase							=			'''es'''
								self.assertListEqual(self.tokenizer.prefix_tokens     ,		[ES_CODE]	)

'''simple docstring'''


from __future__ import annotations

from statistics import mean





def       lowerCAmelCase					(		UpperCamelCase__				:   list[int]    ,					UpperCamelCase__				:   list[int]    ,					UpperCamelCase__				:   int       ):


	"""simple docstring"""
	__UpperCAmelCase							=			[0] * no_of_processes
	__UpperCAmelCase							=			[0] * no_of_processes

	# Initialize remaining_time to waiting_time.

	for i in range(UpperCamelCase__       ):
		__UpperCAmelCase							=			burst_time[i]
	__UpperCAmelCase							=			[]

	__UpperCAmelCase							=			0
	__UpperCAmelCase							=			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:
		__UpperCAmelCase							=			[]
		__UpperCAmelCase							=			-1

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

		if len(UpperCamelCase__       ) > 0:
			__UpperCAmelCase							=			ready_process[0]
			for i in ready_process:
				if remaining_time[i] < remaining_time[target_process]:
					__UpperCAmelCase							=			i
			total_time += burst_time[target_process]
			completed += 1
			__UpperCAmelCase							=			0
			__UpperCAmelCase							=			(
			    total_time - arrival_time[target_process] - burst_time[target_process]
			)
		else:
			total_time += 1

	return waiting_time





def       lowerCAmelCase					(		UpperCamelCase__				:   list[int]    ,					UpperCamelCase__				:   int    ,					UpperCamelCase__				:   list[int]       ):


	"""simple docstring"""
	__UpperCAmelCase							=			[0] * no_of_processes
	for i in range(UpperCamelCase__       ):
		__UpperCAmelCase							=			burst_time[i] + waiting_time[i]
	return turn_around_time


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

					__lowerCAmelCase	:       List[Any]						       =	4
					__lowerCAmelCase	:       List[Any]						       =	[2, 5, 3, 7]
					__lowerCAmelCase	:       Tuple						       =	[0, 0, 0, 0]
					__lowerCAmelCase	:       Optional[int]						       =	calculate_waitingtime(arrival_time, burst_time, no_of_processes)
					__lowerCAmelCase	:       Dict						       =	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}""")
