




import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE:     Tuple									= get_tests_dir('''fixtures/test_sentencepiece.model''')

if is_torch_available():
						from transformers.models.mbart.modeling_mbart import shift_tokens_right

SCREAMING_SNAKE_CASE:     str									= 2_5_0_0_0_4
SCREAMING_SNAKE_CASE:     Any									= 2_5_0_0_2_0



@require_sentencepiece
@require_tokenizers
class    lowercase_		(SCREAMING_SNAKE_CASE__							,	unittest.TestCase ):
						lowerCAmelCase__			      =MBartaaTokenizer
						lowerCAmelCase__			      =MBartaaTokenizerFast
						lowerCAmelCase__			      =True
						lowerCAmelCase__			      =True



						def 	__a					(			self	:   List[str]  ):

								"""simple docstring"""

								super().setUp()

								# We have a SentencePiece fixture for testing
								SCREAMING_SNAKE_CASE_					      =							MBartaaTokenizer(snake_case__					,							src_lang='en_XX'					,							tgt_lang='ro_RO'					,							keep_accents=snake_case__  )
								tokenizer.save_pretrained(self.tmpdirname  )



						def 	__a					(			self	:   Optional[int]  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							'<s>'
								SCREAMING_SNAKE_CASE_					      =							0

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



						def 	__a					(			self	:   int  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							list(self.get_tokenizer().get_vocab().keys()  )

								self.assertEqual(vocab_keys[0]					,							'<s>'  )
								self.assertEqual(vocab_keys[1]					,							'<pad>'  )
								self.assertEqual(vocab_keys[-1]					,							'<mask>'  )
								self.assertEqual(len(snake_case__  )					,							10_54  )



						def 	__a					(			self	:   Tuple  ):

								"""simple docstring"""

								self.assertEqual(self.get_tokenizer().vocab_size					,							10_54  )



						def 	__a					(			self	:   str  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							MBartaaTokenizer(snake_case__					,							src_lang='en_XX'					,							tgt_lang='ro_RO'					,							keep_accents=snake_case__  )

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

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(snake_case__  )					,							[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]					,							)

								SCREAMING_SNAKE_CASE_					      =							tokenizer.tokenize('I was born in 92000, and this is falsé.'  )
								self.assertListEqual(
								    snake_case__					,							[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', '.']					,							)
								SCREAMING_SNAKE_CASE_					      =							tokenizer.convert_tokens_to_ids(snake_case__  )
								self.assertListEqual(
								    snake_case__					,							[
								        value + tokenizer.fairseq_offset
								        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
								    ]					,							)

								SCREAMING_SNAKE_CASE_					      =							tokenizer.convert_ids_to_tokens(snake_case__  )
								self.assertListEqual(
								    snake_case__					,							[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 	__a					(			self	:   Union[str, Any]  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							{'input_ids': [[25_00_04, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [25_00_04, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 7, 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], [25_00_04, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 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]], '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, 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, 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=snake_case__					,							model_name='facebook/mbart-large-50'					,							revision='d3913889c59cd5c9e456b269c376325eabad57e2'					,							)






						def 	__a					(			self	:   Optional[int]  ):

								"""simple docstring"""

								if not self.test_slow_tokenizer:
										# as we don't have a slow version, we can't compare the outputs between slow and fast versions
										return

								SCREAMING_SNAKE_CASE_					      =							(self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart50', {})
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
										with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
												SCREAMING_SNAKE_CASE_					      =							self.rust_tokenizer_class.from_pretrained(snake_case__					,							**snake_case__  )
												SCREAMING_SNAKE_CASE_					      =							self.tokenizer_class.from_pretrained(snake_case__					,							**snake_case__  )

												SCREAMING_SNAKE_CASE_					      =							tempfile.mkdtemp()

												SCREAMING_SNAKE_CASE_					      =							tokenizer_r.save_pretrained(snake_case__  )
												SCREAMING_SNAKE_CASE_					      =							tokenizer_p.save_pretrained(snake_case__  )

												# Checks it save with the same files + the tokenizer.json file for the fast one
												self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files  )  )
												SCREAMING_SNAKE_CASE_					      =							tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f  )
												self.assertSequenceEqual(snake_case__					,							snake_case__  )

												# Checks everything loads correctly in the same way
												SCREAMING_SNAKE_CASE_					      =							tokenizer_r.from_pretrained(snake_case__  )
												SCREAMING_SNAKE_CASE_					      =							tokenizer_p.from_pretrained(snake_case__  )

												# Check special tokens are set accordingly on Rust and Python
												for key in tokenizer_pp.special_tokens_map:
														self.assertTrue(hasattr(snake_case__					,							snake_case__  )  )
														# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
														# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

												shutil.rmtree(snake_case__  )

												# Save tokenizer rust, legacy_format=True
												SCREAMING_SNAKE_CASE_					      =							tempfile.mkdtemp()

												SCREAMING_SNAKE_CASE_					      =							tokenizer_r.save_pretrained(snake_case__					,							legacy_format=snake_case__  )
												SCREAMING_SNAKE_CASE_					      =							tokenizer_p.save_pretrained(snake_case__  )

												# Checks it save with the same files
												self.assertSequenceEqual(snake_case__					,							snake_case__  )

												# Checks everything loads correctly in the same way
												SCREAMING_SNAKE_CASE_					      =							tokenizer_r.from_pretrained(snake_case__  )
												SCREAMING_SNAKE_CASE_					      =							tokenizer_p.from_pretrained(snake_case__  )

												# Check special tokens are set accordingly on Rust and Python
												for key in tokenizer_pp.special_tokens_map:
														self.assertTrue(hasattr(snake_case__					,							snake_case__  )  )

												shutil.rmtree(snake_case__  )

												# Save tokenizer rust, legacy_format=False
												SCREAMING_SNAKE_CASE_					      =							tempfile.mkdtemp()

												SCREAMING_SNAKE_CASE_					      =							tokenizer_r.save_pretrained(snake_case__					,							legacy_format=snake_case__  )
												SCREAMING_SNAKE_CASE_					      =							tokenizer_p.save_pretrained(snake_case__  )

												# Checks it saved the tokenizer.json file
												self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files  )  )

												# Checks everything loads correctly in the same way
												SCREAMING_SNAKE_CASE_					      =							tokenizer_r.from_pretrained(snake_case__  )
												SCREAMING_SNAKE_CASE_					      =							tokenizer_p.from_pretrained(snake_case__  )

												# Check special tokens are set accordingly on Rust and Python
												for key in tokenizer_pp.special_tokens_map:
														self.assertTrue(hasattr(snake_case__					,							snake_case__  )  )

												shutil.rmtree(snake_case__  )



@require_torch
@require_sentencepiece
@require_tokenizers
class    lowercase_		(unittest.TestCase ):
						lowerCAmelCase__			      ="facebook/mbart-large-50-one-to-many-mmt"
						lowerCAmelCase__			      =[
						    " UN Chief Says There Is No Military Solution in Syria",
						    " Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.",
						]
						lowerCAmelCase__			      =[
						    "Şeful ONU declară că nu există o soluţie militară în Siria",
						    "Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"
						    " pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"
						    " face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.",
						]
						lowerCAmelCase__			      =[EN_CODE, 82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2]



						@classmethod
						def 	__a					(			cls	:   Any  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							MBartaaTokenizer.from_pretrained(
								    cls.checkpoint_name					,							src_lang='en_XX'					,							tgt_lang='ro_RO'  )
								SCREAMING_SNAKE_CASE_					      =							1
								return cls



						def 	__a					(			self	:   Dict  ):

								"""simple docstring"""

								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']					,							25_00_01  )
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']					,							25_00_04  )
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']					,							25_00_20  )
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']					,							25_00_38  )



						def 	__a					(			self	:   List[str]  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							self.tokenizer.batch_encode_plus(self.src_text  ).input_ids[0]
								self.assertListEqual(self.expected_src_tokens					,							snake_case__  )



						def 	__a					(			self	:   Optional[Any]  ):

								"""simple docstring"""

								self.assertIn(snake_case__					,							self.tokenizer.all_special_ids  )
								SCREAMING_SNAKE_CASE_					      =							[RO_CODE, 8_84, 90_19, 96, 9, 9_16, 8_67_92, 36, 1_87_43, 1_55_96, 5, 2]
								SCREAMING_SNAKE_CASE_					      =							self.tokenizer.decode(snake_case__					,							skip_special_tokens=snake_case__  )
								SCREAMING_SNAKE_CASE_					      =							self.tokenizer.decode(generated_ids[1:]					,							skip_special_tokens=snake_case__  )
								self.assertEqual(snake_case__					,							snake_case__  )
								self.assertNotIn(self.tokenizer.eos_token					,							snake_case__  )



						def 	__a					(			self	:   Any  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							['this is gunna be a long sentence ' * 20]
								assert isinstance(src_text[0]					,							snake_case__  )
								SCREAMING_SNAKE_CASE_					      =							10
								SCREAMING_SNAKE_CASE_					      =							self.tokenizer(snake_case__					,							max_length=snake_case__					,							truncation=snake_case__  ).input_ids[0]
								self.assertEqual(ids[0]					,							snake_case__  )
								self.assertEqual(ids[-1]					,							2  )
								self.assertEqual(len(snake_case__  )					,							snake_case__  )



						def 	__a					(			self	:   List[Any]  ):

								"""simple docstring"""

								self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']  )					,							[25_00_53, 25_00_01]  )



						def 	__a					(			self	:   List[Any]  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							tempfile.mkdtemp()
								SCREAMING_SNAKE_CASE_					      =							self.tokenizer.fairseq_tokens_to_ids
								self.tokenizer.save_pretrained(snake_case__  )
								SCREAMING_SNAKE_CASE_					      =							MBartaaTokenizer.from_pretrained(snake_case__  )
								self.assertDictEqual(new_tok.fairseq_tokens_to_ids					,							snake_case__  )



						@require_torch
						def 	__a					(			self	:   Dict  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							self.tokenizer(self.src_text					,							text_target=self.tgt_text					,							padding=snake_case__					,							return_tensors='pt'  )
								SCREAMING_SNAKE_CASE_					      =							shift_tokens_right(batch['labels']					,							self.tokenizer.pad_token_id  )

								# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
								assert batch.input_ids[1][0] == EN_CODE
								assert batch.input_ids[1][-1] == 2
								assert batch.labels[1][0] == RO_CODE
								assert batch.labels[1][-1] == 2
								assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]



						@require_torch
						def 	__a					(			self	:   Optional[Any]  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							self.tokenizer(
								    self.src_text					,							text_target=self.tgt_text					,							padding=snake_case__					,							truncation=snake_case__					,							max_length=len(self.expected_src_tokens  )					,							return_tensors='pt'					,							)
								SCREAMING_SNAKE_CASE_					      =							shift_tokens_right(batch['labels']					,							self.tokenizer.pad_token_id  )

								self.assertIsInstance(snake_case__					,							snake_case__  )

								self.assertEqual((2, 14)					,							batch.input_ids.shape  )
								self.assertEqual((2, 14)					,							batch.attention_mask.shape  )
								SCREAMING_SNAKE_CASE_					      =							batch.input_ids.tolist()[0]
								self.assertListEqual(self.expected_src_tokens					,							snake_case__  )
								self.assertEqual(2					,							batch.decoder_input_ids[0, 0]  )  # decoder_start_token_id
								# Test that special tokens are reset
								self.assertEqual(self.tokenizer.prefix_tokens					,							[EN_CODE]  )
								self.assertEqual(self.tokenizer.suffix_tokens					,							[self.tokenizer.eos_token_id]  )



						def 	__a					(			self	:   Any  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							self.tokenizer(self.src_text					,							padding=snake_case__					,							truncation=snake_case__					,							max_length=3					,							return_tensors='pt'  )
								SCREAMING_SNAKE_CASE_					      =							self.tokenizer(
								    text_target=self.tgt_text					,							padding=snake_case__					,							truncation=snake_case__					,							max_length=10					,							return_tensors='pt'  )
								SCREAMING_SNAKE_CASE_					      =							targets['input_ids']
								SCREAMING_SNAKE_CASE_					      =							shift_tokens_right(snake_case__					,							self.tokenizer.pad_token_id  )

								self.assertEqual(batch.input_ids.shape[1]					,							3  )
								self.assertEqual(batch.decoder_input_ids.shape[1]					,							10  )






						@require_torch
						def 	__a					(			self	:   List[str]  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							self.tokenizer._build_translation_inputs(
								    'A test'					,							return_tensors='pt'					,							src_lang='en_XX'					,							tgt_lang='ar_AR'  )

								self.assertEqual(
								    nested_simplify(snake_case__  )					,							{
								        # en_XX, A, test, EOS
								        'input_ids': [[25_00_04, 62, 30_34, 2]],
								        'attention_mask': [[1, 1, 1, 1]],
								        # ar_AR
								        'forced_bos_token_id': 25_00_01,
								    }					,							)





from __future__ import annotations

import math


def 					_a							(					lowerCAmelCase )->	bool:

		if 1 < number < 4:
				# 2 and 3 are primes
				return True
		elif number < 2 or number % 2 == 0 or number % 3 == 0:
				# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
				return False

		# All primes number are in format of 6k +/- 1
		for i in range(5    ,						int(math.sqrt(lowerCAmelCase ) + 1 )    ,						6 ):
				if number % i == 0 or number % (i + 2) == 0:
						return False
		return True


SCREAMING_SNAKE_CASE:     List[str]									= [num for num in range(3, 1_0_0_0_0_1, 2) if not is_prime(num)]


def 					_a							(					lowerCAmelCase )->	list[int]:
		if not isinstance(lowerCAmelCase    ,						lowerCAmelCase ):
				raise ValueError('n must be an integer' )
		if n <= 0:
				raise ValueError('n must be >= 0' )

		SCREAMING_SNAKE_CASE_					      =							[]
		for num in range(len(lowerCAmelCase ) ):
				SCREAMING_SNAKE_CASE_					      =							0
				while 2 * i * i <= odd_composites[num]:
						SCREAMING_SNAKE_CASE_					      =							odd_composites[num] - 2 * i * i
						if is_prime(lowerCAmelCase ):
								break
						i += 1
				else:
						list_nums.append(odd_composites[num] )
						if len(lowerCAmelCase ) == n:
								return list_nums

		return []


def 					_a							(					)->	int:
		return compute_nums(1 )[0]


if __name__ == "__main__":
						print(f"""{solution() = }""")