


"""simple docstring"""


import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class 			lowerCamelCase__						(   UpperCAmelCase_							,    unittest.TestCase			):
						lowerCAmelCase       =     RobertaTokenizer
						lowerCAmelCase       =     RobertaTokenizerFast
						lowerCAmelCase       =     True
						lowerCAmelCase       =     {"""cls_token""": """<s>"""}







						def __a						(							self   :    Union[str, Any]		):
								super().setUp()

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								A					       = [
								    'l',
								    'o',
								    'w',
								    'e',
								    'r',
								    's',
								    't',
								    'i',
								    'd',
								    'n',
								    '\u0120',
								    '\u0120l',
								    '\u0120n',
								    '\u0120lo',
								    '\u0120low',
								    'er',
								    '\u0120lowest',
								    '\u0120newer',
								    '\u0120wider',
								    '<unk>',
								]
								A					       = dict(zip(_lowercase			,			range(len(_lowercase		)		)		)		)
								A					       = ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
								A					       = {'unk_token': '<unk>'}

								A					       = os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['vocab_file']		)
								A					       = os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['merges_file']		)
								with open(self.vocab_file			,			'w'			,			encoding='utf-8'		) as fp:
										fp.write(json.dumps(_lowercase		) + '\n'		)
								with open(self.merges_file			,			'w'			,			encoding='utf-8'		) as fp:
										fp.write('\n'.join(_lowercase		)		)







						def __a						(							self   :    Union[str, Any]			,			**_lowercase   :    str		):
								kwargs.update(self.special_tokens_map		)
								return self.tokenizer_class.from_pretrained(self.tmpdirname			,			**_lowercase		)







						def __a						(							self   :    Union[str, Any]			,			**_lowercase   :    List[Any]		):
								kwargs.update(self.special_tokens_map		)
								return RobertaTokenizerFast.from_pretrained(self.tmpdirname			,			**_lowercase		)







						def __a						(							self   :    Dict			,			_lowercase   :    str		):
								A					       = 'lower newer'
								A					       = 'lower newer'
								return input_text, output_text







						def __a						(							self   :    Any		):
								A					       = self.tokenizer_class(self.vocab_file			,			self.merges_file			,			**self.special_tokens_map		)
								A					       = 'lower newer'
								A					       = ['l', 'o', 'w', 'er', '\u0120', 'n', 'e', 'w', 'er']
								A					       = tokenizer.tokenize(_lowercase		)  # , add_prefix_space=True)
								self.assertListEqual(_lowercase			,			_lowercase		)

								A					       = tokens + [tokenizer.unk_token]
								A					       = [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase		)			,			_lowercase		)







						def __a						(							self   :    Tuple		):
								A					       = self.get_tokenizer()

								self.assertListEqual(tokenizer.encode('Hello world!'			,			add_special_tokens=_lowercase		)			,			[0, 31_414, 232, 328, 2]		)
								self.assertListEqual(
								    tokenizer.encode('Hello world! cécé herlolip 418'			,			add_special_tokens=_lowercase		)			,			[0, 31_414, 232, 328, 740, 1_140, 12_695, 69, 46_078, 1_588, 2]			,			)







						@slow
						def __a						(							self   :    Union[str, Any]		):
								A					       = self.tokenizer_class.from_pretrained('roberta-base'		)

								A					       = tokenizer.encode('sequence builders'			,			add_special_tokens=_lowercase		)
								A					       = tokenizer.encode('multi-sequence build'			,			add_special_tokens=_lowercase		)

								A					       = tokenizer.encode(
								    'sequence builders'			,			add_special_tokens=_lowercase			,			add_prefix_space=_lowercase		)
								A					       = tokenizer.encode(
								    'sequence builders'			,			'multi-sequence build'			,			add_special_tokens=_lowercase			,			add_prefix_space=_lowercase		)

								A					       = tokenizer.build_inputs_with_special_tokens(_lowercase		)
								A					       = tokenizer.build_inputs_with_special_tokens(_lowercase			,			_lowercase		)

								assert encoded_sentence == encoded_text_from_decode
								assert encoded_pair == encoded_pair_from_decode







						def __a						(							self   :    List[str]		):
								A					       = self.get_tokenizer()

								A					       = 'Encode this sequence.'
								A					       = tokenizer.byte_encoder[' '.encode('utf-8'		)[0]]

								# Testing encoder arguments
								A					       = tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase			,			add_prefix_space=_lowercase		)
								A					       = tokenizer.convert_ids_to_tokens(encoded[0]		)[0]
								self.assertNotEqual(_lowercase			,			_lowercase		)

								A					       = tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase			,			add_prefix_space=_lowercase		)
								A					       = tokenizer.convert_ids_to_tokens(encoded[0]		)[0]
								self.assertEqual(_lowercase			,			_lowercase		)

								tokenizer.add_special_tokens({'bos_token': '<s>'}		)
								A					       = tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase		)
								A					       = tokenizer.convert_ids_to_tokens(encoded[1]		)[0]
								self.assertNotEqual(_lowercase			,			_lowercase		)

								# Testing spaces after special tokens
								A					       = '<mask>'
								tokenizer.add_special_tokens(
								    {'mask_token': AddedToken(_lowercase			,			lstrip=_lowercase			,			rstrip=_lowercase		)}		)  # mask token has a left space
								A					       = tokenizer.convert_tokens_to_ids(_lowercase		)

								A					       = 'Encode <mask> sequence'
								A					       = 'Encode <mask>sequence'

								A					       = tokenizer.encode(_lowercase		)
								A					       = encoded.index(_lowercase		)
								A					       = tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]		)[0]
								self.assertEqual(_lowercase			,			_lowercase		)

								A					       = tokenizer.encode(_lowercase		)
								A					       = encoded.index(_lowercase		)
								A					       = tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]		)[0]
								self.assertNotEqual(_lowercase			,			_lowercase		)







						def __a						(							self   :    Optional[Any]		):
								pass







						def __a						(							self   :    List[Any]		):
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
										with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'		):
												A					       = self.rust_tokenizer_class.from_pretrained(_lowercase			,			**_lowercase		)
												A					       = self.tokenizer_class.from_pretrained(_lowercase			,			**_lowercase		)
												A					       = 'A, <mask> AllenNLP sentence.'
												A					       = tokenizer_r.encode_plus(_lowercase			,			add_special_tokens=_lowercase			,			return_token_type_ids=_lowercase		)
												A					       = tokenizer_p.encode_plus(_lowercase			,			add_special_tokens=_lowercase			,			return_token_type_ids=_lowercase		)

												# token_type_ids should put 0 everywhere
												self.assertEqual(sum(tokens_r['token_type_ids']		)			,			sum(tokens_p['token_type_ids']		)		)

												# attention_mask should put 1 everywhere, so sum over length should be 1
												self.assertEqual(
												    sum(tokens_r['attention_mask']		) / len(tokens_r['attention_mask']		)			,			sum(tokens_p['attention_mask']		) / len(tokens_p['attention_mask']		)			,			)

												A					       = tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']		)
												A					       = tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids']		)

												# Rust correctly handles the space before the mask while python doesnt
												self.assertSequenceEqual(tokens_p['input_ids']			,			[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]		)
												self.assertSequenceEqual(tokens_r['input_ids']			,			[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]		)

												self.assertSequenceEqual(
												    _lowercase			,			['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']		)
												self.assertSequenceEqual(
												    _lowercase			,			['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']		)







						def __a						(							self   :    Any		):
								for trim_offsets, add_prefix_space in itertools.product([True, False]			,			repeat=2		):
										A					       = self.rust_tokenizer_class.from_pretrained(
										    self.tmpdirname			,			use_fast=_lowercase			,			add_prefix_space=_lowercase			,			trim_offsets=_lowercase		)

										A					       = json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()		)
										A					       = json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()		)

										self.assertEqual(pre_tokenizer_state['add_prefix_space']			,			_lowercase		)

										self.assertEqual(post_processor_state['add_prefix_space']			,			_lowercase		)
										self.assertEqual(post_processor_state['trim_offsets']			,			_lowercase		)







						def __a						(							self   :    Tuple		):
								# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
								# `trim_offsets`
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
										with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'		):
												A					       = 'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
												A					       = f'{text_of_1_token} {text_of_1_token}'

												A					       = self.rust_tokenizer_class.from_pretrained(
												    _lowercase			,			use_fast=_lowercase			,			add_prefix_space=_lowercase			,			trim_offsets=_lowercase		)
												A					       = tokenizer_r(_lowercase			,			return_offsets_mapping=_lowercase			,			add_special_tokens=_lowercase		)
												self.assertEqual(encoding.offset_mapping[0]			,			(0, len(_lowercase		))		)
												self.assertEqual(
												    encoding.offset_mapping[1]			,			(len(_lowercase		) + 1, len(_lowercase		) + 1 + len(_lowercase		))			,			)

												A					       = self.rust_tokenizer_class.from_pretrained(
												    _lowercase			,			use_fast=_lowercase			,			add_prefix_space=_lowercase			,			trim_offsets=_lowercase		)
												A					       = tokenizer_r(_lowercase			,			return_offsets_mapping=_lowercase			,			add_special_tokens=_lowercase		)
												self.assertEqual(encoding.offset_mapping[0]			,			(0, len(_lowercase		))		)
												self.assertEqual(
												    encoding.offset_mapping[1]			,			(len(_lowercase		) + 1, len(_lowercase		) + 1 + len(_lowercase		))			,			)

												A					       = self.rust_tokenizer_class.from_pretrained(
												    _lowercase			,			use_fast=_lowercase			,			add_prefix_space=_lowercase			,			trim_offsets=_lowercase		)
												A					       = tokenizer_r(_lowercase			,			return_offsets_mapping=_lowercase			,			add_special_tokens=_lowercase		)
												self.assertEqual(encoding.offset_mapping[0]			,			(0, len(_lowercase		))		)
												self.assertEqual(
												    encoding.offset_mapping[1]			,			(len(_lowercase		), len(_lowercase		) + 1 + len(_lowercase		))			,			)

												A					       = self.rust_tokenizer_class.from_pretrained(
												    _lowercase			,			use_fast=_lowercase			,			add_prefix_space=_lowercase			,			trim_offsets=_lowercase		)
												A					       = tokenizer_r(_lowercase			,			return_offsets_mapping=_lowercase			,			add_special_tokens=_lowercase		)
												self.assertEqual(encoding.offset_mapping[0]			,			(0, len(_lowercase		))		)
												self.assertEqual(
												    encoding.offset_mapping[1]			,			(len(_lowercase		), len(_lowercase		) + 1 + len(_lowercase		))			,			)

												A					       = f' {text}'

												# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
												#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
												# )
												# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
												# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
												# self.assertEqual(
												#     encoding.offset_mapping[1],
												#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
												# )

												A					       = self.rust_tokenizer_class.from_pretrained(
												    _lowercase			,			use_fast=_lowercase			,			add_prefix_space=_lowercase			,			trim_offsets=_lowercase		)
												A					       = tokenizer_r(_lowercase			,			return_offsets_mapping=_lowercase			,			add_special_tokens=_lowercase		)
												self.assertEqual(encoding.offset_mapping[0]			,			(1, 1 + len(_lowercase		))		)
												self.assertEqual(
												    encoding.offset_mapping[1]			,			(1 + len(_lowercase		) + 1, 1 + len(_lowercase		) + 1 + len(_lowercase		))			,			)

												A					       = self.rust_tokenizer_class.from_pretrained(
												    _lowercase			,			use_fast=_lowercase			,			add_prefix_space=_lowercase			,			trim_offsets=_lowercase		)
												A					       = tokenizer_r(_lowercase			,			return_offsets_mapping=_lowercase			,			add_special_tokens=_lowercase		)
												self.assertEqual(encoding.offset_mapping[0]			,			(0, 1 + len(_lowercase		))		)
												self.assertEqual(
												    encoding.offset_mapping[1]			,			(1 + len(_lowercase		), 1 + len(_lowercase		) + 1 + len(_lowercase		))			,			)

												A					       = self.rust_tokenizer_class.from_pretrained(
												    _lowercase			,			use_fast=_lowercase			,			add_prefix_space=_lowercase			,			trim_offsets=_lowercase		)
												A					       = tokenizer_r(_lowercase			,			return_offsets_mapping=_lowercase			,			add_special_tokens=_lowercase		)
												self.assertEqual(encoding.offset_mapping[0]			,			(0, 1 + len(_lowercase		))		)
												self.assertEqual(
												    encoding.offset_mapping[1]			,			(1 + len(_lowercase		), 1 + len(_lowercase		) + 1 + len(_lowercase		))			,			)









"""simple docstring"""


from math import sqrt







def  __snake_case       (   UpperCamelCase__	)      ->		int:







		"""simple docstring"""





		A					       = 0
		for i in range(1 ,			int(sqrt(UpperCamelCase__	) + 1	)	):
				if n % i == 0 and i != sqrt(UpperCamelCase__	):
						total += i + n // i
				elif i == sqrt(UpperCamelCase__	):
						total += i
		return total - n







def  __snake_case       (   UpperCamelCase__ = 10000	)      ->		int:







		"""simple docstring"""





		A					       = sum(
		    i
		    for i in range(1 ,			UpperCamelCase__	)
		    if sum_of_divisors(sum_of_divisors(UpperCamelCase__	)	) == i and sum_of_divisors(UpperCamelCase__	) != i	)
		return total


if __name__ == "__main__":
	print(solution(int(str(input()).strip())))





