






"""simple docstring"""


import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class 			lowerCamelCase__						(   snake_case__							,    unittest.TestCase			):
						lowerCAmelCase       =     CLIPTokenizer
						lowerCAmelCase       =     CLIPTokenizerFast
						lowerCAmelCase       =     True
						lowerCAmelCase       =     {}
						lowerCAmelCase       =     False







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

								# fmt: off
								A					       = ['l', 'o', 'w', 'e', 'r', 's', 't', 'i', 'd', 'n', 'lo', 'l</w>', 'w</w>', 'r</w>', 't</w>', 'low</w>', 'er</w>', 'lowest</w>', 'newer</w>', 'wider', '<unk>', '<|startoftext|>', '<|endoftext|>']
								# fmt: on
								A					       = dict(zip(_SCREAMING_SNAKE_CASE			,			range(len(_SCREAMING_SNAKE_CASE		)		)		)		)
								A					       = ['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>']
								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(_SCREAMING_SNAKE_CASE		) + '\n'		)
								with open(self.merges_file			,			'w'			,			encoding='utf-8'		) as fp:
										fp.write('\n'.join(_SCREAMING_SNAKE_CASE		)		)







						def __a						(							self   :    Optional[int]			,			**_lowercase   :    Optional[int]		):
								kwargs.update(self.special_tokens_map		)
								return CLIPTokenizer.from_pretrained(self.tmpdirname			,			**_SCREAMING_SNAKE_CASE		)







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







						def __a						(							self   :    Any			,			_lowercase   :    Optional[int]		):
								A					       = 'lower newer'
								A					       = 'lower newer'
								return input_text, output_text







						def __a						(							self   :    List[str]		):
								A					       = CLIPTokenizer(self.vocab_file			,			self.merges_file			,			**self.special_tokens_map		)
								A					       = 'lower newer'
								A					       = ['lo', 'w', 'er</w>', 'n', 'e', 'w', 'er</w>']
								A					       = tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
								self.assertListEqual(_SCREAMING_SNAKE_CASE			,			_SCREAMING_SNAKE_CASE		)

								A					       = tokens + [tokenizer.unk_token]
								A					       = [10, 2, 16, 9, 3, 2, 16, 20]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)			,			_SCREAMING_SNAKE_CASE		)







						@require_ftfy
						def __a						(							self   :    Union[str, Any]		):
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
										with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'		):
												A					       = self.tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE			,			**_SCREAMING_SNAKE_CASE		)
												A					       = self.rust_tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE			,			**_SCREAMING_SNAKE_CASE		)

												A					       = 'A\n\'ll 11p223RF☆ho!!to?\'d\'d\'\'d of a cat to-$\'\'d.'
												A					       = tokenizer_s.tokenize(_SCREAMING_SNAKE_CASE		)
												A					       = tokenizer_r.tokenize(_SCREAMING_SNAKE_CASE		)

												self.assertListEqual(_SCREAMING_SNAKE_CASE			,			_SCREAMING_SNAKE_CASE		)

												# Test that the tokenization is identical on an example containing a character (Latin Small Letter A
												# with Tilde) encoded in 2 different ways
												A					       = 'xa\u0303y' + ' ' + 'x\xe3y'
												A					       = tokenizer_s.tokenize(_SCREAMING_SNAKE_CASE		)
												A					       = tokenizer_r.tokenize(_SCREAMING_SNAKE_CASE		)

												self.assertListEqual(_SCREAMING_SNAKE_CASE			,			_SCREAMING_SNAKE_CASE		)

												# Test that the tokenization is identical on unicode of space type
												A					       = [
												    '\u0009',  # (horizontal tab, '\t')
												    '\u000B',  # (vertical tab)
												    '\u000C',  # (form feed)
												    '\u0020',  # (space, ' ')
												    '\u200E',  # (left-to-right mark):w
												    '\u200F',  # (right-to-left mark)
												]
												for unicode_seq in spaces_unicodes:
														A					       = tokenizer_s.tokenize(_SCREAMING_SNAKE_CASE		)
														A					       = tokenizer_r.tokenize(_SCREAMING_SNAKE_CASE		)

														self.assertListEqual(_SCREAMING_SNAKE_CASE			,			_SCREAMING_SNAKE_CASE		)

												# Test that the tokenization is identical on unicode of line break type
												A					       = [
												    '\u000A',  # (line feed, '\n')
												    '\r\n',  # (carriage return and line feed, '\r\n')
												    '\u000D',  # (carriage return, '\r')
												    '\r',  # (carriage return, '\r')
												    '\u000D',  # (carriage return, '\r')
												    '\u2028',  # (line separator)
												    '\u2029',  # (paragraph separator)
												    # "\u0085", # (next line)
												]

												# The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
												# it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
												# space (and thus into an empty list).

												for unicode_seq in line_break_unicodes:
														A					       = tokenizer_s.tokenize(_SCREAMING_SNAKE_CASE		)
														A					       = tokenizer_r.tokenize(_SCREAMING_SNAKE_CASE		)

														self.assertListEqual(_SCREAMING_SNAKE_CASE			,			_SCREAMING_SNAKE_CASE		)







						def __a						(							self   :    List[str]		):
								# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space`
								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(
												    _SCREAMING_SNAKE_CASE			,			use_fast=_SCREAMING_SNAKE_CASE			,			)
												A					       = tokenizer_r(_SCREAMING_SNAKE_CASE			,			return_offsets_mapping=_SCREAMING_SNAKE_CASE			,			add_special_tokens=_SCREAMING_SNAKE_CASE		)
												self.assertEqual(encoding.offset_mapping[0]			,			(0, len(_SCREAMING_SNAKE_CASE		))		)
												self.assertEqual(
												    encoding.offset_mapping[1]			,			(len(_SCREAMING_SNAKE_CASE		) + 1, len(_SCREAMING_SNAKE_CASE		) + 1 + len(_SCREAMING_SNAKE_CASE		))			,			)

												A					       = f' {text}'

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







						def __a						(							self   :    Any		):
								# Test related to the breaking change introduced in transformers v4.17.0
								# We need to check that an error in raised when the user try to load a previous version of the tokenizer.
								with self.assertRaises(_SCREAMING_SNAKE_CASE		) as context:
										self.rust_tokenizer_class.from_pretrained('robot-test/old-clip-tokenizer'		)

								self.assertTrue(
								    context.exception.args[0].startswith(
								        'The `backend_tokenizer` provided does not match the expected format.'		)		)







						@require_ftfy
						def __a						(							self   :    Optional[int]		):
								super().test_tokenization_python_rust_equals()







						def __a						(							self   :    Any		):
								pass









"""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())))





