
"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowerCamelCase     =  {'configuration_xglm': ['XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XGLMConfig']}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCamelCase     =  ['XGLMTokenizer']

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCamelCase     =  ['XGLMTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCamelCase     =  [
	    'XGLM_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'XGLMForCausalLM',
	    'XGLMModel',
	    'XGLMPreTrainedModel',
	]


try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCamelCase     =  [
	    'FlaxXGLMForCausalLM',
	    'FlaxXGLMModel',
	    'FlaxXGLMPreTrainedModel',
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCamelCase     =  [
	    'TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'TFXGLMForCausalLM',
	    'TFXGLMModel',
	    'TFXGLMPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_xglm import XGLMTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_xglm_fast import XGLMTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_xglm import (
		    TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFXGLMForCausalLM,
		    TFXGLMModel,
		    TFXGLMPreTrainedModel,
		)


else:
	import sys

	_lowerCamelCase     =  _LazyModule(__name__, globals()['__file__'], _import_structure)




"""simple docstring"""






from math import sqrt


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


def __lowercase     (      lowerCamelCase_  :      int = 10000  ):
				SCREAMING_SNAKE_CASE__     							=				sum(
				    i
				    for i in range(1						,					lowerCamelCase_  )
				    if sum_of_divisors(sum_of_divisors(lowerCamelCase_  )  ) == i and sum_of_divisors(lowerCamelCase_  ) != i  )
				return total


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