



"""simple docstring"""







from __future__ import annotations

def       _lowerCamelCase				(							UpperCAmelCase_ :       int | str     )	-> bool:






	"""simple docstring"""





	A__											=					str(UpperCAmelCase_     )
	return n == n[::-1]

def       _lowerCamelCase				(							UpperCAmelCase_ :       int = 1000000     )	-> Dict:






	"""simple docstring"""





	A__											=					0

	for i in range(1,	UpperCAmelCase_     ):
		if is_palindrome(UpperCAmelCase_     ) and is_palindrome(bin(UpperCAmelCase_     ).split("b"     )[1]     ):
			total += i
	return total


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








"""simple docstring"""


import unittest

from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_vision_available():
	from PIL import Image
else:
	class     _UpperCamelCase    :
								'''simple docstring'''







								@staticmethod
								def      snake_case							(	*__a       ,  **__a      ):
											pass
@is_pipeline_test
@require_torch
@require_vision
class     _UpperCamelCase    (  unittest.TestCase						):
							'''simple docstring'''







							__UpperCAmelCase		:       str							 =MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING

							def      snake_case							(	self       ,  __a       ,  __a       ,  __a      ):
										__lowerCAmelCase							       =     pipeline("visual-question-answering"       ,  model="hf-internal-testing/tiny-vilt-random-vqa"      )
										__lowerCAmelCase							       =     [
										    {
										        "image": Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png"      ),
										        "question": "How many cats are there?",
										    },
										    {
										        "image": "./tests/fixtures/tests_samples/COCO/000000039769.png",
										        "question": "How many cats are there?",
										    },
										]
										return vqa_pipeline, examples

							def      snake_case							(	self       ,  __a       ,  __a      ):
										__lowerCAmelCase							       =     vqa_pipeline(__a       ,  top_k=1      )
										self.assertEqual(
										    __a       ,  [
										        [{"score": ANY(__a      ), "answer": ANY(__a      )}],
										        [{"score": ANY(__a      ), "answer": ANY(__a      )}],
										    ]       ,  )

							@require_torch
							def      snake_case							(	self      ):
										__lowerCAmelCase							       =     pipeline("visual-question-answering"       ,  model="hf-internal-testing/tiny-vilt-random-vqa"      )
										__lowerCAmelCase							       =     "./tests/fixtures/tests_samples/COCO/000000039769.png"
										__lowerCAmelCase							       =     "How many cats are there?"

										__lowerCAmelCase							       =     vqa_pipeline(image=__a       ,  question="How many cats are there?"       ,  top_k=2      )
										self.assertEqual(
										    __a       ,  [{"score": ANY(__a      ), "answer": ANY(__a      )}, {"score": ANY(__a      ), "answer": ANY(__a      )}]      )

										__lowerCAmelCase							       =     vqa_pipeline({"image": image, "question": question}       ,  top_k=2      )
										self.assertEqual(
										    __a       ,  [{"score": ANY(__a      ), "answer": ANY(__a      )}, {"score": ANY(__a      ), "answer": ANY(__a      )}]      )

							@slow
							@require_torch
							def      snake_case							(	self      ):
										__lowerCAmelCase							       =     pipeline("visual-question-answering"       ,  model="dandelin/vilt-b32-finetuned-vqa"      )
										__lowerCAmelCase							       =     "./tests/fixtures/tests_samples/COCO/000000039769.png"
										__lowerCAmelCase							       =     "How many cats are there?"

										__lowerCAmelCase							       =     vqa_pipeline(image=__a       ,  question=__a       ,  top_k=2      )
										self.assertEqual(
										    nested_simplify(__a       ,  decimals=4      )       ,  [{"score": 0.8_7_9_9, "answer": "2"}, {"score": 0.2_9_6, "answer": "1"}]      )

										__lowerCAmelCase							       =     vqa_pipeline({"image": image, "question": question}       ,  top_k=2      )
										self.assertEqual(
										    nested_simplify(__a       ,  decimals=4      )       ,  [{"score": 0.8_7_9_9, "answer": "2"}, {"score": 0.2_9_6, "answer": "1"}]      )

										__lowerCAmelCase							       =     vqa_pipeline(
										    [{"image": image, "question": question}, {"image": image, "question": question}]       ,  top_k=2      )
										self.assertEqual(
										    nested_simplify(__a       ,  decimals=4      )       ,  [[{"score": 0.8_7_9_9, "answer": "2"}, {"score": 0.2_9_6, "answer": "1"}]] * 2       ,  )



							@require_tf
							@unittest.skip("Visual question answering not implemented in TF"      )
							def      snake_case							(	self      ):
										pass




