


import sys

snake_case				:    int       				=     (
    '''73167176531330624919225119674426574742355349194934'''
    '''96983520312774506326239578318016984801869478851843'''
    '''85861560789112949495459501737958331952853208805511'''
    '''12540698747158523863050715693290963295227443043557'''
    '''66896648950445244523161731856403098711121722383113'''
    '''62229893423380308135336276614282806444486645238749'''
    '''30358907296290491560440772390713810515859307960866'''
    '''70172427121883998797908792274921901699720888093776'''
    '''65727333001053367881220235421809751254540594752243'''
    '''52584907711670556013604839586446706324415722155397'''
    '''53697817977846174064955149290862569321978468622482'''
    '''83972241375657056057490261407972968652414535100474'''
    '''82166370484403199890008895243450658541227588666881'''
    '''16427171479924442928230863465674813919123162824586'''
    '''17866458359124566529476545682848912883142607690042'''
    '''24219022671055626321111109370544217506941658960408'''
    '''07198403850962455444362981230987879927244284909188'''
    '''84580156166097919133875499200524063689912560717606'''
    '''05886116467109405077541002256983155200055935729725'''
    '''71636269561882670428252483600823257530420752963450'''
)
def 				__lowerCamelCase						( UpperCAmelCase_						:		str = N						):




      """simple docstring"""





      a						:Optional[Any] 							=       -sys.maxsize - 1
      for i in range(len(UpperCAmelCase_						) - 12						):
            a						:Dict 							=       1
            for j in range(13						):
                  product *= int(n[i + j]						)
            if product > largest_product:
                  a						:str 							=       product
      return largest_product


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













"""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        a     :







        @staticmethod
        def 			UpperCamelCase_      (			*_lowerCamelCase							,		**_lowerCamelCase       ):
          pass

@is_pipeline_test
@require_torch
@require_vision
class        a     (   unittest.TestCase	):
    UpperCAmelCase_ :     Union[str, Any]	     =MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING







    def 			UpperCamelCase_      (			self							,		_lowerCamelCase							,		_lowerCamelCase							,		_lowerCamelCase       ):
      lowercase							    =       pipeline('visual-question-answering'							,		model='hf-internal-testing/tiny-vilt-random-vqa'       )
      lowercase							    =       [
          {
              '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 			UpperCamelCase_      (			self							,		_lowerCamelCase							,		_lowerCamelCase       ):
      lowercase							    =       vqa_pipeline(_lowerCamelCase							,		top_k=1       )
      self.assertEqual(
          _lowerCamelCase							,		[
              [{'score': ANY(_lowerCamelCase       ), 'answer': ANY(_lowerCamelCase       )}],
              [{'score': ANY(_lowerCamelCase       ), 'answer': ANY(_lowerCamelCase       )}],
          ]							,		)







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

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

      lowercase							    =       vqa_pipeline({'image': image, 'question': question}							,		top_k=2       )
      self.assertEqual(
          _lowerCamelCase							,		[{'score': ANY(_lowerCamelCase       ), 'answer': ANY(_lowerCamelCase       )}, {'score': ANY(_lowerCamelCase       ), 'answer': ANY(_lowerCamelCase       )}]       )







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

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

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

      lowercase							    =       vqa_pipeline(
          [{'image': image, 'question': question}, {'image': image, 'question': question}]							,		top_k=2       )
      self.assertEqual(
          nested_simplify(_lowerCamelCase							,		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 			UpperCamelCase_      (			self       ):
      pass


