





'''simple docstring'''







import sys

snake_case_     :       Optional[int]						=  (
    "73167176531330624919225119674426574742355349194934"
    "96983520312774506326239578318016984801869478851843"
    "85861560789112949495459501737958331952853208805511"
    "12540698747158523863050715693290963295227443043557"
    "66896648950445244523161731856403098711121722383113"
    "62229893423380308135336276614282806444486645238749"
    "30358907296290491560440772390713810515859307960866"
    "70172427121883998797908792274921901699720888093776"
    "65727333001053367881220235421809751254540594752243"
    "52584907711670556013604839586446706324415722155397"
    "53697817977846174064955149290862569321978468622482"
    "83972241375657056057490261407972968652414535100474"
    "82166370484403199890008895243450658541227588666881"
    "16427171479924442928230863465674813919123162824586"
    "17866458359124566529476545682848912883142607690042"
    "24219022671055626321111109370544217506941658960408"
    "07198403850962455444362981230987879927244284909188"
    "84580156166097919133875499200524063689912560717606"
    "05886116467109405077541002256983155200055935729725"
    "71636269561882670428252483600823257530420752963450"
)





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			str = N   ) ->	int:
						UpperCAmelCase_			:      str     						=  -sys.maxsize - 1
						for i in range(len(SCREAMING_SNAKE_CASE__   ) - 12   ):
												UpperCAmelCase_			:      Union[str, Any]     						=  1
												for j in range(13   ):
																		product *= int(n[i + j]   )
												if product > largest_product:
																		UpperCAmelCase_			:      List[Any]     						=  product
						return largest_product


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












'''simple docstring'''







import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin


class 					__a      (lowerCamelCase       ,		unittest.TestCase     ):
							__a					:   List[str]									=       BlenderbotSmallTokenizer
							__a					:   List[Any]									=       False

							def     UpperCAmelCase__	(							self							:     str   )					->       str:







													"""simple docstring"""
													super().setUp()

													UpperCAmelCase_			:      Tuple     						=  ['''__start__''', '''adapt''', '''act''', '''ap@@''', '''te''', '''__end__''', '''__unk__''']
													UpperCAmelCase_			:      Optional[Any]     						=  dict(zip(__magic_name__       ,     range(len(__magic_name__   )   )   )   )

													UpperCAmelCase_			:      int     						=  ['''#version: 0.2''', '''a p''', '''t e</w>''', '''ap t</w>''', '''a d''', '''ad apt</w>''', '''a c''', '''ac t</w>''', '''''']
													UpperCAmelCase_			:      Optional[Any]     						=  {'''unk_token''': '''__unk__''', '''bos_token''': '''__start__''', '''eos_token''': '''__end__'''}

													UpperCAmelCase_			:      Tuple     						=  os.path.join(self.tmpdirname       ,     VOCAB_FILES_NAMES['''vocab_file''']   )
													UpperCAmelCase_			:      Dict     						=  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(__magic_name__   ) + '''\n'''   )
													with open(self.merges_file       ,     '''w'''       ,     encoding='''utf-8'''   ) as fp:
																			fp.write('''\n'''.join(__magic_name__   )   )

							def     UpperCAmelCase__	(							self							:     List[Any]       ,     **__magic_name__							:     Dict   )					->       Tuple:







													"""simple docstring"""
													kwargs.update(self.special_tokens_map   )
													return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname       ,     **__magic_name__   )

							def     UpperCAmelCase__	(							self							:     Optional[int]       ,     __magic_name__							:     List[str]   )					->       List[str]:







													"""simple docstring"""
													UpperCAmelCase_			:      str     						=  '''adapt act apte'''
													UpperCAmelCase_			:      Tuple     						=  '''adapt act apte'''
													return input_text, output_text

							def     UpperCAmelCase__	(							self							:     str   )					->       Any:







													"""simple docstring"""
													UpperCAmelCase_			:      str     						=  BlenderbotSmallTokenizer(self.vocab_file       ,     self.merges_file       ,     **self.special_tokens_map   )
													UpperCAmelCase_			:      List[Any]     						=  '''adapt act apte'''
													UpperCAmelCase_			:      Dict     						=  ['''adapt''', '''act''', '''ap@@''', '''te''']
													UpperCAmelCase_			:      Dict     						=  tokenizer.tokenize(__magic_name__   )
													self.assertListEqual(__magic_name__       ,     __magic_name__   )

													UpperCAmelCase_			:      Tuple     						=  [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

													UpperCAmelCase_			:      Dict     						=  [0, 1, 2, 3, 4, 5]
													self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__   )       ,     __magic_name__   )

							def     UpperCAmelCase__	(							self							:     int   )					->       List[str]:







													"""simple docstring"""
													UpperCAmelCase_			:      List[Any]     						=  BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''   )
													assert tok('''sam'''   ).input_ids == [13_84]
													UpperCAmelCase_			:      Optional[int]     						=  '''I am a small frog.'''
													UpperCAmelCase_			:      List[str]     						=  tok([src_text]       ,     padding=__magic_name__       ,     truncation=__magic_name__   )['''input_ids''']
													UpperCAmelCase_			:      Dict     						=  tok.batch_decode(__magic_name__       ,     skip_special_tokens=__magic_name__       ,     clean_up_tokenization_spaces=__magic_name__   )[0]
													assert src_text != decoded  # I wish it did!
													assert decoded == "i am a small frog ."



							def     UpperCAmelCase__	(							self							:     Any   )					->       Union[str, Any]:







													"""simple docstring"""
													UpperCAmelCase_			:      int     						=  BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''   )
													UpperCAmelCase_			:      List[Any]     						=  '''I am a small frog .'''
													UpperCAmelCase_			:      Any     						=  '''.'''
													UpperCAmelCase_			:      List[Any]     						=  tok(__magic_name__   )['''input_ids''']
													UpperCAmelCase_			:      Optional[int]     						=  tok(__magic_name__   )['''input_ids''']

													assert encoded[-1] == encoded_dot[0]





