




'''simple docstring'''

import sys

a  :				Dict									=  (
    '73167176531330624919225119674426574742355349194934'
    '96983520312774506326239578318016984801869478851843'
    '85861560789112949495459501737958331952853208805511'
    '12540698747158523863050715693290963295227443043557'
    '66896648950445244523161731856403098711121722383113'
    '62229893423380308135336276614282806444486645238749'
    '30358907296290491560440772390713810515859307960866'
    '70172427121883998797908792274921901699720888093776'
    '65727333001053367881220235421809751254540594752243'
    '52584907711670556013604839586446706324415722155397'
    '53697817977846174064955149290862569321978468622482'
    '83972241375657056057490261407972968652414535100474'
    '82166370484403199890008895243450658541227588666881'
    '16427171479924442928230863465674813919123162824586'
    '17866458359124566529476545682848912883142607690042'
    '24219022671055626321111109370544217506941658960408'
    '07198403850962455444362981230987879927244284909188'
    '84580156166097919133875499200524063689912560717606'
    '05886116467109405077541002256983155200055935729725'
    '71636269561882670428252483600823257530420752963450'
)


def 		__magic_name__    (	__UpperCAmelCase	)		->					int:

					'''simple docstring'''

					snake_case_									=				1
					for digit in s:
										product *= int(__UpperCAmelCase	)
					return product


def 		__magic_name__    (	__UpperCAmelCase = N	)		->					int:

					'''simple docstring'''

					snake_case_									=				-sys.maxsize - 1
					snake_case_									=				n[:13]
					snake_case_									=				13
					while cur_index < len(__UpperCAmelCase	) - 13:
										if int(n[cur_index]	) >= int(substr[0]	):
															snake_case_									=				substr[1:] + n[cur_index]
															cur_index += 1
										else:
															snake_case_									=				max(__UpperCAmelCase,      str_eval(__UpperCAmelCase	)	)
															snake_case_									=				n[cur_index : cur_index + 13]
															cur_index += 13
					return largest_product


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





'''simple docstring'''






import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin






class    __snake_case       (   _SCREAMING_SNAKE_CASE	,unittest.TestCase):







    """simple docstring"""



    lowercase    =					BioGptTokenizer
    lowercase    =					False

    def __lowercase   (   self    :  List[Any]		)   ->  List[str]:
      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      lowerCAmelCase_			:      Optional[Any]			=   [
          """l""",
          """o""",
          """w""",
          """e""",
          """r""",
          """s""",
          """t""",
          """i""",
          """d""",
          """n""",
          """w</w>""",
          """r</w>""",
          """t</w>""",
          """lo""",
          """low""",
          """er</w>""",
          """low</w>""",
          """lowest</w>""",
          """newer</w>""",
          """wider</w>""",
          """<unk>""",
      ]
      lowerCAmelCase_			:      int			=   dict(zip(lowerCamelCase    ,						range(len(lowerCamelCase		)		)		)		)
      lowerCAmelCase_			:      int			=   ["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

      lowerCAmelCase_			:      Optional[int]			=   os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES["""vocab_file"""]		)
      lowerCAmelCase_			:      Union[str, Any]			=   os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES["""merges_file"""]		)
      with open(self.vocab_file    ,						"""w"""		) as fp:
        fp.write(json.dumps(lowerCamelCase		)		)
      with open(self.merges_file    ,						"""w"""		) as fp:
        fp.write("""\n""".join(lowerCamelCase		)		)

    def __lowercase   (   self    :  Union[str, Any]    ,						lowerCamelCase    :  Any		)   ->  List[str]:
      lowerCAmelCase_			:      Dict			=   """lower newer"""
      lowerCAmelCase_			:      str			=   """lower newer"""
      return input_text, output_text

    def __lowercase   (   self    :  Optional[int]		)   ->  str:
      lowerCAmelCase_			:      Any			=   BioGptTokenizer(self.vocab_file    ,						self.merges_file		)

      lowerCAmelCase_			:      int			=   """lower"""
      lowerCAmelCase_			:      str			=   ["""low""", """er</w>"""]
      lowerCAmelCase_			:      Any			=   tokenizer.tokenize(lowerCamelCase		)
      self.assertListEqual(lowerCamelCase    ,						lowerCamelCase		)

      lowerCAmelCase_			:      Dict			=   tokens + ["""<unk>"""]
      lowerCAmelCase_			:      Optional[Any]			=   [14, 15, 20]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase		)    ,						lowerCamelCase		)





    @slow
    def __lowercase   (   self    :  str		)   ->  Optional[Any]:
      lowerCAmelCase_			:      Dict			=   BioGptTokenizer.from_pretrained("""microsoft/biogpt"""		)

      lowerCAmelCase_			:      int			=   tokenizer.encode("""sequence builders"""    ,						add_special_tokens=lowerCamelCase		)
      lowerCAmelCase_			:      Optional[Any]			=   tokenizer.encode("""multi-sequence build"""    ,						add_special_tokens=lowerCamelCase		)

      lowerCAmelCase_			:      str			=   tokenizer.build_inputs_with_special_tokens(lowerCamelCase		)
      lowerCAmelCase_			:      Optional[int]			=   tokenizer.build_inputs_with_special_tokens(lowerCamelCase    ,						lowerCamelCase		)

      self.assertTrue(encoded_sentence == [2] + text		)
      self.assertTrue(encoded_pair == [2] + text + [2] + text_a		)



