

'''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_albert''': ['''ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''AlbertConfig''', '''AlbertOnnxConfig'''],
}

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

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

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						    =      [
          '''ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''AlbertForMaskedLM''',
          '''AlbertForMultipleChoice''',
          '''AlbertForPreTraining''',
          '''AlbertForQuestionAnswering''',
          '''AlbertForSequenceClassification''',
          '''AlbertForTokenClassification''',
          '''AlbertModel''',
          '''AlbertPreTrainedModel''',
          '''load_tf_weights_in_albert''',
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						    =      [
          '''TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''TFAlbertForMaskedLM''',
          '''TFAlbertForMultipleChoice''',
          '''TFAlbertForPreTraining''',
          '''TFAlbertForQuestionAnswering''',
          '''TFAlbertForSequenceClassification''',
          '''TFAlbertForTokenClassification''',
          '''TFAlbertMainLayer''',
          '''TFAlbertModel''',
          '''TFAlbertPreTrainedModel''',
      ]

try:
      if not is_flax_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						    =      [
          '''FlaxAlbertForMaskedLM''',
          '''FlaxAlbertForMultipleChoice''',
          '''FlaxAlbertForPreTraining''',
          '''FlaxAlbertForQuestionAnswering''',
          '''FlaxAlbertForSequenceClassification''',
          '''FlaxAlbertForTokenClassification''',
          '''FlaxAlbertModel''',
          '''FlaxAlbertPreTrainedModel''',
      ]

if TYPE_CHECKING:
      from .configuration_albert import ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, AlbertConfig, AlbertOnnxConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_albert import AlbertTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_albert_fast import AlbertTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_albert import (
                ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                AlbertForMaskedLM,
                AlbertForMultipleChoice,
                AlbertForPreTraining,
                AlbertForQuestionAnswering,
                AlbertForSequenceClassification,
                AlbertForTokenClassification,
                AlbertModel,
                AlbertPreTrainedModel,
                load_tf_weights_in_albert,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_albert import (
                TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFAlbertForMaskedLM,
                TFAlbertForMultipleChoice,
                TFAlbertForPreTraining,
                TFAlbertForQuestionAnswering,
                TFAlbertForSequenceClassification,
                TFAlbertForTokenClassification,
                TFAlbertMainLayer,
                TFAlbertModel,
                TFAlbertPreTrainedModel,
            )

      try:
            if not is_flax_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_flax_albert import (
                FlaxAlbertForMaskedLM,
                FlaxAlbertForMultipleChoice,
                FlaxAlbertForPreTraining,
                FlaxAlbertForQuestionAnswering,
                FlaxAlbertForSequenceClassification,
                FlaxAlbertForTokenClassification,
                FlaxAlbertModel,
                FlaxAlbertPreTrainedModel,
            )
else:
      import sys

      __lowerCamelCase						    =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



'''simple docstring'''







import sys

__lowerCamelCase						    =      (
    '''73167176531330624919225119674426574742355349194934'''
    '''96983520312774506326239578318016984801869478851843'''
    '''85861560789112949495459501737958331952853208805511'''
    '''12540698747158523863050715693290963295227443043557'''
    '''66896648950445244523161731856403098711121722383113'''
    '''62229893423380308135336276614282806444486645238749'''
    '''30358907296290491560440772390713810515859307960866'''
    '''70172427121883998797908792274921901699720888093776'''
    '''65727333001053367881220235421809751254540594752243'''
    '''52584907711670556013604839586446706324415722155397'''
    '''53697817977846174064955149290862569321978468622482'''
    '''83972241375657056057490261407972968652414535100474'''
    '''82166370484403199890008895243450658541227588666881'''
    '''16427171479924442928230863465674813919123162824586'''
    '''17866458359124566529476545682848912883142607690042'''
    '''24219022671055626321111109370544217506941658960408'''
    '''07198403850962455444362981230987879927244284909188'''
    '''84580156166097919133875499200524063689912560717606'''
    '''05886116467109405077541002256983155200055935729725'''
    '''71636269561882670428252483600823257530420752963450'''
)
def  UpperCAmelCase__      ( UpperCAmelCase__ = N			)     ->     int:
       A_		   = -sys.maxsize - 1
       for i in range(len(UpperCAmelCase__			) - 12			):
              A_		   = 1
              for j in range(13			):
                     product *= int(n[i + j]			)
              if product > largest_product:
                     A_		   = product
       return largest_product


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