
'''simple docstring'''
import sys

a_											=						(
    "73167176531330624919225119674426574742355349194934"
    "96983520312774506326239578318016984801869478851843"
    "85861560789112949495459501737958331952853208805511"
    "12540698747158523863050715693290963295227443043557"
    "66896648950445244523161731856403098711121722383113"
    "62229893423380308135336276614282806444486645238749"
    "30358907296290491560440772390713810515859307960866"
    "70172427121883998797908792274921901699720888093776"
    "65727333001053367881220235421809751254540594752243"
    "52584907711670556013604839586446706324415722155397"
    "53697817977846174064955149290862569321978468622482"
    "83972241375657056057490261407972968652414535100474"
    "82166370484403199890008895243450658541227588666881"
    "16427171479924442928230863465674813919123162824586"
    "17866458359124566529476545682848912883142607690042"
    "24219022671055626321111109370544217506941658960408"
    "07198403850962455444362981230987879927244284909188"
    "84580156166097919133875499200524063689912560717606"
    "05886116467109405077541002256983155200055935729725"
    "71636269561882670428252483600823257530420752963450"
)

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE = N       ):
    """simple docstring"""






    snake_case_ :    Tuple     			=						-sys.maxsize - 1
    for i in range(len(__SCREAMING_SNAKE_CASE       ) - 1_2       ):
        snake_case_ :    List[str]     			=						1
        for j in range(1_3       ):
            product *= int(n[i + j]       )
        if product > largest_product:
            snake_case_ :    str     			=						product
    return largest_product


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






'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_											=						{"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_											=						[
      "WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST",
      "WavLMForAudioFrameClassification",
      "WavLMForCTC",
      "WavLMForSequenceClassification",
      "WavLMForXVector",
      "WavLMModel",
      "WavLMPreTrainedModel",
  ]

if TYPE_CHECKING:
  from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_wavlm import (
        WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
        WavLMForAudioFrameClassification,
        WavLMForCTC,
        WavLMForSequenceClassification,
        WavLMForXVector,
        WavLMModel,
        WavLMPreTrainedModel,
    )

else:
  import sys

  a_											=						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




