



'''simple docstring'''

def      __lowerCamelCase     (      lowerCAmelCase_						,			lowerCAmelCase_  )			->      str:

		if not (isinstance(lowerCAmelCase_						,			lowerCAmelCase_  ) and isinstance(lowerCAmelCase_						,			lowerCAmelCase_  )):
				raise ValueError('longest_common_substring() takes two strings for inputs'  )

		_a     :      List[str]        =							len(lowerCAmelCase_  )
		_a     :      int        =							len(lowerCAmelCase_  )

		_a     :      Any        =							[[0] * (texta_length + 1) for _ in range(texta_length + 1  )]
		_a     :      Any        =							0
		_a     :      List[str]        =							0

		for i in range(1						,			texta_length + 1  ):
				for j in range(1						,			texta_length + 1  ):
						if texta[i - 1] == texta[j - 1]:
								_a     :      Optional[Any]        =							1 + dp[i - 1][j - 1]
								if dp[i][j] > ans_length:
										_a     :      int        =							i
										_a     :      Optional[int]        =							dp[i][j]

		return texta[ans_index - ans_length : ans_index]


if __name__ == "__main__":
							import doctest

							doctest.testmod()









'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCAmelCase									=   {
    '''configuration_lilt''': ['''LILT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LiltConfig'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase									=   [
							    '''LILT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''LiltForQuestionAnswering''',
							    '''LiltForSequenceClassification''',
							    '''LiltForTokenClassification''',
							    '''LiltModel''',
							    '''LiltPreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_lilt import (
														    LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    LiltForQuestionAnswering,
														    LiltForSequenceClassification,
														    LiltForTokenClassification,
														    LiltModel,
														    LiltPreTrainedModel,
														)

else:
							import sys

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




