






def 							A     (       a_							,a_					)     ->						str:

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

					__UpperCamelCase      :					str       		=len(a_					)
					__UpperCamelCase      :					Dict       		=len(a_					)

					__UpperCamelCase      :					Union[str, Any]       		=[[0] * (texta_length + 1) for _ in range(texta_length + 1					)]
					__UpperCamelCase      :					Dict       		=0
					__UpperCamelCase      :					Dict       		=0

					for i in range(1							,texta_length + 1					):
										for j in range(1							,texta_length + 1					):
															if texta[i - 1] == texta[j - 1]:
																				__UpperCamelCase      :					Any       		=1 + dp[i - 1][j - 1]
																				if dp[i][j] > ans_length:
																									__UpperCamelCase      :					Dict       		=i
																									__UpperCamelCase      :					Optional[Any]       		=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 ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable


lowerCAmelCase__											=	{
    '''configuration_gpt_neox_japanese''': ['''GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXJapaneseConfig'''],
    '''tokenization_gpt_neox_japanese''': ['''GPTNeoXJapaneseTokenizer'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase__											=	[
     '''GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''GPTNeoXJapaneseForCausalLM''',
     '''GPTNeoXJapaneseLayer''',
     '''GPTNeoXJapaneseModel''',
     '''GPTNeoXJapanesePreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
 from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_gpt_neox_japanese import (
      GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
      GPTNeoXJapaneseForCausalLM,
      GPTNeoXJapaneseLayer,
      GPTNeoXJapaneseModel,
      GPTNeoXJapanesePreTrainedModel,
  )


else:
 import sys

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

