

def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):

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

	UpperCAmelCase__:	Optional[int]									= len(SCREAMING_SNAKE_CASE      )
	UpperCAmelCase__:	List[str]									= len(SCREAMING_SNAKE_CASE      )

	UpperCAmelCase__:	List[str]									= [[0] * (texta_length + 1) for _ in range(texta_length + 1      )]
	UpperCAmelCase__:	Any									= 0
	UpperCAmelCase__:	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]:
				UpperCAmelCase__:	Any									= 1 + dp[i - 1][j - 1]
				if dp[i][j] > ans_length:
					UpperCAmelCase__:	str									= i
					UpperCAmelCase__:	List[str]									= dp[i][j]

	return texta[ans_index - ans_length : ans_index]


if __name__ == "__main__":
					import doctest

					doctest.testmod()


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCAmelCase  :      Union[str, Any]			 ={
    """configuration_clap""": [
        """CLAP_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """ClapAudioConfig""",
        """ClapConfig""",
        """ClapTextConfig""",
    ],
    """processing_clap""": ["""ClapProcessor"""],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowerCAmelCase  :      Union[str, Any]			 =[
					    """CLAP_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """ClapModel""",
					    """ClapPreTrainedModel""",
					    """ClapTextModel""",
					    """ClapTextModelWithProjection""",
					    """ClapAudioModel""",
					    """ClapAudioModelWithProjection""",
					]
					_lowerCAmelCase  :      List[str]			 =["""ClapFeatureExtractor"""]

if TYPE_CHECKING:
					from .configuration_clap import (
					    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
					    ClapAudioConfig,
					    ClapConfig,
					    ClapTextConfig,
					)
					from .processing_clap import ClapProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_clap import ClapFeatureExtractor
										from .modeling_clap import (
										    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ClapAudioModel,
										    ClapAudioModelWithProjection,
										    ClapModel,
										    ClapPreTrainedModel,
										    ClapTextModel,
										    ClapTextModelWithProjection,
										)


else:
					import sys

					_lowerCAmelCase  :      Optional[int]			 =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)