
def 							__SCREAMING_SNAKE_CASE       (		SCREAMING_SNAKE_CASE	:				Tuple   ,							SCREAMING_SNAKE_CASE	:				str      )					->						str:
				if len(str(SCREAMING_SNAKE_CASE      )      ) == 1 or len(str(SCREAMING_SNAKE_CASE      )      ) == 1:
								return a * b

				__lowercase								= max(len(str(SCREAMING_SNAKE_CASE      )      )   ,							len(str(SCREAMING_SNAKE_CASE      )      )      )
				__lowercase								= ma // 2

				__lowercase		, __lowercase								= divmod(SCREAMING_SNAKE_CASE   ,							10**ma      )
				__lowercase		, __lowercase								= divmod(SCREAMING_SNAKE_CASE   ,							10**ma      )

				__lowercase								= karatsuba(SCREAMING_SNAKE_CASE   ,							SCREAMING_SNAKE_CASE      )
				__lowercase								= karatsuba((aa + aa)   ,							(ba + ba)      )
				__lowercase								= karatsuba(SCREAMING_SNAKE_CASE   ,							SCREAMING_SNAKE_CASE      )

				return (z * 10 ** (2 * ma)) + ((y - z - x) * 10 ** (ma)) + (x)




def 							__SCREAMING_SNAKE_CASE       (		)					->						str:
				print(karatsuba(15463   ,							23489      )      )


if __name__ == "__main__":
							main()







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


SCREAMING_SNAKE_CASE__							=    {"""configuration_hubert""": ["""HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """HubertConfig"""]}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__							=    [
							    """HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """HubertForCTC""",
							    """HubertForSequenceClassification""",
							    """HubertModel""",
							    """HubertPreTrainedModel""",
							]


try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__							=    [
							    """TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFHubertForCTC""",
							    """TFHubertModel""",
							    """TFHubertPreTrainedModel""",
							]

if TYPE_CHECKING:
							from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_hubert import (
														    HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    HubertForCTC,
														    HubertForSequenceClassification,
														    HubertModel,
														    HubertPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_hubert import (
														    TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFHubertForCTC,
														    TFHubertModel,
														    TFHubertPreTrainedModel,
														)


else:
							import sys

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





