



def 			A_      (	__a     :				int ,		__a     :				int		):

				"""simple docstring"""
				if a < 0 or b < 0:
								raise ValueError("""the value of both inputs must be positive"""		)

				a__				      =		str(bin(__a		)		)[2:]  # remove the leading "0b"
				a__				      =		str(bin(__a		)		)[2:]  # remove the leading "0b"

				a__				      =		max(len(__a		) ,		len(__a		)		)

				return "0b" + "".join(
				    str(int(char_a == """1""" and char_b == """1"""		)		)
				    for char_a, char_b in zip(a_binary.zfill(__a		) ,		b_binary.zfill(__a		)		)		)


if __name__ == "__main__":
	import doctest

	doctest.testmod()






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


UpperCAmelCase							 =					{
    """configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconConfig"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase							 =					[
	    """FALCON_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """FalconForCausalLM""",
	    """FalconModel""",
	    """FalconPreTrainedModel""",
	    """FalconForSequenceClassification""",
	    """FalconForTokenClassification""",
	    """FalconForQuestionAnswering""",
	]


if TYPE_CHECKING:
	from .configuration_falcon import FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP, FalconConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_falcon import (
		    FALCON_PRETRAINED_MODEL_ARCHIVE_LIST,
		    FalconForCausalLM,
		    FalconForQuestionAnswering,
		    FalconForSequenceClassification,
		    FalconForTokenClassification,
		    FalconModel,
		    FalconPreTrainedModel,
		)


else:
	import sys

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

