


def 				lowerCamelCase__				(	A       :      int				,       A       :      int					):




						'''simple docstring'''






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

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

						UpperCAmelCase					    =     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()









'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowercase      :      List[str]            =					{
    """configuration_time_series_transformer""": [
        """TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """TimeSeriesTransformerConfig""",
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase      :      Dict            =					[
	    """TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TimeSeriesTransformerForPrediction""",
	    """TimeSeriesTransformerModel""",
	    """TimeSeriesTransformerPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_time_series_transformer import (
	    TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    TimeSeriesTransformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_time_series_transformer import (
		    TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TimeSeriesTransformerForPrediction,
		    TimeSeriesTransformerModel,
		    TimeSeriesTransformerPreTrainedModel,
		)

else:
	import sys

	_lowercase      :      Tuple            =					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





