


'''simple docstring'''



from typing import TYPE_CHECKING

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


_lowercase      :      List[str]            =					{
    """configuration_tapas""": ["""TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TapasConfig"""],
    """tokenization_tapas""": ["""TapasTokenizer"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase      :      Dict            =					[
	    """TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TapasForMaskedLM""",
	    """TapasForQuestionAnswering""",
	    """TapasForSequenceClassification""",
	    """TapasModel""",
	    """TapasPreTrainedModel""",
	    """load_tf_weights_in_tapas""",
	]
try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase      :      Tuple            =					[
	    """TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TFTapasForMaskedLM""",
	    """TFTapasForQuestionAnswering""",
	    """TFTapasForSequenceClassification""",
	    """TFTapasModel""",
	    """TFTapasPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
	from .tokenization_tapas import TapasTokenizer

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tapas import (
		    TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TapasForMaskedLM,
		    TapasForQuestionAnswering,
		    TapasForSequenceClassification,
		    TapasModel,
		    TapasPreTrainedModel,
		    load_tf_weights_in_tapas,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_tapas import (
		    TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFTapasForMaskedLM,
		    TFTapasForQuestionAnswering,
		    TFTapasForSequenceClassification,
		    TFTapasModel,
		    TFTapasPreTrainedModel,
		)


else:
	import sys

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









'''simple docstring'''



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




						'''simple docstring'''






						return int(input_a == input_a == 0					)


def 				lowerCamelCase__				(	):




						'''simple docstring'''






						print('''Truth Table of NOR Gate:'''					)
						print('''|   Input 1   |  Input 2  | Output |'''					)
						print(f"""|      0      |    0      |  {nor_gate(0				,       0					)}     |"""					)
						print(f"""|      0      |    1      |  {nor_gate(0				,       1					)}     |"""					)
						print(f"""|      1      |    0      |  {nor_gate(1				,       0					)}     |"""					)
						print(f"""|      1      |    1      |  {nor_gate(1				,       1					)}     |"""					)


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()





