




from typing import TYPE_CHECKING

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


__A						:		Union[str, Any]          =						{
    "configuration_led": ["LED_PRETRAINED_CONFIG_ARCHIVE_MAP", "LEDConfig"],
    "tokenization_led": ["LEDTokenizer"],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A						:		Optional[int]          =						["LEDTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A						:		Optional[int]          =						[
	    "LED_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "LEDForConditionalGeneration",
	    "LEDForQuestionAnswering",
	    "LEDForSequenceClassification",
	    "LEDModel",
	    "LEDPreTrainedModel",
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A						:		Tuple          =						["TFLEDForConditionalGeneration", "TFLEDModel", "TFLEDPreTrainedModel"]


if TYPE_CHECKING:
	from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
	from .tokenization_led import LEDTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_led_fast import LEDTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_led import (
		    LED_PRETRAINED_MODEL_ARCHIVE_LIST,
		    LEDForConditionalGeneration,
		    LEDForQuestionAnswering,
		    LEDForSequenceClassification,
		    LEDModel,
		    LEDPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
	import sys

	__A						:		List[Any]          =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






"""simple docstring"""

def    lowerCAmelCase			(__UpperCamelCase							:    int							,					__UpperCamelCase							:    int			):
							"""simple docstring"""


							return (input_a, input_a).count(0			) % 2


def    lowerCAmelCase			():
							"""simple docstring"""


							assert xor_gate(0							,					0			) == 0
							assert xor_gate(0							,					1			) == 1
							assert xor_gate(1							,					0			) == 1
							assert xor_gate(1							,					1			) == 0


if __name__ == "__main__":
				print(xor_gate(0, 0))
				print(xor_gate(0, 1))



