

"""simple docstring"""






from typing import TYPE_CHECKING

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


snake_case_   :   Any        =       {
    "configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MobileViTConfig", "MobileViTOnnxConfig"],
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_   :   Dict        =       ["MobileViTFeatureExtractor"]
	snake_case_   :   int        =       ["MobileViTImageProcessor"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_   :   Any        =       [
	    "MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "MobileViTForImageClassification",
	    "MobileViTForSemanticSegmentation",
	    "MobileViTModel",
	    "MobileViTPreTrainedModel",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_   :   Any        =       [
	    "TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TFMobileViTForImageClassification",
	    "TFMobileViTForSemanticSegmentation",
	    "TFMobileViTModel",
	    "TFMobileViTPreTrainedModel",
	]

if TYPE_CHECKING:
	from .configuration_mobilevit import MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTConfig, MobileViTOnnxConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_mobilevit import MobileViTFeatureExtractor
		from .image_processing_mobilevit import MobileViTImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_mobilevit import (
		    MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MobileViTForImageClassification,
		    MobileViTForSemanticSegmentation,
		    MobileViTModel,
		    MobileViTPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_mobilevit import (
		    TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFMobileViTForImageClassification,
		    TFMobileViTForSemanticSegmentation,
		    TFMobileViTModel,
		    TFMobileViTPreTrainedModel,
		)


else:
	import sys

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









"""simple docstring"""






def   lowercase_	(    _lowercase       :		int							,      _lowercase       :		int	):




					'''simple docstring'''






					return int(input_a == input_a == 0	)



def   lowercase_	(    ):




					'''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()


