





from typing import TYPE_CHECKING

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


lowerCAmelCase							:       Any					 =	{
    'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
    'configuration_maskformer_swin': ['MaskFormerSwinConfig'],
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase							:       Tuple					 =	['MaskFormerFeatureExtractor']
							lowerCAmelCase							:       List[str]					 =	['MaskFormerImageProcessor']


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase							:       Optional[Any]					 =	[
							    'MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'MaskFormerForInstanceSegmentation',
							    'MaskFormerModel',
							    'MaskFormerPreTrainedModel',
							]
							lowerCAmelCase							:       Optional[int]					 =	[
							    'MaskFormerSwinBackbone',
							    'MaskFormerSwinModel',
							    'MaskFormerSwinPreTrainedModel',
							]

if TYPE_CHECKING:
							from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
							from .configuration_maskformer_swin import MaskFormerSwinConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_maskformer import MaskFormerFeatureExtractor
														from .image_processing_maskformer import MaskFormerImageProcessor
							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_maskformer import (
														    MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MaskFormerForInstanceSegmentation,
														    MaskFormerModel,
														    MaskFormerPreTrainedModel,
														)
														from .modeling_maskformer_swin import (
														    MaskFormerSwinBackbone,
														    MaskFormerSwinModel,
														    MaskFormerSwinPreTrainedModel,
														)


else:
							import sys

							lowerCAmelCase							:       Union[str, Any]					 =	_LazyModule(__name__, globals()["""__file__"""], _import_structure)







'''simple docstring'''
def       _lowercase							(					UpperCamelCase__							:       int,					UpperCamelCase__							:       int      ):
 return 1 if input_a == input_a else 0


def       _lowercase							(					):
 assert xnor_gate(0,					0      ) == 1
 assert xnor_gate(0,					1      ) == 0
 assert xnor_gate(1,					0      ) == 0
 assert xnor_gate(1,					1      ) == 1


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






