from ..utils import DummyObject, requires_backends





class       lowercase__		(     metaclass=UpperCamelCase_):
						UpperCamelCase_  =	["""note_seq"""]


						def __init__( self			:       Dict					,	*UpperCamelCase__			:       str					,	**UpperCamelCase__			:       List[str]		):





												'''simple docstring'''





												requires_backends(self					,	['''note_seq''']		)


						@classmethod
						def  __A ( cls			:       List[str]					,	*UpperCamelCase__			:       int					,	**UpperCamelCase__			:       Dict		):





												'''simple docstring'''





												requires_backends(cls					,	['''note_seq''']		)



						@classmethod
						def  __A ( cls			:       List[Any]					,	*UpperCamelCase__			:       Union[str, Any]					,	**UpperCamelCase__			:       List[Any]		):





												'''simple docstring'''





												requires_backends(cls					,	['''note_seq''']		)






from typing import TYPE_CHECKING

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


__UpperCamelCase	: Tuple    		=  {
    'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
    'configuration_maskformer_swin': ['MaskFormerSwinConfig'],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase	: Optional[Any]    		=  ['MaskFormerFeatureExtractor']
					__UpperCamelCase	: List[Any]    		=  ['MaskFormerImageProcessor']


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase	: Optional[int]    		=  [
					    'MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'MaskFormerForInstanceSegmentation',
					    'MaskFormerModel',
					    'MaskFormerPreTrainedModel',
					]
					__UpperCamelCase	: Union[str, Any]    		=  [
					    '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

					__UpperCamelCase	: List[str]    		=  _LazyModule(__name__, globals()['__file__'], _import_structure)





