

"""simple docstring"""


from ..utils import DummyObject, requires_backends





class    snake_case     (    metaclass=__snake_case  ):
				SCREAMING_SNAKE_CASE_       :				Any       				=  ["""transformers""", """torch""", """note_seq"""]

				def __init__(     self							:    Optional[int]					,  *UpperCamelCase__							:    Dict					,  **UpperCamelCase__							:    List[Any])->       Dict:



						'''simple docstring'''


						requires_backends(self					,  ["transformers", "torch", "note_seq"])

				@classmethod
				def 							lowercase_					(     cls							:    Tuple					,  *UpperCamelCase__							:    Dict					,  **UpperCamelCase__							:    Tuple)->       Union[str, Any]:



						'''simple docstring'''


						requires_backends(cls					,  ["transformers", "torch", "note_seq"])




				@classmethod
				def 							lowercase_					(     cls							:    Optional[Any]					,  *UpperCamelCase__							:    List[str]					,  **UpperCamelCase__							:    List[str])->       Dict:



						'''simple docstring'''


						requires_backends(cls					,  ["transformers", "torch", "note_seq"])





"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A						       =      {
    "configuration_swinv2": ["SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Swinv2Config"],
}


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A						       =      [
			    "SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "Swinv2ForImageClassification",
			    "Swinv2ForMaskedImageModeling",
			    "Swinv2Model",
			    "Swinv2PreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_swinva import (
						    SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SwinvaForImageClassification,
						    SwinvaForMaskedImageModeling,
						    SwinvaModel,
						    SwinvaPreTrainedModel,
						)


else:
			import sys

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


