






from typing import TYPE_CHECKING

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


__magic_name__:					Dict							=     {"""configuration_beit""": ["""BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BeitConfig""", """BeitOnnxConfig"""]}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__magic_name__:					int							=     ["""BeitFeatureExtractor"""]
			__magic_name__:					Any							=     ["""BeitImageProcessor"""]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__magic_name__:					Any							=     [
			    """BEIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """BeitForImageClassification""",
			    """BeitForMaskedImageModeling""",
			    """BeitForSemanticSegmentation""",
			    """BeitModel""",
			    """BeitPreTrainedModel""",
			]


try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__magic_name__:					List[str]							=     [
			    """FlaxBeitForImageClassification""",
			    """FlaxBeitForMaskedImageModeling""",
			    """FlaxBeitModel""",
			    """FlaxBeitPreTrainedModel""",
			]

if TYPE_CHECKING:
			from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_beit import BeitFeatureExtractor
						from .image_processing_beit import BeitImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_beit import (
						    BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    BeitForImageClassification,
						    BeitForMaskedImageModeling,
						    BeitForSemanticSegmentation,
						    BeitModel,
						    BeitPreTrainedModel,
						)

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flax_beit import (
						    FlaxBeitForImageClassification,
						    FlaxBeitForMaskedImageModeling,
						    FlaxBeitModel,
						    FlaxBeitPreTrainedModel,
						)


else:
			import sys

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








__magic_name__:					List[Any]							=     "\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"

__magic_name__:					Dict							=     [{"type": "code", "content": INSTALL_CONTENT}]
__magic_name__:					Optional[Any]							=     {
    "{processor_class}": "FakeProcessorClass",
    "{model_class}": "FakeModelClass",
    "{object_class}": "FakeObjectClass",
}
