



from typing import TYPE_CHECKING

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


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

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

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


try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case		=  [
						    "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

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





"""simple docstring"""







import warnings

from diffusers import StableDiffusionImgaImgPipeline  # noqa F401


warnings.warn(
    """The `image_to_image.py` script is outdated. Please use directly `from diffusers import"""
    """ StableDiffusionImg2ImgPipeline` instead."""
)





