
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image


if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
			__A				={
			    '''linear''': PIL.Image.Resampling.BILINEAR,
			    '''bilinear''': PIL.Image.Resampling.BILINEAR,
			    '''bicubic''': PIL.Image.Resampling.BICUBIC,
			    '''lanczos''': PIL.Image.Resampling.LANCZOS,
			    '''nearest''': PIL.Image.Resampling.NEAREST,
			}
else:
			__A				={
			    '''linear''': PIL.Image.LINEAR,
			    '''bilinear''': PIL.Image.BILINEAR,
			    '''bicubic''': PIL.Image.BICUBIC,
			    '''lanczos''': PIL.Image.LANCZOS,
			    '''nearest''': PIL.Image.NEAREST,
			}





def 			lowerCamelCase_ (				lowerCamelCase__    ):
				lowerCamelCase_						=			(images / 2 + 0.5).clamp(0	, 1    )
				lowerCamelCase_						=			images.cpu().permute(0	, 2	, 3	, 1    ).float().numpy()
				lowerCamelCase_						=			numpy_to_pil(lowerCamelCase__    )
				return images





def 			lowerCamelCase_ (				lowerCamelCase__    ):
				if images.ndim == 3:
								lowerCamelCase_						=			images[None, ...]
				lowerCamelCase_						=			(images * 2_5_5).round().astype("uint8"    )
				if images.shape[-1] == 1:
								# special case for grayscale (single channel) images
								lowerCamelCase_						=			[Image.fromarray(image.squeeze()	, mode="L"    ) for image in images]
				else:
								lowerCamelCase_						=			[Image.fromarray(lowerCamelCase__    ) for image in images]

				return pil_images




from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__   :			List[Any]												=    {
    "configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfig", "ResNetOnnxConfig"]
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__   :			int												=    [
					    "RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "ResNetForImageClassification",
					    "ResNetModel",
					    "ResNetPreTrainedModel",
					    "ResNetBackbone",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__   :			List[Any]												=    [
					    "TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "TFResNetForImageClassification",
					    "TFResNetModel",
					    "TFResNetPreTrainedModel",
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__   :			Union[str, Any]												=    [
					    "FlaxResNetForImageClassification",
					    "FlaxResNetModel",
					    "FlaxResNetPreTrainedModel",
					]

if TYPE_CHECKING:
					from .configuration_resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig, ResNetOnnxConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_resnet import (
										    RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ResNetBackbone,
										    ResNetForImageClassification,
										    ResNetModel,
										    ResNetPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_resnet import (
										    TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFResNetForImageClassification,
										    TFResNetModel,
										    TFResNetPreTrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel


else:
					import sys

					SCREAMING_SNAKE_CASE__   :			Any												=    _LazyModule(__name__, globals()["__file__"], _import_structure)



