o Vñ hšã@s`ddlZddlmZmZmZddlZddlZddl Z ddl m Z ddl mZGdd„deƒZdS)éN)ÚAnyÚDictÚUnion)Ú functional)Ú Transformcs^eZdZdZejjejfZd ‡fdd„ Z de ejjejfde e e fdejfdd „Z‡ZS) ÚToTensora‚[DEPRECATED] Use ``v2.Compose([v2.ToImage(), v2.ToDtype(torch.float32, scale=True)])`` instead. Convert a PIL Image or ndarray to tensor and scale the values accordingly. .. warning:: :class:`v2.ToTensor` is deprecated and will be removed in a future release. Please use instead ``v2.Compose([v2.ToImage(), v2.ToDtype(torch.float32, scale=True)])``. Output is equivalent up to float precision. This transform does not support torchscript. Converts a PIL Image or numpy.ndarray (H x W x C) in the range [0, 255] to a torch.FloatTensor of shape (C x H x W) in the range [0.0, 1.0] if the PIL Image belongs to one of the modes (L, LA, P, I, F, RGB, YCbCr, RGBA, CMYK, 1) or if the numpy.ndarray has dtype = np.uint8 In the other cases, tensors are returned without scaling. .. note:: Because the input image is scaled to [0.0, 1.0], this transformation should not be used when transforming target image masks. See the `references`_ for implementing the transforms for image masks. .. _references: https://github.com/pytorch/vision/tree/main/references/segmentation ÚreturnNcst d¡tƒ ¡dS)NzÕThe transform `ToTensor()` is deprecated and will be removed in a future release. Instead, please use `v2.Compose([v2.ToImage(), v2.ToDtype(torch.float32, scale=True)])`.Output is equivalent up to float precision.)ÚwarningsÚwarnÚsuperÚ__init__)Úself©Ú __class__©úY/var/www/vscode/kcb/lib/python3.10/site-packages/torchvision/transforms/v2/_deprecated.pyr )sÿzToTensor.__init__ÚinptÚparamscCs t |¡S)N)Ú_FÚ to_tensor)r rrrrrÚ transform1s zToTensor.transform)rN)Ú__name__Ú __module__Ú __qualname__Ú__doc__ÚPILÚImageÚnpÚndarrayÚ_transformed_typesr rrÚstrrÚtorchÚTensorrÚ __classcell__rrrrr s 6r)r ÚtypingrrrÚnumpyrÚ PIL.Imagerr!Útorchvision.transformsrrÚtorchvision.transforms.v2rrrrrrÚs