\hbSSKrSSKJrJr SSKrSSKrSSKrSSK J r SSK J r "SS\ 5rg)N)AnyUnion) functional) Transformc^\rSrSrSr\R R \R4r S U4Sjjr S\ \R R \R4S\ \ \4S\R 4SjrSrU=r$) ToTensor aB[DEPRECATED] Use ``v2.Compose([v2.ToImage(), v2.ToDtype(torch.float32, scale=True)])`` instead. Convert a PIL Image or ndarray to tensor and scale the values accordingly. .. warning:: :class:`v2.ToTensor` is deprecated and will be removed in a future release. Please use instead ``v2.Compose([v2.ToImage(), v2.ToDtype(torch.float32, scale=True)])``. Output is equivalent up to float precision. This transform does not support torchscript. Converts a PIL Image or numpy.ndarray (H x W x C) in the range [0, 255] to a torch.FloatTensor of shape (C x H x W) in the range [0.0, 1.0] if the PIL Image belongs to one of the modes (L, LA, P, I, F, RGB, YCbCr, RGBA, CMYK, 1) or if the numpy.ndarray has dtype = np.uint8 In the other cases, tensors are returned without scaling. .. note:: Because the input image is scaled to [0.0, 1.0], this transformation should not be used when transforming target image masks. See the `references`_ for implementing the transforms for image masks. .. _references: https://github.com/pytorch/vision/tree/main/references/segmentation returncN>[R"S5 [TU] 5 g)NzThe transform `ToTensor()` is deprecated and will be removed in a future release. Instead, please use `v2.Compose([v2.ToImage(), v2.ToDtype(torch.float32, scale=True)])`.Output is equivalent up to float precision.)warningswarnsuper__init__)self __class__s _/var/www/fran/franai/venv/lib/python3.13/site-packages/torchvision/transforms/v2/_deprecated.pyrToTensor.__init__)s!  : inptparamsc.[R"U5$)N)_F to_tensor)rrrs r transformToTensor.transform1s||D!!r)r N)__name__ __module__ __qualname____firstlineno____doc__PILImagenpndarray_transformed_typesrrdictstrrtorchTensorr__static_attributes__ __classcell__)rs@rrr sk4))//2::6"eCIIOORZZ$?@"$sTWx."]b]i]i""rr)r typingrrnumpyr$ PIL.Imager"r)torchvision.transformsrrtorchvision.transforms.v2rrrrrr2s& 3/&"y&"r