khVddlmZddlmZmZmZddlZddlZddl m Z Gdde Z y)) annotations)AnyOptionalUnionN)TVTensorcBeZdZdZdddd ddZddddZy) Imagea:class:`torch.Tensor` subclass for images with shape ``[..., C, H, W]``. .. note:: In the :ref:`transforms `, ``Image`` instances are largely interchangeable with pure :class:`torch.Tensor`. See :ref:`this note ` for more details. Args: data (tensor-like, PIL.Image.Image): Any data that can be turned into a tensor with :func:`torch.as_tensor` as well as PIL images. dtype (torch.dtype, optional): Desired data type. If omitted, will be inferred from ``data``. device (torch.device, optional): Desired device. If omitted and ``data`` is a :class:`torch.Tensor`, the device is taken from it. Otherwise, the image is constructed on the CPU. requires_grad (bool, optional): Whether autograd should record operations. If omitted and ``data`` is a :class:`torch.Tensor`, the value is taken from it. Otherwise, defaults to ``False``. Ndtypedevice requires_gradc.t|tjjrddlm}|j |}|j ||||}|jdkrt|jdk(r|jd}|j|S)Nr) functionalr ) isinstancePILr torchvision.transforms.v2r pil_to_tensor _to_tensorndim ValueError unsqueeze as_subclass)clsdatar r rFtensors Y/var/www/teggl/fontify/venv/lib/python3.12/site-packages/torchvision/tv_tensors/_image.py__new__z Image.__new__s| dCIIOO , A??4(DE&P]^ ;;?  [[A %%a(F!!#&&)tensor_contentsc"|jS)N) _make_repr)selfr"s r__repr__zImage.__repr__4s  r!) rrr zOptional[torch.dtype]r z'Optional[Union[torch.device, str, int]]rzOptional[bool]returnr )r"rr'str)__name__ __module__ __qualname____doc__r r&r!rr r sQ.(,:>(, ''% ' 8 ' & ' '*26!r!r ) __future__rtypingrrr PIL.Imagertorch _tv_tensorrr r-r!rr3s#"'' *!H*!r!