%`iVddlmZddlmZddlZddlZddlmZGddeZ dS)) annotations)AnyN)TVTensorc$eZdZdZdddddd ZdS)Maska:class:`torch.Tensor` subclass for segmentation and detection masks with shape ``[..., H, W]``. 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 mask 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_graddatarr torch.dtype | Noner torch.device | str | int | Noner bool | Nonereturnct|tjjrddlm}||}|||||}||S)Nr) functionalr ) isinstancePILImagetorchvision.transforms.v2r pil_to_tensor _to_tensor as_subclass)clsr r r r Ftensors p/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/torchvision/tv_tensors/_mask.py__new__z Mask.__new__sk dCIO , , ) A A A A A A??4((DE&P]^^!!#&&&) r rr rr rr rrr)__name__ __module__ __qualname____doc__rr rrr sG  "%)26%) ''''''''r r) __future__rtypingr PIL.Imagertorch _tv_tensorrrr%r rr+s"""""" '''''8'''''r