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# Source code for torchvision.tv_tensors._video

    from __future__ import annotations

    from typing import Any, Optional, Union

    import torch

    from ._tv_tensor import TVTensor

    class Video(TVTensor):
        """[BETA] :class:`torch.Tensor` subclass for videos.

        Args:
            data (tensor-like): Any data that can be turned into a tensor with :func:`torch.as_tensor`.
            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 video 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``.
        """

        def __new__(
            cls,
            data: Any,
            *,
            dtype: Optional[torch.dtype] = None,
            device: Optional[Union[torch.device, str, int]] = None,
            requires_grad: Optional[bool] = None,
        ) -> Video:
            tensor = cls._to_tensor(data, dtype=dtype, device=device, requires_grad=requires_grad)
            if data.ndim < 4:
                raise ValueError
            return tensor.as_subclass(cls)

        def __repr__(self, *, tensor_contents: Any = None) -> str:  # type: ignore[override]
            return self._make_repr()

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