l with the same input
        types. See also below the ``antialias`` parameter, which can help making the output of PIL images and tensors
        closer.

    Args:
        img (PIL Image or Tensor): Image to be resized.
        size (sequence or int): Desired output size. If size is a sequence like
            (h, w), the output size will be matched to this. If size is an int,
            the smaller edge of the image will be matched to this number maintaining
            the aspect ratio. i.e, if height > width, then image will be rescaled to
            :math:`\left(\text{size} \times \frac{\text{height}}{\text{width}}, \text{size}\right)`.

            .. note::
                In torchscript mode size as single int is not supported, use a sequence of length 1: ``[size, ]``.
        interpolation (InterpolationMode): Desired interpolation enum defined by
            :class:`torchvision.transforms.InterpolationMode`.
            Default is ``InterpolationMode.BILINEAR``. If input is Tensor, only ``InterpolationMode.NEAREST``,
            ``InterpolationMode.NEAREST_EXACT``, ``InterpolationMode.BILINEAR`` and ``InterpolationMode.BICUBIC`` are
            supported.
            The corresponding Pillow integer constants, e.g. ``PIL.Image.BILINEAR`` are accepted as well.
        max_size (int, optional): The maximum allowed for the longer edge of
            the resized image: if the longer edge of the image is greater
            than ``max_size`` after being resized according to ``size``, then
            the image is resized again so that the longer edge is equal to
            ``max_size``. As a result, ``size`` might be overruled, i.e. the
            smaller edge may be shorter than ``size``. This is only supported
            if ``size`` is an int (or a sequence of length 1 in torchscript
            mode).
        antialias (bool, optional): Whether to apply antialiasing.
            It only affects **tensors** with bilinear or bicubic modes and it is
            ignored otherwise: on PIL images, antialiasing is always applied on
            bilinear or bicubic modes; on other modes (for PIL images and
            tensors), antialiasing makes no sense and this parameter is ignored.
            Possible values are:

            - ``True``: will apply antialiasing for bilinear or bicubic modes.
              Other mode aren't affected. This is probably what you want to use.
            - ``False``: will not apply antialiasing for tensors on any mode. PIL
              images are still antialiased on bilinear or bicubic modes, because
              PIL doesn't support no antialias.
            - ``None``: equivalent to ``False`` for tensors and ``True`` for
              PIL images. This value exists for legacy reasons and you probably
              don't want to use it unless you really know what you are doing.

            The current default is ``None`` **but will change to** ``True`` **in
            v0.17** for the PIL and Tensor backends to be consistent.

    Returns:
        PIL Image or Tensor: Resized image.
    ú_Argument interpolation should be a InterpolationMode or a corresponding Pillow integer constant)