ision.models.detection.SSDLite320_MobileNet_V3_Large_Weights`, optional): The
            pretrained weights to use. See
            :class:`~torchvision.models.detection.SSDLite320_MobileNet_V3_Large_Weights` below for
            more details, and possible values. By default, no pre-trained
            weights are used.
        progress (bool, optional): If True, displays a progress bar of the
            download to stderr. Default is True.
        num_classes (int, optional): number of output classes of the model
            (including the background).
        weights_backbone (:class:`~torchvision.models.MobileNet_V3_Large_Weights`, optional): The pretrained
            weights for the backbone.
        trainable_backbone_layers (int, optional): number of trainable (not frozen) layers
            starting from final block. Valid values are between 0 and 6, with 6 meaning all
            backbone layers are trainable. If ``None`` is passed (the default) this value is
            set to 6.
        norm_layer (callable, optional): Module specifying the normalization layer to use.
        **kwargs: parameters passed to the ``torchvision.models.detection.ssd.SSD``
            base class. Please refer to the `source code
            <https://github.com/pytorch/vision/blob/main/torchvision/models/detection/ssd.py>`_
            for more details about this class.

    .. autoclass:: torchvision.models.detection.SSDLite320_MobileNet_V3_Large_Weights
        :members:
    