def vgg(depth: int, batch_normalization=False, pretrained=False) -> Module:
    """
    Wrapper for VGG net of verious depths availble in the pytorchcv package.
    VGG is only availabe for imagenet.

    :param depth: Depth of the model, one of (11, 13, 16, 19)
    :param batch_normalization: include batch normalizaion layers
    :param pretrained: loads model pretrained on imagnet
    """
    available_depths = [11, 13, 16, 19]
    if depth not in available_depths:
        raise ValueError(
            f"Depth {depth} not available, " f"availble depths are {available_depths}"
        )

    name = f"vgg{depth}"
    if batch_normalization:
        name = f"bn_{name}"

    return ptcv_get_model(name, pretrained=pretrained)

    Wrapper for VGG net of verious depths availble in the pytorchcv package.
    VGG is only availabe for imagenet.

    :param depth: Depth of the model, one of (11, 13, 16, 19)
    :param batch_normalization: include batch normalizaion layers
    :param pretrained: loads model pretrained on imagnet
    
avalanche/models/pytorchcv_wrapper.py