def get_norm(norm, out_channels):
    """
    Args:
        norm (str or callable): either one of BN, SyncBN, FrozenBN, GN;
            or a callable that takes a channel number and returns
            the normalization layer as a nn.Layer.
        out_channels (int): out_channels
    Returns:
        nn.Layer or None: the normalization layer
    """
    if norm is None:
        return None
    if isinstance(norm, str):
        if len(norm) == 0:
            return None
        norm = {
            "BN": nn.BatchNorm2d,
            "SyncBN": nn.SyncBatchNorm,
            "FrozenBN": FrozenBatchNorm,
        }[norm]
    return norm(out_channels)
Args:
norm (str or callable): either one of BN, SyncBN, FrozenBN, GN;
or a callable that takes a channel number and returns
the normalization layer as a nn.Layer.
out_channels (int): out_channels
Returns:
nn.Layer or None: the normalization layer
ptstructure/vqa/pytorchnlp/transformers/layoutxlm/visual_backbone.py