def METHOD_NAME():
    """Legalizes QNN ops. As opposed to Relay Legalize, this one legalizes only QNN ops. One can
    register a transformation/legalization function for an op by using the FTVMQnnLegalize attr_name
    for FTVMLegalize op attribute. The isolation of QNN and Relay Legalize gives us separation of
    concerns, leading to a better software practice. The legalization can be configured to happen
    per target. An example of this type of legalization is shown below.
    Examples
    ________
    Suppose the original graph is as follows
            data(u8)  weight(u8)
                |       |
                |       |
               qnn.conv2d (int32)
                   |
                   |
                nn.relu (int32)
    Now, we know that Intel Cascade Lake has VNNI instructions to speedup convolution. However, it
    only works on u8 x i8 inputs. So, here, we can use QNN Legalize to transform the above graph as
    follows
            data(u8)  weight(u8)
               |          |
               |          |
               |     requantize(i8)
               |        |
               |        |
               qnn.conv2d (int32)
                   |
                   |
                 nn.relu (int32)
    In this legalization, since we have isolated legalization for QNN ops, it will only trigger the
    transformation for qnn.conv2d (and not nn.relu). This pass can be followed by CanonicalizeOps to
    further lower the qnn.requantize and qnn.conv2d into an expr containing only Relay ops.
    Returns
    -------
    ret : tvm.transform.Pass
        The registered pass that legalizes QNN ops.
    """
    return relay.transform.METHOD_NAME("FTVMQnnLegalize")