def METHOD_NAME():
    """Check multiply operator with two inputs is not offloaded."""
    np.random.seed(0)
    shape = (1, 4, 5, 6)
    dtype = "int8"
    iinfo = np.iinfo(dtype)
    data_min = iinfo.min
    data_max = iinfo.max
    input_zp = np.random.randint(data_min, data_max)
    input_sc = np.random.random() * 2
    input2_zp = np.random.randint(data_min, data_max)
    input2_sc = np.random.random() * 2
    output_zp, output_sc = tei.get_conv2d_qnn_params(
        dtype, input_zp, input_sc, input2_zp, input2_sc, 1, 1, shape[3]
    )
    x = relay.var("x", shape=shape, dtype=dtype)
    y = relay.var("y", shape=shape, dtype=dtype)
    model = relay.qnn.op.mul(
        x,
        y,
        relay.const(input_sc, "float32"),
        relay.const(input_zp, "int32"),
        relay.const(input2_sc, "float32"),
        relay.const(input2_zp, "int32"),
        relay.const(output_sc, "float32"),
        relay.const(output_zp, "int32"),
    )
    expected_host_ops = 1
    npu_partitions = 0
    for npu in [False, True]:
        mod = tei.make_module(model, {})
        tei.build(
            mod,
            {},
            npu=npu,
            expected_host_ops=expected_host_ops,
            npu_partitions=npu_partitions,
        )