def METHOD_NAME():
    """Test that the LUT optimization pass runs as part of the NPU compilation pipeline."""
    ifm_shape = (1, 4, 4, 4)
    @tf.function
    def get_graph(x):
        weight1 = tf.constant(np.random.uniform(size=(1, 1, 4, 4)), dtype=tf.float32)
        op = tf.nn.conv2d(x, weight1, (1, 1), "VALID")
        op = tf.nn.tanh(op)
        weight2 = tf.constant(np.random.uniform(size=(1, 1, 4, 1)), dtype=tf.float32)
        op = tf.nn.depthwise_conv2d(op, weight2, (1, 1, 1, 1), "VALID")
        return tf.nn.tanh(op)
    mod, _ = infra.get_tflite_graph(get_graph, [ifm_shape])
    mod = partition_for_ethosu(mod)
    mod = relay_to_tir(mod)
    external_gv_name = mod["main"].body.op.name_hint
    prim_func = mod[external_gv_name]
    # Check for hints in the TIR prim func that the LUT optimization pass has ran.
    # If the module was optimized, there should be no identity operations.
    def check_identity(stmt):
        if isinstance(stmt, tvm.tir.expr.Call):
            assert stmt.args[0] != "ethosu_identity"
    tvm.tir.stmt_functor.post_order_visit(prim_func.body, check_identity)