def METHOD_NAME(op):
    """Internal traverse function"""
    # inline all one-to-one-mapping operators except the last stage (output)
    if tag.is_broadcast(op.tag) or "elemwise" in op.tag:
        if op not in s.outputs:
            s[op].compute_inline()
        for tensor in op.input_tensors:
            if isinstance(tensor.op, tvm.te.ComputeOp):
                METHOD_NAME(tensor.op)
    elif op.tag == "bitserial_dense" or "bitserial_dense_unipolar":
        output = op.output(0)
        weight_vec = op.input_tensors[0]
        data_vec = op.input_tensors[1]
        data = data_vec.op.input_tensors[0]
        if "QuantizeInput" in data.op.name:
            data = data.op.input_tensors[0]
        unipolar = output.op.tag == "bitserial_dense_unipolar"
        _schedule(cfg, s, data_vec, weight_vec, output, unipolar)
    else:
        raise RuntimeError(f"Unsupported operator: {op.tag}")