class_docstr: Graph compiler with auxiliary graph to compose with the topology.
  The supervision graph contains the auxiliary graph information.
code: def compile(
      self,
      targets: torch.Tensor,
      target_lengths: torch.Tensor,
      aux_graph: Optional["k2.Fsa"] = None,
  ) -> "k2.Fsa":
      if aux_graph is None and self.base_graph is None:
          raise ValueError(
              f"At least one of aux_graph and self.base_graph must be set: {aux_graph}, {self.base_graph}"
          )
      elif aux_graph is not None:
          self.base_graph = intersect_with_self_loops(
              self.ctc_topo_inv, aux_graph
          ).invert()
          self.base_graph = k2.arc_sort(self.base_graph).to(self.device)
      return super().compile(targets, target_lengths)
  
imports: from typing import Optional, Tuple
  import torch
  from nemo.collections.asr.parts.k2.utils import add_self_loops, compose_with_self_loops, intersect_with_self_loops
  from nemo.core.utils.k2_guard import k2
label_desc: Use image node_id 2 for calling the CtcNumGraphCompiler obj's underlying member method code with example usage: obj.compile(targets, target_lengths, aux_graph) and returns: super