code: def _path(opt):
      # Build the data if it doesn't exist.
      build(opt)
      # for now train, valid and test will be identical, will change with more data.
      dt = opt["datatype"].split(":")[0]
      if (
          opt.get("light_unseen_test", False) is True
          or opt.get("light_unseen_test", False) == "True"
      ):
          if dt == "test":
              dt = "test_unseen"
          else:
              raise ValueError("No unseen train or valid.")
      fields = [
          "taskname",
          "setting",
          "objects",
          "person_names",
          "persona",
          "emote",
          "speech",
          "action",
          "affordances",
          "repeat",
          "cands",
          "current_self_output",
          "clip_cands",
          "speech_prefix",
      ]
      fpath = ""
      for f in fields:
          fpath += f + str(opt["light_use_" + f]) + "_"
      return os.path.join(
          opt["datapath"],
          "light_dialogue",
          fpath[:-1],
          opt["light_label_type"] + "_" + dt + ".txt",
      )
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from parlai.core.teachers import ParlAIDialogTeacher
  from .build import build
  import copy
  import os
  import random
label_desc: Use image node_id 1 for calling a global function with example usage: _path(opt) and returns: os