class_docstr: Managing class for the acute evaluator process.
  
  Relevant args are parsed in the `setup_args` function above.
class_docstr_tok: ["Managing","class","for","the","acute","evaluator","process",".","Relevant","args","are","parsed","in","the","`","setup_args","`","function","above","."]
docstr: Return the data for an agent already assigned to a particular unit.
docstr_tok: ["Return","the","data","for","an","agent","already","assigned","to","a","particular","unit","."]
code: def get_init_data_for_agent(
      self, agent: "Agent"
  ) -> List[PairingsDict]:
      """
      Return the data for an agent already assigned to a particular unit.
      """
      init_state = agent.state.get_init_state()
      if init_state is not None:
          # reconnecting agent, give what we've got
          return init_state
      else:
          worker = agent.get_worker()
          task_data = self.get_new_task_data(worker.db_id)
          agent.state.set_init_state(task_data)
          self.unit_agent_map[agent.get_unit().db_id] = (
              worker.db_id,
              task_data,
          )
          return task_data
  
imports: import json
  import queue
  import random
  from typing import List, Any, Dict, Tuple, Set, TYPE_CHECKING
  from mephisto.utils.logger_core import get_logger
  from mephisto.abstractions.blueprint import SharedTaskState, TaskRunner
  from omegaconf import DictConfig
label_desc: Use image node_id 13 for calling the AcuteEvalRunner obj's underlying member method code with example usage: obj.get_init_data_for_agent(agent) and returns: init_state, task_data