code: def restore_positives(
      neg_samples: List[Dict[str, Any]], indices: List[int]
  ) -> List[Dict[str, Any]]:
      mixed_samples = copy.deepcopy(neg_samples)
  
      for i in indices:
          mixed_samples[i]["perturbed"] = False
          mixed_samples[i]["dialog"][0][0]["steps"] = mixed_samples[i][
              "dialog"
          ][0][0]["original_steps"]
          mixed_samples[i]["dialog"][0][0]["eval_labels"] = [
              "\t".join(mixed_samples[i]["dialog"][0][0]["steps"])
          ]
          mixed_samples[i]["dialog"][0][1]["text"] = "\t".join(
              mixed_samples[i]["dialog"][0][0]["steps"]
          )
      return mixed_samples
  
file_path: ParlAI/projects/roscoe/roscoe_data/restore_data.py
imports: import copy
  import json
  import os
  import random
  from typing import Any, Dict, Iterable, List, Set
  from parlai.core.params import ParlaiParser
label_desc: Use image node_id 2 for calling a global function with example usage: restore_positives(neg_samples, indices) and returns: mixed_samples