code: def gather_results(
      model, val_iter, field, world_size, optional_names=[]
  ):
      loss, predictions, answers, outputs = compute_validation_outputs(
          model, val_iter, field, optional_names=optional_names
      )
      clip = get_clip(val_iter)
      if (
          not hasattr(val_iter.dataset.examples[0], "squad_id")
          and not hasattr(val_iter.dataset.examples[0], "wikisql_id")
          and not hasattr(val_iter.dataset.examples[0], "woz_id")
      ):
          answers = all_reverse(answers, world_size, field, clip)
      return (
          loss,
          all_reverse(predictions, world_size, field, clip),
          answers,
          [all_reverse(x, world_size, field, clip) for x in outputs],
      )
  
file_path: decanlp/validate.py
imports: import torch
  from util import pad
  from metrics import compute_metrics
label_desc: Use image node_id 4 for calling a global function with example usage: gather_results(model, val_iter, field, world_size, optional_names) and returns: loss,  all_reverse,  answers,  unknown