code: def evaluate(model, instances, data_iterator, cuda_device):
      _warned_tqdm_ignores_underscores = False
      check_for_gpu(cuda_device)
      with torch.no_grad():
          model.eval()
  
          iterator = data_iterator(
              instances,
              num_epochs=1,
              shuffle=False,
              cuda_device=cuda_device,
          )
          logger.info("Iterating over dataset")
          generator_tqdm = Tqdm.tqdm(
              iterator, total=data_iterator.get_num_batches(instances)
          )
          for batch in generator_tqdm:
              model(**batch)
              metrics = model.get_metrics()
              if not _warned_tqdm_ignores_underscores and any(
                  metric_name.startswith("_") for metric_name in metrics
              ):
                  logger.warning(
                      'Metrics with names beginning with "_" will '
                      "not be logged to the tqdm progress bar."
                  )
                  _warned_tqdm_ignores_underscores = True
              description = (
                  ", ".join(
                      [
                          "%s: %.2f" % (name, value)
                          for name, value in list(metrics.items())
                          if not name.startswith("_")
                      ]
                  )
                  + " ||"
              )
              generator_tqdm.set_description(description, refresh=False)
  
          return model.get_metrics(reset=True)
  
imports: from __future__ import with_statement
  from __future__ import absolute_import
  import argparse
  import logging
  import json
  import torch
  from allennlp.commands.subcommand import Subcommand
  from allennlp.common.checks import check_for_gpu
  from allennlp.common.util import prepare_environment
  from allennlp.common.tqdm import Tqdm
  from allennlp.data import Instance
  from allennlp.data.dataset_readers.dataset_reader import DatasetReader
  from allennlp.data.iterators import DataIterator
  from allennlp.models.archival import load_archive
  from allennlp.models.model import Model
  from io import open
label_desc: Use image node_id 1 for calling a global function with example usage: evaluate(model, instances, data_iterator, cuda_device) and returns: model