code: def get_model_select_metric(self, metrics):
      if self.model_select_metric_key == "em":
          return metrics.exact_match
      else:
          return metrics.loss[self.model_select_metric_key]
  
imports: from collections import defaultdict
  from typing import Dict, List
  import numpy
  import torch
  from pytext.common.constants import BatchContext, DatasetFieldName, Stage
  from pytext.data.tensorizers import Tensorizer
  from pytext.metric_reporters.channel import ConsoleChannel
  from pytext.metric_reporters.seq2seq_compositional import CompositionalSeq2SeqFileChannel, Seq2SeqCompositionalMetricReporter
  from pytext.metric_reporters.seq2seq_metric_reporter import Seq2SeqFileChannel, Seq2SeqMetricReporter
  from pytext.metric_reporters.seq2seq_utils import stringify
  from pytext.metrics import safe_division
  from pytext.metrics.mask_metrics import compute_length_metrics
  from pytext.metrics.seq2seq_metrics import MaskedSeq2SeqTopKMetrics
label_desc: Use image node_id 9 for calling the MaskedSeq2SeqTopKMetricReporter obj's underlying member method code with example usage: obj.get_model_select_metric(metrics) and returns: metrics, metrics