code: def add_batch_stats(
      self, n_batches, preds, targets, scores, loss, m_input, **context
  ):
      # target = 1 means the first response was ranked higher than the second response
      # however, our training data is tuples of {pos_response, neg_response} pairs
      # i.e, pos_response is always the first response, neg_response is always the
      # second response. so target = 1 for all cases
      targets = [1] * preds.shape[0]
      super().add_batch_stats(
          n_batches, preds, targets, scores, loss, m_input, **context
      )
  
file_path: pytext/pytext/metric_reporters/pairwise_ranking_metric_reporter.py
imports: from pytext.data import CommonMetadata
  from pytext.metrics import compute_pairwise_ranking_metrics
  from .channel import ConsoleChannel
  from .metric_reporter import MetricReporter
label_desc: Use image node_id 3 for calling the PairwiseRankingMetricReporter obj's underlying member method code with example usage: obj.add_batch_stats(n_batches, preds, targets, scores, loss, m_input) without return types