code: def _compute(
      self,
      predictions,
      references,
      labels=None,
      pos_label=1,
      average="binary",
      sample_weight=None,
      zero_division="warn",
  ):
      score = recall_score(
          references,
          predictions,
          labels=labels,
          pos_label=pos_label,
          average=average,
          sample_weight=sample_weight,
          zero_division=zero_division,
      )
      return {"recall": float(score) if score.size == 1 else score}
  
imports: from sklearn.metrics import recall_score
  import datasets
label_desc: Use image node_id 2 for calling the Recall obj's underlying member method code with example usage: obj._compute(predictions, references, labels, pos_label, average, sample_weight, zero_division) and returns: dict