class_docstr: :class:`LossMetric` is a base object of loss based metrics and AUC. If you want to
  implement an loss based metric, you can inherit this class.
  
  Args:
      config (Config): The config of evaluator.
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docstr: Get scores that model predicted and the ground truth.
docstr_tok: ["Get","scores","that","model","predicted","and","the","ground","truth","."]
code: def used_info(self, dataobject):
      """Get scores that model predicted and the ground truth."""
      preds = dataobject.get("rec.score")
      trues = dataobject.get("data.label")
  
      return preds.squeeze(-1).numpy(), trues.squeeze(-1).numpy()
  
file_path: RecBole/recbole/evaluator/base_metric.py
imports: import torch
  from recbole.utils import EvaluatorType
label_desc: Use image node_id 2 for calling the LossMetric obj's underlying member method code with example usage: obj.used_info(dataobject) and returns: preds,  trues