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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code: def output_metric(self, metric, dataobject):
      preds, trues = self.used_info(dataobject)
      result = self.metric_info(preds, trues)
      return {metric: round(result, self.decimal_place)}
  
file_path: RecBole/recbole/evaluator/base_metric.py
imports: import torch
  from recbole.utils import EvaluatorType
label_desc: Use image node_id 3 for calling the LossMetric obj's underlying member method code with example usage: obj.output_metric(metric, dataobject) and returns: dict