docstr: Computes the metric based on it's accumulated state.
  This is called at the end of each epoch.
  :return: the actual quantity of interest
docstr_tok: ["Computes","the","metric","based","on","it","'s","accumulated","state",".","This","is","called","at","the","end","of","each","epoch",".",":","return",":","the","actual","quantity","of","interest"]
code: def compute(self):
      """
      Computes the metric based on it's accumulated state.
      This is called at the end of each epoch.
      :return: the actual quantity of interest
      """
      pass
  
file_path: DeepKE/src/deepke/relation_extraction/standard/tools/metrics.py
imports: import torch
  import numpy
  from abc import ABCMeta, abstractmethod
  from sklearn.metrics import precision_recall_fscore_support
label_desc: Use image node_id 4 for calling the Metric obj's underlying member method code with example usage: obj.compute() without return types