docstr: Returns a dictionary of metric attributes {metric_name: {attribute_name: value}}.
  Required attributes: 'direction': 'higher-better' or 'higher-worse'
                       'type': metric type
docstr_tok: ["Returns","a","dictionary","of","metric","attributes","{","metric_name",":","{","attribute_name",":","value","}","}",".","Required","attributes",":","'direction","'",":","'higher-better","'","or","'higher-worse'","'type","'",":","metric","type"]
code: def get_attributes(self):
      """
      Returns a dictionary of metric attributes {metric_name: {attribute_name: value}}.
      Required attributes: 'direction': 'higher-better' or 'higher-worse'
                           'type': metric type
      """
      return {
          self._name: {"direction": "higher-better", "type": "accuracy"}
      }
  
imports: import os
  import json
  import random
  from PIL import Image
  import numpy
  from compression.api import DataLoader, Metric
  from torchvision.transforms import transforms
label_desc: Use image node_id 6 for calling the Accuracy obj's underlying member method code with example usage: obj.get_attributes() and returns: dict