code: def test_get_explore_eval_stats():
      vw = vowpalwabbit.Workspace(
          "--cb_explore_adf --explore_eval --dsjson --extra_metrics"
      )
  
      ex_l_str = '{"_label_cost":-0.9,"_label_probability":0.5,"_label_Action":1,"_labelIndex":0,"o":[{"v":1.0,"EventId":"38cbf24f-70b2-4c76-aa0c-970d0c8d388e","ActionTaken":false}],"Timestamp":"2020-11-15T17:09:31.8350000Z","Version":"1","EventId":"38cbf24f-70b2-4c76-aa0c-970d0c8d388e","a":[1,2],"c":{ "GUser":{"id":"person5","major":"engineering","hobby":"hiking","favorite_character":"spock"}, "_multi": [ { "TAction":{"topic":"SkiConditions-VT"} }, { "TAction":{"topic":"HerbGarden"} } ] },"p":[0.5,0.5],"VWState":{"m":"N/A"}}\n'
      ex_l = vw.parse(ex_l_str)
      vw.learn(ex_l)
      vw.finish_example(ex_l)
      learner_metric_dict = vw.get_learner_metrics()
      assert learner_metric_dict["weighted_update_count"] == 1.0
      assert (
          learner_metric_dict["average_accepted_example_weight"] == 1.0
      )
  
imports: import os
  from pathlib import Path
  import vowpalwabbit
  from vowpalwabbit import Workspace
  import pytest
  import warnings
  import filecmp
label_desc: Use image node_id 52 for calling a global function with example usage: test_get_explore_eval_stats() without return types