class_docstr: Test the Metrics aggregator.
class_docstr_tok: ["Test","the","Metrics","aggregator","."]
code: def test_verymultithreaded(self):
      # legacy test, but useful all the same, for ensuring
      # metrics doesn't care about the order things are done
      m = Metrics()
      nt = 128
      ms = [Metrics(shared=m.share()) for _ in range(nt)]
  
      # intentionally just over the int overflow
      for _ in range(32768 + 1):
          ms[random.randint(0, nt - 1)].add("key", SumMetric(1))
      thread_ids = list(range(nt))
      random.shuffle(thread_ids)
      assert m.report()["key"] == 32768 + 1
  
imports: import unittest
  from typing import Dict
  import torch
  import random
  from parlai.core.metrics import AverageMetric, SumMetric, FixedMetric, Metrics, GlobalAverageMetric, MacroAverageMetric, TimerMetric, aggregate_unnamed_reports, aggregate_named_reports, InterDistinctMetric, IntraDistinctMetric, FairseqBleuMetric
  from parlai.core.torch_classifier_agent import ConfusionMatrixMetric, WeightedF1Metric, AUCMetrics
  from parlai.core.torch_generator_agent import PPLMetric
  import parlai.utils.testing
label_desc: Use image node_id 4 for calling the TestMetrics obj's underlying member method code with example usage: obj.test_verymultithreaded() without return types