docstr: This test verifies that the meter works as expected on a single
  update + reset + same single update with multilabel target.
docstr_tok: ["This","test","verifies","that","the","meter","works","as","expected","on","a","single","update","+","reset","+","same","single","update","with","multilabel","target","."]
code: def test_single_meter_update_and_reset_multilabel(self) -> None:
      """
      This test verifies that the meter works as expected on a single
      update + reset + same single update with multilabel target.
      """
      meter = AccuracyListMeter(
          num_meters=1, topk_values=[1, 2], meter_names=[]
      )
  
      # Batchsize = 7, num classes = 3, score is a value in {1, 2,
      # 3}...3 is the highest score
      model_output = torch.tensor(
          [
              [3, 2, 1],
              [3, 1, 2],
              [1, 3, 2],
              [1, 2, 3],
              [2, 1, 3],
              [2, 3, 1],
              [1, 3, 2],
          ]
      )
  
      target = torch.tensor(
          [
              [1, 1, 0],
              [0, 0, 1],
              [1, 0, 0],
              [0, 0, 1],
              [0, 1, 1],
              [1, 1, 1],
              [1, 0, 1],
          ]
      )
  
      # 1st, 4th, 5th, 6th sample has top class correct, 2nd and 7th have at least
      # one correct class in top 2.
      expected_value = {"top_1": 4 / 7.0, "top_2": 6 / 7.0}
  
      self.meter_update_and_reset_test(
          meter, model_output, target, expected_value
      )
  
file_path: vissl/tests/test_meter_accuracy.py
imports: import torch
  import vissl.meters
  from classy_vision.meters import build_meter
  from meter_test_utils import ClassificationMeterTest
  from vissl.meters.accuracy_list_meter import AccuracyListMeter
label_desc: Use image node_id 5 for calling the TestAccuracyListMeter obj's underlying member method code with example usage: obj.test_single_meter_update_and_reset_multilabel() without return types