code: def test_double_meter_update_and_reset(self) -> None:
      meter = AccuracyListMeter(
          num_meters=1, topk_values=[1, 2], meter_names=[]
      )
  
      # Batchsize = 3, num classes = 3, score is a value in {1, 2,
      # 3}...3 is the highest score...two batches in this test
      model_outputs = [
          torch.tensor([[3, 2, 1], [3, 1, 2], [1, 3, 2]]),
          torch.tensor([[3, 2, 1], [1, 3, 2], [1, 3, 2]]),
      ]
  
      # Class 0 is the correct class for sample 1, class 2 for
      # sample 2, etc, in both batches
      targets = [torch.tensor([0, 1, 2]), torch.tensor([0, 1, 2])]
  
      # First batch has top-1 accuracy of 1/3.0, top-2 accuracy of 2/3.0
      # Second batch has top-1 accuracy of 2/3.0, top-2 accuracy of 3/3.0
      expected_value = {"top_1": 3 / 6.0, "top_2": 5 / 6.0}
  
      self.meter_update_and_reset_test(
          meter, model_outputs, targets, 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 3 for calling the TestAccuracyListMeter obj's underlying member method code with example usage: obj.test_double_meter_update_and_reset() without return types