code: def test_meter_get_set_classy_state_test(self) -> None:
      # In this test we update meter0 with model_output0 & target0
      # and we update meter1 with model_output1 & target1 then
      # transfer the state from meter1 to meter0 and validate they
      # give same expected value.
      # Expected value is the expected value of meter1
      meters = [
          AccuracyListMeter(
              num_meters=1, topk_values=[1, 2], meter_names=[]
          ),
          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
      model_outputs = [
          torch.tensor([[1, 2, 3], [1, 2, 3], [2, 3, 1]]),
          torch.tensor([[3, 2, 1], [3, 1, 2], [1, 3, 2]]),
      ]
  
      # Class 0 is the correct class for sample 1, class 2 for sample 2, etc
      targets = [torch.tensor([0, 1, 2]), torch.tensor([0, 1, 2])]
  
      # Value for second update
      expected_value = {"top_1": 1 / 3.0, "top_2": 2 / 3.0}
  
      self.meter_get_set_classy_state_test(
          meters, 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 6 for calling the TestAccuracyListMeter obj's underlying member method code with example usage: obj.test_meter_get_set_classy_state_test() without return types