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 For this test
      # to work, top-1 / top-2 values of meter0 / meter1 should be
      # different
      meters = [
          PrecisionAtKListMeter(
              num_meters=1, topk_values=[1, 2], meter_names=[]
          ),
          PrecisionAtKListMeter(
              num_meters=1, topk_values=[1, 2], meter_names=[]
          ),
      ]
      model_outputs = [
          torch.tensor(
              [[0.05, 0.4, 0.05], [0.2, 0.65, 0.15], [0.33, 0.33, 0.34]]
          ),
          torch.tensor(
              [[0.05, 0.4, 0.05], [0.15, 0.65, 0.2], [0.4, 0.2, 0.4]]
          ),
      ]
      targets = [
          torch.tensor([[0, 1, 0], [1, 0, 0], [1, 1, 0]]),
          torch.tensor([[0, 1, 0], [0, 1, 0], [0, 1, 0]]),
      ]
  
      # Second update's expected value
      expected_value = {"top_1": 2 / 3.0, "top_2": 2 / 6.0}
  
      self.meter_get_set_classy_state_test(
          meters, model_outputs, targets, expected_value
      )
  
file_path: vissl/tests/test_meter_precision.py
imports: import torch
  import vissl.meters
  from classy_vision.meters import build_meter
  from meter_test_utils import ClassificationMeterTest
  from vissl.meters.precision_at_k_list_meter import PrecisionAtKListMeter
label_desc: Use image node_id 4 for calling the TestPrecisionAtKListMeter obj's underlying member method code with example usage: obj.test_meter_get_set_classy_state_test() without return types