code: def test_meter_invalid_model_output(self):
      meter = VideoAccuracyMeter(
          topk=[1, 2], clips_per_video_train=1, clips_per_video_test=2
      )
      # This model output has 3 dimensions instead of expected 2
      model_output = torch.tensor(
          [[[3, 2, 1], [1, 2, 3]], [[-1, -3, -4], [-10, -90, -100]]],
          dtype=torch.float,
      )
      target = torch.tensor([0, 1, 2])
  
      self.meter_invalid_meter_input_test(meter, model_output, target)
  
file_path: ClassyVision/test/meters_video_accuracy_meter_test.py
imports: import torch
  from classy_vision import meters
  from classy_vision.meters import VideoAccuracyMeter
  from test.generic.meter_test_utils import ClassificationMeterTest
label_desc: Use image node_id 4 for calling the TestVideoAccuracyMeter obj's underlying member method code with example usage: obj.test_meter_invalid_model_output() without return types