def METHOD_NAME(self):
    data_sample = self.get_pose_data_sample()
    # test gt_instances
    data_sample.gt_instances = InstanceData()
    # test gt_fields
    data_sample.gt_fields = PixelData()
    # test multilevel gt_fields
    data_sample = self.get_pose_data_sample(multilevel=True)
    data_sample.gt_fields = MultilevelPixelData()
    # test pred_instances as pytorch tensor
    pred_instances_data = dict(
        keypoints=torch.rand(1, 17, 2), scores=torch.rand(1, 17, 1))
    data_sample.pred_instances = InstanceData(**pred_instances_data)
    self.assertTrue(
        self._equal(data_sample.pred_instances.keypoints,
                    pred_instances_data['keypoints']))
    self.assertTrue(
        self._equal(data_sample.pred_instances.scores,
                    pred_instances_data['scores']))
    # test pred_fields as numpy array
    pred_fields_data = dict(heatmaps=np.random.rand(17, 64, 48))
    data_sample.pred_fields = PixelData(**pred_fields_data)
    self.assertTrue(
        self._equal(data_sample.pred_fields.heatmaps,
                    pred_fields_data['heatmaps']))
    # test to_tensor
    data_sample = data_sample.to_tensor()
    self.assertTrue(
        self._equal(data_sample.pred_fields.heatmaps,
                    torch.from_numpy(pred_fields_data['heatmaps'])))