def METHOD_NAME(self):
    trainer, model = setup_trainer_and_model_detection("test_detection_extreme_batch_with_metric_sanity")
    self.od_training_params["phase_callbacks"] = [
        ExtremeBatchDetectionVisualizationCallback(
            classes=["1"],
            metric=DetectionMetrics_050(
                normalize_targets=True,
                post_prediction_callback=PPYoloEPostPredictionCallback(score_threshold=0.03, nms_top_k=1000, max_predictions=300, nms_threshold=0.65),
                num_cls=1,
            ),
            metric_component_name="mAP@0.50",
            post_prediction_callback=PPYoloEPostPredictionCallback(score_threshold=0.03, nms_top_k=1000, max_predictions=300, nms_threshold=0.65),
        )
    ]
    trainer.train(model=model, training_params=self.od_training_params, train_loader=detection_test_dataloader(), valid_loader=detection_test_dataloader())