Hey. As you can see here, the loss function ignores labels as long as the network is in eval mode, and, as you can see here, for testing the network indeed is in eval mode. So, no worries ;)
Hey. As you can see here, the loss function ignores labels as long as the network is in eval mode, and, as you can see here, for testing the network indeed is in eval mode. So, no worries ;)
In the trainner.test(), it seems the calculation of anomaly_scores of test data need to use its groundtruth label? It may be unresonable?