if you carefully choose your privacy parameters model, optimizer, train_loader = privacy_engine.make_private_with_epsilon( module=model, # the model you want to train with DP optimizer=optimizer, data_loader=train_loader, epochs=EPOCHS, target_epsilon=EPSILON, # privacy budget target_delta=DELTA, max_grad_norm=MAX_GRAD_NORM, # clipping value )