HelinLin

I changed the loss value to nan after using the DPFedAvgAdaptive class

1

### What is your question? My Reproduction Code： strategy = fl.server.strategy.FedAvg( fraction_fit=0.2, fraction_evaluate=0.2, min_fit_clients=2, min_evaluate_clients=2, min_available_clients=5, evaluate_fn=get_evaluate_fn(model, args.toy), on_fit_config_fn=fit_config, on_evaluate_config_fn=evaluate_config, initial_parameters=fl.common.ndarrays_to_parameters(model_parameters), ) strategy_adp = DPFedAvgAdaptive( strategy=strategy, num_sampled_clients=10, init_clip_norm=0.1, noise_multiplier=1.1, server_side_noising=True,...

When adaptive cropping, my l2 norm is very high

2

### What is your question? def _get_update_norm(update: NDArrays) -> float: flattened_update = update[0] for i in range(1, len(update)): flattened_update = np.append(flattened_update, update[i]) # type: ignore return float(np.sqrt(np.sum(np.square(flattened_update)))) def add_gaussian_noise(update: NDArrays,...