model_logging.py [65:78]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    param_name = "alpha" if model_type == "curve" else "topk"
    param_print = "" if param is None else f" ({param_name} = {param})"
    print(
        f"Test set{param_print}: Average loss: {loss:.4f} | Accuracy: {acc:.4f} | Sparsity: {sparsity:.4f}"
    )

    if metric_dict is not None:
        metric_dict["acc"].append(acc)
        metric_dict["sparsity"].append(sparsity)
        if param_name not in metric_dict:
            metric_dict[param_name] = []
        metric_dict[param_name].append(param)

    return metric_dict
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



model_logging.py [133:146]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    param_name = "alpha" if model_type == "curve" else "topk"
    param_print = "" if param is None else f" ({param_name} = {param})"
    print(
        f"Test set{param_print}: Average loss: {loss:.4f} | Accuracy: {acc:.4f} | Sparsity: {sparsity:.4f}"
    )

    if metric_dict is not None:
        metric_dict["acc"].append(acc)
        metric_dict["sparsity"].append(sparsity)
        if param_name not in metric_dict:
            metric_dict[param_name] = []
        metric_dict[param_name].append(param)

    return metric_dict
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -