nvflare.edge.widgets.evaluator module

class GlobalEvaluator(model_path: str | Module, eval_frequency: int = 1, torchvision_dataset: Dict | None = None, custom_dataset: Dict | None = None)

Bases: Widget

Initialize the evaluator with either a dataset path or custom dataset.

Parameters:

• model_path – PyTorch model to evaluate

• eval_frequency – Frequency of evaluation (evaluate every N rounds)

• torchvision_dataset – Torchvision dataset (for standard datasets like CIFAR10)

• custom_dataset – Dictionary containing ‘data’ and ‘labels’ tensors

evaluate(_event_type: str, fl_ctx: FLContext)