Function evaluate

training/mlp_train.py:115–126

(model: nn.Module, loader: DataLoader, device: torch.device)

def evaluate(model: nn.Module, loader: DataLoader, device: torch.device) -> float:
    model.eval()
    correct = 0
    total = 0
    with torch.no_grad():
        for data, target in loader:
            data, target = data.to(device), target.to(device)
            output = model(data)
            pred = output.argmax(dim=1)
            correct += (pred == target).sum().item()
            total += target.size(0)
    return correct / total


def parse_hidden_dims(raw: Sequence[int]) -> list[int]: