def METHOD_NAME(self, iter_dataloader, batch_idx) -> Dict[str, Any]:
    """
    Calculate validation metrics for a batch and return them as a dictionary.
    This method is not necessary if the user defines evaluate_full_dataset().
    """
    batch = self.context.to_device(next(iter_dataloader))
    images, labels = batch[0], batch[1]
    if self.fp16:
        images = images.half()
    outputs = self.model_engine(images)
    _, predicted = torch.max(outputs.data, 1)
    total = labels.size(0)
    correct = (predicted == labels).sum().item()
    self.reducer.update((correct, total))
    return {}