def METHOD_NAME(self, batch: TorchData) -> 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().
    """
    # TODO: Perform your evaluation step
    batch = cast(Tuple[torch.Tensor, torch.Tensor], batch)
    data, labels = batch
    output = self.model(data)
    # Log predictions to our custom reducer for aggregation
    self.predictions.update(output.argmax(dim=1))
    # TODO: Optionally log metrics to Determined
    accuracy = accuracy_rate(output, labels)
    return {"validation_accuracy": accuracy, "validation_error": 1.0 - accuracy}