sockeye/loss.py [66:126]:
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    @abstractmethod
    def create_metric(self) -> 'LossMetric':
        """
        Create an instance of the EvalMetric that corresponds to this Loss function.
        """
        raise NotImplementedError()

    @property
    def metric(self) -> 'LossMetric':
        if self._metric is None:
            self._metric = self.create_metric()
        return self._metric

    @property
    def weight(self) -> float:
        return self._weight

    @property
    def name(self) -> str:
        return self._name

    @property
    def output_name(self) -> str:
        return self._output_name

    @property
    def label_name(self) -> str:
        return self._label_name


class LossMetric(ABC):
    def __init__(self, name: str, short_name: Optional[str] = None, prefix: str = '') -> None:
        self._name = prefix + name
        self._short_name = prefix + short_name if short_name else self._name
        self._sum = 0.0
        self._num_inst = 0.0

    def __repr__(self):
        return "%s(%.2f/%.2f=%.2f)" % (self.name, self._sum, self._num_inst, self.get())

    def __str__(self):
        return "%s=%f" % (self.short_name, self.get())

    @property
    def name(self):
        return self._name

    @property
    def short_name(self) -> str:
        return self._short_name

    def update(self, loss, num_samples):
        self._sum += loss
        self._num_inst += num_samples

    def get(self) -> float:
        return self._sum / self._num_inst if self._num_inst else float('nan')

    def reset(self):
        self._sum = 0.0
        self._num_inst = 0.0
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sockeye/loss_pt.py [64:125]:
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    @abstractmethod
    def create_metric(self) -> 'LossMetric':
        """
        Create an instance of the EvalMetric that corresponds to this Loss function.
        """
        raise NotImplementedError()

    @property
    def metric(self) -> 'LossMetric':
        if self._metric is None:
            self._metric = self.create_metric()
        return self._metric

    @property
    def weight(self) -> float:
        return self._weight

    @property
    def name(self) -> str:
        return self._name

    @property
    def output_name(self) -> str:
        return self._output_name

    @property
    def label_name(self) -> str:
        return self._label_name


class LossMetric(ABC):

    def __init__(self, name: str, short_name: Optional[str] = None, prefix: str = '') -> None:
        self._name = prefix + name
        self._short_name = prefix + short_name if short_name else self._name
        self._sum = 0.0
        self._num_inst = 0.0

    def __repr__(self):
        return "%s(%.2f/%.2f=%.2f)" % (self.name, self._sum, self._num_inst, self.get())

    def __str__(self):
        return "%s=%f" % (self.short_name, self.get())

    @property
    def name(self):
        return self._name

    @property
    def short_name(self) -> str:
        return self._short_name

    def update(self, loss, num_samples):
        self._sum += loss
        self._num_inst += num_samples

    def get(self) -> float:
        return self._sum / self._num_inst if self._num_inst else float('nan')

    def reset(self):
        self._sum = 0.0
        self._num_inst = 0.0
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