f9362e87bd07346492802c30fe71192401f9195e,fairseq/criterions/cross_entropy.py,CrossEntropyCriterion,aggregate_logging_outputs,#Any#,41

Before Change

    def aggregate_logging_outputs(logging_outputs):
        Aggregate logging outputs from data parallel training.
        sample_size = sum(log.get("sample_size", 0) for log in logging_outputs)
        return {
            "loss": sum(log.get("loss", 0) for log in logging_outputs) / sample_size / math.log(2),
        }

After Change

    @staticmethod
    def aggregate_logging_outputs(logging_outputs):
        Aggregate logging outputs from data parallel training.
        loss_sum = sum(log.get("loss", 0) for log in logging_outputs)
        ntokens = sum(log.get("ntokens", 0) for log in logging_outputs)
        sample_size = sum(log.get("sample_size", 0) for log in logging_outputs)
        agg_output = {
            "loss": loss_sum / sample_size / math.log(2),
        }
        if sample_size != ntokens:
            agg_output["nll_loss"] = loss_sum / ntokens / math.log(2)
        return agg_output

Instances