a615533788c1842483a9708787db0d73902dc1ec,fairseq/multiprocessing_trainer.py,MultiprocessingTrainer,valid_step,#MultiprocessingTrainer#Any#Any#,191

Before Change

    def valid_step(self, samples, criterion):
        Do forward pass in parallel.
        // scatter sample across GPUs
        samples, data_events = self._scatter_samples(samples, volatile=True)
        criterion.prepare(samples)

        // forward pass
        losses = [
            self.call_async(rank, "_async_valid_step", sample=samples[rank],
                            criterion=criterion, data_event=event)
            for rank, event in enumerate(data_events)
        ]

        // aggregate losses
        loss = criterion.aggregate(Future.gen_list(losses))

After Change

    def valid_step(self, samples, criterion):
        Do forward pass in parallel.
        // scatter sample across GPUs
        self._scatter_samples(samples, volatile=True)
        criterion.prepare(samples)

        // forward pass
        losses = [
            self.call_async(rank, "_async_valid_step", criterion=criterion)
            for rank in range(self.num_replicas)
        ]

        // aggregate losses
        loss = criterion.aggregate(Future.gen_list(losses))

Instances