415be78cc0d1275a29d0ceda550d0d7a7a5224ea,python/ray/util/sgd/torch/training_operator.py,TrainingOperator,train_epoch,#TrainingOperator#Any#Any#,120

Before Change

            metric_meters.update(metrics, n=metrics.pop(NUM_SAMPLES, 1))
            self.global_step += 1

        if self.scheduler and info.get(SCHEDULER_STEP) == SCHEDULER_STEP_EPOCH:
            self.scheduler.step()

        return metric_meters.summary()

After Change

        metric_meters = AverageMeterCollection()

        model.train()
        for batch_idx, batch in enumerate(iterator):
            batch_info = {
                "batch_idx": batch_idx,
                "global_step": self.global_step

Instances