d192ef06119f3eccf569a844b30976db99cfa0f6,python/ray/util/sgd/torch/training_operator.py,TrainingOperator,validate,#TrainingOperator#Any#Any#,206

Before Change

                    losses.update(
                        metrics["loss"], n=metrics.get("num_samples", 1))

                if "num_correct" in metrics:
                    total_correct += metrics["num_correct"]

        stats = {
            "batch_count": batch_idx + 1,
            "mean_validation_loss": losses.avg,
            "mean_accuracy": total_correct / losses.count

After Change

                metrics = self.validate_batch(batch, batch_info)
                metric_meters.update(metrics, n=metrics.pop(NUM_SAMPLES, 1))

        return metric_meters.summary()

    def validate_batch(self, batch, batch_info):
        Calcuates the loss and accuracy over a given batch.

Instances