415be78cc0d1275a29d0ceda550d0d7a7a5224ea,python/ray/util/sgd/torch/training_operator.py,TrainingOperator,train_batch,#TrainingOperator#Any#Any#,202

Before Change

        // Call step of optimizer to update model params.
        with self.timers.record("apply"):
            self.optimizer.step()

        return {"train_loss": loss.item(), NUM_SAMPLES: features[0].size(0)}

    def validate(self, val_iterator, info):

After Change

            raise RuntimeError("Either set self.model in setup function or "
                               "override this method to implement a custom "
                               "training loop.")
        if not hasattr(self, "optimizer"):
            raise RuntimeError("Either set self.optimizer in setup function "
                               "or override this method to implement a custom "
                               "training loop.")
        if not hasattr(self, "criterion"):
            raise RuntimeError("Either set self.criterion in setup function "
                               "or override this method to implement a custom "
                               "training loop.")
        model = self.model
        optimizer = self.optimizer
        criterion = self.criterion
        // unpack features into list to support multiple inputs model
        *features, target = batch
        // Create non_blocking tensors for distributed training
        if self.use_gpu:

Instances