874da9a25fd4f1d8aac44d29c365fa2143f7793e,python/ray/util/sgd/torch/training_operator.py,TrainingOperator,register,#TrainingOperator#,167

Before Change

        else:
            return_vals.append(self._models)

        if len(self._optimizers) == 1:
            return_vals.append(self._optimizers[0])
        else:
            return_vals.append(self._optimizers)

        if self._criterion is not None:
            return_vals.append(self._criterion)

        if self._schedulers is not None:

After Change

            if not isinstance(self._schedulers, Iterable):
                self._schedulers = [self._schedulers]
        else:
            if isinstance(schedulers, Iterable):
                self._schedulers = []
            else:
                self._schedulers = None

        if criterion:
            logger.debug("Registering loss.")
            self._criterion = criterion
            if self.use_gpu and torch.cuda.is_available():

Instances