def update_train_loop_lr_schedulers(self, monitor_metrics=None):
    num_accumulated_batches_reached = self._accumulated_batches_reached()
    num_training_batches_reached = self._num_training_batches_reached()
    if (num_accumulated_batches_reached or num_training_batches_reached):
        self.trainer.optimizer_connector.update_learning_rates(interval='step', monitor_metrics=monitor_metrics, opt_indices=[opt_idx for (opt_idx, _) in self.get_optimizers_iterable()])
def update_train_loop_lr_schedulers(self, monitor_metrics=None):
    num_accumulated_batches_reached = self._accumulated_batches_reached()
    num_training_batches_reached = self._num_training_batches_reached()
    if (num_accumulated_batches_reached or num_training_batches_reached):
        self.trainer.optimizer_connector.update_learning_rates(interval='step', monitor_metrics=monitor_metrics, opt_indices=[opt_idx for (opt_idx, _) in self.get_optimizers_iterable()])