    def configure_optimizers(self):
        """
        Initializes the optimizer and learning rate scheduler

        :return: output - Initialized optimizer and scheduler
        """
        self.optimizer = torch.optim.Adam(self.parameters(), lr=self.args["lr"])
        self.scheduler = {
            "scheduler": torch.optim.lr_scheduler.ReduceLROnPlateau(
                self.optimizer,
                mode="min",
                factor=0.2,
                patience=2,
                min_lr=1e-6,
                verbose=True,
            ),
            "monitor": "val_loss",
        }
        return [self.optimizer], [self.scheduler]
Initializes the optimizer and learning rate scheduler

:return: output - Initialized optimizer and scheduler
tests/integration/frameworks/mlflow/MNIST/mnist_autolog_example.py