add lr scheduler

cli/train.py

@@ -1,7 +1,9 @@
 import os
+from types import MethodType
 import hydra
 from hydra.utils import instantiate
 from omegaconf import DictConfig
+from torch.optim.lr_scheduler import ReduceLROnPlateau
 from pytorch_lightning.callbacks import ModelCheckpoint, EarlyStopping
 from pytorch_lightning.loggers import MLFlowLogger
 os.environ["HYDRA_FULL_ERROR"] = "1"
@@ -37,6 +39,20 @@ def main(config: DictConfig):
         )
     callbacks.append(early_stopping)
     
+    def configure_optimizer(self):
+        optimizer = instantiate(config.optimizer,lr=parameters.get("lr"),parameters=self.parameters())
+        scheduler = ReduceLROnPlateau(
+            optimizer=optimizer,
+            mode=direction,
+            factor=0.1,
+            verbose=True,
+            min_lr=parameters.get("min_lr",1e-6),
+            patience=3
+        )
+        return {"optimizer":optimizer, "lr_scheduler":scheduler}
+
+    model.configure_parameters = MethodType(configure_optimizer,model)
+
     trainer = instantiate(config.trainer,logger=logger,callbacks=callbacks)
     trainer.fit(model)
     logger.experiment.log_artifact(logger.run_id,f"./model/model_{JOB_ID}")