add callbacks

cli/train.py

@@ -1,21 +1,14 @@
 import hydra
-from hydra.core.config_store import ConfigStore
 from hydra.utils import instantiate
-
+from omegaconf import DictConfig
-from omegaconf import DictConfig,OmegaConf
-from pytorch_lightning import Trainer
 from pytorch_lightning.callbacks import ModelCheckpoint, EarlyStopping
 from pytorch_lightning.loggers import MLFlowLogger
-import torch
-
-
-from enhancer.models.demucs import Demucs
-from enhancer.data.dataset import EnhancerDataset
 
 
 @hydra.main(config_path="train_config",config_name="config")
 def main(config: DictConfig):
 
+    callbacks = []
     logger = MLFlowLogger(experiment_name=config.mlflow.experiment_name,
                             run_name=config.mlflow.run_name)
 
@@ -26,7 +19,22 @@ def main(config: DictConfig):
     model = instantiate(config.model,dataset=dataset,lr=parameters.get("lr"),
             loss=parameters.get("loss"), metric = parameters.get("metric"))
 
-    trainer = instantiate(config.trainer,logger=logger)
+    checkpoint = ModelCheckpoint(
+        dirpath="",filename="model",monitor=parameters.get("loss"),verbose=False,
+        mode="min",every_n_epochs=1
+    )
+    callbacks.append(checkpoint)
+    early_stopping = EarlyStopping(
+            monitor=parameters.get("loss"),
+            mode="min",
+            min_delta=0.0,
+            patience=100,
+            strict=True,
+            verbose=False,
+        )
+    callbacks.append(early_stopping)
+
+    trainer = instantiate(config.trainer,logger=logger,callbacks=callbacks)
     trainer.fit(model)