Fix hyperparameter saving

src/batdetect2/train/lightning.py

@@ -1,5 +1,6 @@
 import lightning as L
 import torch
+from pydantic import BaseModel
 from torch.optim.adam import Adam
 from torch.optim.lr_scheduler import CosineAnnealingLR
 
@@ -20,23 +21,27 @@ class TrainingModule(L.LightningModule):
     def __init__(self, config: FullTrainingConfig):
         super().__init__()
 
-        self.save_hyperparameters()
+        # NOTE: Need to convert to vanilla python object so that DVCLive can
+        # store it.
+        self._config = (
+            config.model_dump() if isinstance(config, BaseModel) else config
+        )
+        self.save_hyperparameters({"config": self._config})
 
-        self.loss = build_loss(config.train.loss)
+        self.config = FullTrainingConfig.model_validate(self._config)
-        self.targets = build_targets(config.targets)
+        self.loss = build_loss(self.config.train.loss)
+        self.targets = build_targets(self.config.targets)
         self.detector = build_model(
             num_classes=len(self.targets.class_names),
-            config=config.model,
+            config=self.config.model,
         )
-        self.preprocessor = build_preprocessor(config.preprocess)
+        self.preprocessor = build_preprocessor(self.config.preprocess)
         self.postprocessor = build_postprocessor(
             self.targets,
             min_freq=self.preprocessor.min_freq,
             max_freq=self.preprocessor.max_freq,
         )
 
-        self.config = config
-
     def forward(self, spec: torch.Tensor) -> ModelOutput:
         return self.detector(spec)
 

tests/test_train/test_lightning.py

@@ -1,7 +1,6 @@
 from pathlib import Path
 
 import lightning as L
-import pytest
 import torch
 import xarray as xr
 from soundevent import data