Fix trainer init

src/batdetect2/train/train.py

@@ -18,7 +18,11 @@ from batdetect2.targets import TargetProtocol
 from batdetect2.train.augmentations import build_augmentations
 from batdetect2.train.callbacks import ValidationMetrics
 from batdetect2.train.clips import build_clipper
-from batdetect2.train.config import FullTrainingConfig, TrainingConfig
+from batdetect2.train.config import (
+    FullTrainingConfig,
+    PLTrainerConfig,
+    TrainingConfig,
+)
 from batdetect2.train.dataset import (
     LabeledDataset,
     RandomExampleSource,
@@ -96,24 +100,12 @@ def build_trainer(
     conf: FullTrainingConfig,
     targets: TargetProtocol,
 ) -> Trainer:
+    trainer_conf = PLTrainerConfig.model_validate(
+        conf.train,
+        from_attributes=True,
+    )
     return Trainer(
-        accelerator=conf.train.accelerator,
+        **trainer_conf.model_dump(exclude_none=True),
-        accumulate_grad_batches=conf.train.accumulate_grad_batches,
-        deterministic=conf.train.deterministic,
-        check_val_every_n_epoch=conf.train.check_val_every_n_epoch,
-        devices=conf.train.devices,
-        enable_checkpointing=conf.train.enable_checkpointing,
-        gradient_clip_val=conf.train.gradient_clip_val,
-        limit_train_batches=conf.train.limit_train_batches,
-        limit_test_batches=conf.train.limit_test_batches,
-        limit_val_batches=conf.train.limit_val_batches,
-        log_every_n_steps=conf.train.log_every_n_steps,
-        max_epochs=conf.train.max_epochs,
-        min_epochs=conf.train.min_epochs,
-        max_steps=conf.train.max_steps,
-        min_steps=conf.train.min_steps,
-        max_time=conf.train.max_time,
-        precision=conf.train.precision,
         val_check_interval=conf.train.val_check_interval,
         logger=build_logger(conf.train.logger),
         callbacks=build_trainer_callbacks(targets),