Add wandb logger

src/qusi/internal/lightning_train_session.py

@@ -4,6 +4,7 @@
 from warnings import warn
 
 import lightning
+from lightning.pytorch.loggers import WandbLogger
 from torch.nn import BCELoss, Module
 from torch.optim import Optimizer
 from torch.utils.data import DataLoader
@@ -66,6 +67,8 @@ def train_session(
         system_configuration = TrainSystemConfiguration.new()
     if loss_metric is None:
         loss_metric = BCELoss()
+    if logging_configuration is None:
+        logging_configuration = TrainLoggingConfiguration.new()
     if logging_metrics is None:
         logging_metrics = [BinaryAccuracy(), BinaryAUROC()]
 
@@ -100,9 +103,11 @@ def train_session(
 
     lightning_model = QusiLightningModule.new(model=model, optimizer=optimizer, loss_metric=loss_metric,
                                               logging_metrics=logging_metrics)
+    wandb_logger = WandbLogger(project=logging_configuration.wandb_project, entity=logging_configuration.wandb_entity)
     trainer = lightning.Trainer(
         max_epochs=hyperparameter_configuration.cycles,
         limit_train_batches=hyperparameter_configuration.train_steps_per_cycle,
         limit_val_batches=hyperparameter_configuration.validation_steps_per_cycle,
+        logger=[wandb_logger]
     )
     trainer.fit(model=lightning_model, train_dataloaders=train_dataloader, val_dataloaders=validation_dataloaders)