Trying to get the CNNTransformer to work, but it is hard.

2 files changed, 5 insertions, 2 deletions

diff --git a/src/training/trainer/callbacks/lr_schedulers.py b/src/training/trainer/callbacks/lr_schedulers.py
index 907e292..630c434 100644
--- a/src/training/trainer/callbacks/lr_schedulers.py
+++ b/src/training/trainer/callbacks/lr_schedulers.py
@@ -22,7 +22,10 @@ class LRScheduler(Callback):
     def on_epoch_end(self, epoch: int, logs: Optional[Dict] = None) -> None:
         """Takes a step at the end of every epoch."""
         if self.interval == "epoch":
-            self.lr_scheduler.step()
+            if "ReduceLROnPlateau" in self.lr_scheduler.__class__.__name__:
+                self.lr_scheduler.step(logs["val_loss"])
+            else:
+                self.lr_scheduler.step()
 
     def on_train_batch_end(self, batch: int, logs: Optional[Dict] = None) -> None:
         """Takes a step at the end of every training batch."""
diff --git a/src/training/trainer/callbacks/wandb_callbacks.py b/src/training/trainer/callbacks/wandb_callbacks.py
index f24e5cc..1627f17 100644
--- a/src/training/trainer/callbacks/wandb_callbacks.py
+++ b/src/training/trainer/callbacks/wandb_callbacks.py
@@ -111,7 +111,7 @@ class WandbImageLogger(Callback):
                     ]
                 ).rstrip("_")
             else:
-                ground_truth = self.targets[i]
+                ground_truth = self.model.mapper(int(self.targets[i]))
             caption = f"Prediction: {pred} Confidence: {conf:.3f} Ground Truth: {ground_truth}"
             images.append(wandb.Image(image, caption=caption))