Updated Fabric trainer example to not call self.trainer.model during validation

examples/fabric/build_your_own_trainer/trainer.py

@@ -156,6 +156,20 @@ def fit(
         assert optimizer is not None
         model, optimizer = self.fabric.setup(model, optimizer)
 
+        if not is_overridden("on_validation_model_eval", _unwrap_objects(model)):
+
+            def ovme(s) -> None:
+                s.eval()
+
+            model.on_validation_model_eval = MethodType(ovme, model)
+
+        if not is_overridden("on_validation_model_train", _unwrap_objects(model)):
+
+            def ovmt(s) -> None:
+                s.train()
+
+            model.on_validation_model_train = MethodType(ovmt, model)
+
         # assemble state (current epoch and global step will be added in save)
         state = {"model": model, "optim": optimizer, "scheduler": scheduler_cfg}
 
@@ -264,7 +278,7 @@ def val_loop(
         val_loader: Optional[torch.utils.data.DataLoader],
         limit_batches: Union[int, float] = float("inf"),
     ):
-        """The validation loop ruunning a single validation epoch.
+        """The validation loop running a single validation epoch.
 
         Args:
             model: the LightningModule to evaluate