small fixes

src/nanotron/trainer.py

@@ -692,7 +692,7 @@ def validation_step(self, dataloader: Iterator[Dict[str, Union[torch.Tensor, Ten
         lang_losses_list = list(lang_losses.keys())
 
         # Compute losses
-        if isinstance(outputs[0], torch.Tensor):
+        if len(outputs) > 0 and isinstance(outputs[0], torch.Tensor):
             # Multilingual losses
             for loss, lang_code in zip(outputs, lang_codes):
                 lang_losses[lang_losses_list[lang_code]].append(loss)
@@ -703,7 +703,7 @@ def validation_step(self, dataloader: Iterator[Dict[str, Union[torch.Tensor, Ten
                 if not lang_losses[
                     lang
                 ]:  # If the list is empty --> Set local language loss to -1 to exclude it from the global computation
-                    lang_losses[lang] = torch.tensor(-1, dtype=torch.float32)
+                    lang_losses[lang] = torch.tensor(-1, dtype=torch.float32, device="cuda")
                 else:  # If we have at least 1 loss from a given language --> compute local language loss mean
                     lang_losses[lang] = torch.mean(torch.stack(lang_losses[lang]))