Refactor SETR_PUP to streamline metric computation; unify loss calcul…

…ation and metrics handling for improved clarity.

minerva/models/nets/image/setr.py

@@ -742,13 +742,10 @@ def _single_step(self, batch: torch.Tensor, batch_idx: int, step_name: str):
         x, y = batch
         if self.test_engine and (step_name == "test" or step_name == "val"):
             y_hat = self.test_engine(self.model, x)
-            loss = self._loss_func(y_hat, y.squeeze(1))
-            metrics = self._compute_metrics(y_hat, y, step_name)
         else:
             y_hat = self.model(x)
-            metrics = self._compute_metrics(y_hat[0], y, step_name)
 
-        print(len(y_hat))
+        metrics = self._compute_metrics(y_hat[0], y, step_name)
         loss = self._loss_func(y_hat, y.squeeze(1))
 
         for metric_name, metric_value in metrics.items():