test fix

minerva/models/nets/setr.py

@@ -457,10 +457,18 @@ def __init__(
             The interpolation mode for upsampling in the decoder. Defaults to "bilinear".
         loss_fn : nn.Module, optional
             The loss function to be used during training. Defaults to None.
-        log_metrics : bool
-            Whether to log metrics during training. Defaults to True.
-        metrics : list[MetricTypeSetR], optional
-            The metrics to be used for evaluation. Defaults to [MetricTypeSetR.mIoU, MetricTypeSetR.mIoU, MetricTypeSetR.mIoU].
+        train_metrics : Dict[str, Metric], optional
+            The metrics to be used for training evaluation. Defaults to None.
+        val_metrics : Dict[str, Metric], optional
+            The metrics to be used for validation evaluation. Defaults to None.
+        test_metrics : Dict[str, Metric], optional
+            The metrics to be used for testing evaluation. Defaults to None.
+        aux_output : bool
+            Whether to include auxiliary output heads in the model. Defaults to True.
+        aux_output_layers : list[int] | None
+            The indices of the layers to output auxiliary predictions. Defaults to [9, 14, 19].
+        aux_weights : list[float]
+            The weights for the auxiliary predictions. Defaults to [0.3, 0.3, 0.3].
 
         """
         super().__init__()

tests/models/nets/test_setr.py

@@ -27,7 +27,7 @@ def test_setr_predict():
     preds = model.predict_step((x, mask), 0)
     assert preds is not None
     assert (
-        preds[0].shape == mask_shape
+        preds.shape == mask_shape
     ), f"Expected shape {mask_shape}, but got {preds[0].shape}"