add test_target to explainer_fn parameters, because most methods need…

… an output neuron to explain

src/explainers/aggregators/self_influence.py

@@ -19,5 +19,13 @@ def get_self_influence_ranking(
     size = len(training_data)
     self_inf = torch.zeros((size,))
     for i, (x, y) in enumerate(training_data):
-        self_inf[i] = explain_fn(model, model_id, cache_dir, training_data, i, **explain_fn_kwargs)
-    return self_inf.argsort()
+        self_inf[i] = explain_fn(
+            model=model,
+            model_id=model_id,
+            cache_dir=cache_dir,
+            test_tensor=x[None],
+            test_label=y[None],
+            train_dataset=training_data,
+            train_ids=[i],
+            **explain_fn_kwargs,
+        )

src/utils/explain_wrapper.py

@@ -26,8 +26,9 @@ def explain(
     model_id: str,
     cache_dir: str,
     method: str,
-    test_tensor: torch.Tensor,
     train_dataset: torch.utils.data.Dataset,
+    test_tensor: torch.Tensor,
+    test_target: Optional[torch.Tensor] = None,
     train_ids: Optional[Union[List[int], torch.Tensor]] = None,
     **kwargs,
 ) -> torch.Tensor: