Merge branch 'main' into docs_corrections

dilyabareeva · Dec 29, 2024 · 7a61984 · 7a61984
2 parents f827cfa + 501e009
commit 7a61984
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Showing 11 changed files with 40 additions and 22 deletions.
diff --git a/quanda/benchmarks/downstream_eval/class_detection.py b/quanda/benchmarks/downstream_eval/class_detection.py
@@ -333,6 +333,6 @@ def evaluate(
                 test_tensor=input,
                 targets=targets,
             )
-            metric.update(targets, explanations)
+            metric.update(explanations=explanations, test_labels=targets)
 
         return metric.compute()
diff --git a/quanda/benchmarks/downstream_eval/shortcut_detection.py b/quanda/benchmarks/downstream_eval/shortcut_detection.py
@@ -595,6 +595,10 @@ def evaluate(
                 test_tensor=input,
                 targets=targets,
             )
-            metric.update(explanations, test_tensor=input, test_labels=labels)
+            metric.update(
+                explanations=explanations,
+                test_tensor=input,
+                test_labels=labels,
+            )
 
         return metric.compute()
diff --git a/quanda/benchmarks/downstream_eval/subclass_detection.py b/quanda/benchmarks/downstream_eval/subclass_detection.py
@@ -565,8 +565,8 @@ def evaluate(
             )
 
             metric.update(
-                labels,
-                explanations,
+                test_subclasses=labels,
+                explanations=explanations,
                 test_tensor=inputs,
                 test_classes=grouped_labels,
             )

diff --git a/quanda/benchmarks/heuristics/mixed_datasets.py b/quanda/benchmarks/heuristics/mixed_datasets.py
@@ -554,6 +554,10 @@ def evaluate(
             explanations = explainer.explain(
                 test_tensor=inputs, targets=targets
             )
-            metric.update(explanations, test_tensor=inputs, test_labels=labels)
+            metric.update(
+                explanations=explanations,
+                test_tensor=inputs,
+                test_labels=labels,
+            )
 
         return metric.compute()
diff --git a/quanda/benchmarks/heuristics/top_k_cardinality.py b/quanda/benchmarks/heuristics/top_k_cardinality.py
@@ -345,6 +345,6 @@ def evaluate(
                 test_tensor=input,
                 targets=targets,
             )
-            metric.update(explanations)
+            metric.update(explanations=explanations)
 
         return metric.compute()
diff --git a/quanda/metrics/base.py b/quanda/metrics/base.py
@@ -59,11 +59,21 @@ def __init__(
     @abstractmethod
     def update(
         self,
+        explanations: torch.Tensor,
         *args: Any,
         **kwargs: Any,
     ):
         """Update the metric with new data.
 
+        Parameters
+        ----------
+        explanations : torch.Tensor
+            Explanations of the test samples.
+        *args : Any
+            Additional positional arguments.
+        **kwargs : Any
+            Additional keyword arguments.
+
         Raises
         ------
         NotImplementedError

diff --git a/quanda/metrics/downstream_eval/class_detection.py b/quanda/metrics/downstream_eval/class_detection.py
@@ -61,15 +61,15 @@ def __init__(
 
         self.scores: List[torch.Tensor] = []
 
-    def update(self, test_labels: torch.Tensor, explanations: torch.Tensor):
+    def update(self, explanations: torch.Tensor, test_labels: torch.Tensor):
         """Update the metric state with the provided explanations.
 
         Parameters
         ----------
-        test_labels : torch.Tensor
-            Labels of the test samples.
         explanations : torch.Tensor
             Explanations of the test samples.
+        test_labels : torch.Tensor
+            Labels of the test samples.
 
         """
         assert test_labels.shape[0] == explanations.shape[0], (

diff --git a/quanda/metrics/downstream_eval/mislabeling_detection.py b/quanda/metrics/downstream_eval/mislabeling_detection.py
@@ -227,9 +227,9 @@ def aggr_based(
 
     def update(
         self,
+        explanations: torch.Tensor,
         test_data: torch.Tensor,
         test_labels: torch.Tensor,
-        explanations: torch.Tensor,
         **kwargs,
     ):
         """Update the aggregator based metric with local attributions.
@@ -238,12 +238,12 @@ def update(
 
         Parameters
         ----------
+        explanations : torch.Tensor
+            The local attributions to be added to the aggregated scores.
         test_data : torch.Tensor
             The test data for which the attributions were computed.
         test_labels : torch.Tensor
             The true labels of the test data.
-        explanations : torch.Tensor
-            The local attributions to be added to the aggregated scores.
         kwargs : Any
             Additional keyword arguments.
 

diff --git a/quanda/metrics/downstream_eval/subclass_detection.py b/quanda/metrics/downstream_eval/subclass_detection.py
@@ -70,19 +70,19 @@ def __init__(
 
     def update(
         self,
-        test_subclasses: Union[List[int], torch.Tensor],
         explanations: torch.Tensor,
+        test_subclasses: Union[List[int], torch.Tensor],
         test_tensor: Optional[torch.Tensor] = None,
         test_classes: Optional[torch.Tensor] = None,
     ):
         """Update the metric state with the provided explanations.
 
         Parameters
         ----------
-        test_subclasses : torch.Tensor
-            Original labels of the test samples
         explanations : torch.Tensor
-            Explanations of the test samples
+            Explanations of the test samples.
+        test_subclasses : torch.Tensor
+            Original labels of the test samples.
         test_tensor: Optional[torch.Tensor]
             Test samples to used to generate the explanations.
             Only required if `filter_by_prediction` is True during

diff --git a/quanda/metrics/ground_truth/linear_datamodeling.py b/quanda/metrics/ground_truth/linear_datamodeling.py
@@ -228,22 +228,22 @@ def load_counterfactual_model(self, model_idx: int):
 
     def update(
         self,
-        test_tensor: torch.Tensor,
         explanations: torch.Tensor,
         explanation_targets: torch.Tensor,
+        test_tensor: torch.Tensor,
         **kwargs,
     ):
         """Update the evaluation scores based on new data.
 
         Parameters
         ----------
-        test_tensor : torch.Tensor
-            The test data used for evaluation.
         explanations : torch.Tensor
             The explanation scores for the test data with shape (test_samples,
             dataset_size).
         explanation_targets : torch.Tensor
             The target values for the explanations.
+        test_tensor : torch.Tensor
+            The test data used for evaluation.
         kwargs: Any
             Additional keyword arguments
 

diff --git a/quanda/metrics/heuristics/model_randomization.py b/quanda/metrics/heuristics/model_randomization.py
@@ -112,18 +112,18 @@ def __init__(
 
     def update(
         self,
-        test_data: torch.Tensor,
         explanations: torch.Tensor,
+        test_data: torch.Tensor,
         explanation_targets: Optional[torch.Tensor] = None,
     ):
         """Update the evaluation scores based on the provided data.
 
         Parameters
         ----------
-        test_data : torch.Tensor
-            The test data used for evaluation.
         explanations : torch.Tensor
             The explanations generated by the model.
+        test_data : torch.Tensor
+            The test data used for evaluation.
         explanation_targets : Optional[torch.Tensor], optional
             The target values for the explanations, by default None.