Function to handle loss functions with or without sample_weight arg

python/dalex/dalex/model_explanations/_variable_importance/utils.py

@@ -82,3 +82,18 @@ def loss_after_permutation(data, y, weights, model, predict, loss_function, vari
     loss_features['_baseline_'] = loss_baseline
 
     return pd.DataFrame(loss_features, index=[0])
+
+
+def calculate_loss(loss_function, observed, predicted, sample_weights=None):
+    # Determine if loss function accepts 'sample_weight'
+    loss_args = inspect.signature(loss_function).parameters
+    supports_weight = "sample_weight" in loss_args
+
+    if supports_weight:
+        return loss_function(observed, predicted, sample_weight=sample_weights)
+    else:
+        if sample_weights:
+            warnings.warn(
+                f"Loss function {loss_function.__name__} does not take sample weights. Calculating unweighted loss."
+            )
+        return loss_function(observed, predicted)