test: add control check for inputs to the metric, update the test

Author: begumcig

src/pruna/evaluation/metrics/metric_evalharness.py

@@ -91,8 +91,11 @@ def update(
         outputs : List[Any] | torch.Tensor
             Output data.
         """
-        if len(x) != len(gt) != len(outputs):
-            raise ValueError(f"Input, ground truth, and output length mismatch: {len(x)} vs {len(gt)} vs {len(outputs)}")
+        if not (len(x) == len(gt) == len(outputs)):
+            error_message = f"Input, ground truth, and output length mismatch: {len(x)} vs {len(gt)} vs {len(outputs)}"
+            pruna_logger.error(error_message)
+            raise ValueError(error_message)
+        pruna_logger.debug(f"Processing {len(x)} samples for {self.metric_name}")
         inputs = metric_data_processor(x, gt, outputs, self.call_type)
         for ref, pred in zip(inputs[0], inputs[1]):
             raw_item = self.metric_fn((ref, pred))

tests/evaluation/test_evalharness_metrics.py

@@ -48,7 +48,7 @@ def test_lm_eval_metric_length_mismatch():
     refs = ["a", "b", "c"]
     preds = ["a", "b"]
 
-    with pytest.raises(ValueError, match="Preds and refs length mismatch"):
+    with pytest.raises(ValueError):
         metric.update(refs, refs, preds)