test: Add test for MulticlassRecall with ignore_index+macro (fixes Lightning-AI#2441)

Author: rittik9

tests/unittests/classification/test_precision_recall.py

@@ -659,6 +659,37 @@ def test_corner_case():
     assert res == 1.0
 
 
+def test_multiclass_recall_ignore_index():
+    """Issue: https://github.com/Lightning-AI/torchmetrics/issues/2441."""
+    y_true = torch.tensor([0, 0, 1, 1])
+    y_pred = torch.tensor([
+        [0.9, 0.1],
+        [0.9, 0.1],
+        [0.9, 0.1],
+        [0.1, 0.9],
+    ])
+
+    # Test with ignore_index=0 and average="macro"
+    metric_ignore_0 = MulticlassRecall(num_classes=2, ignore_index=0, average="macro")
+    res_ignore_0 = metric_ignore_0(y_pred, y_true)
+    assert res_ignore_0 == 0.5, f"Expected 0.5, but got {res_ignore_0}"
+
+    # Test with ignore_index=1 and average="macro"
+    metric_ignore_1 = MulticlassRecall(num_classes=2, ignore_index=1, average="macro")
+    res_ignore_1 = metric_ignore_1(y_pred, y_true)
+    assert res_ignore_1 == 1.0, f"Expected 1.0, but got {res_ignore_1}"
+
+    # Test with no ignore_index and average="macro"
+    metric_no_ignore = MulticlassRecall(num_classes=2, average="macro")
+    res_no_ignore = metric_no_ignore(y_pred, y_true)
+    assert res_no_ignore == 0.75, f"Expected 0.75, but got {res_no_ignore}"
+
+    # Test with ignore_index=0 and average="none"
+    metric_none = MulticlassRecall(num_classes=2, ignore_index=0, average="none")
+    res_none = metric_none(y_pred, y_true)
+    assert torch.allclose(res_none, torch.tensor([0.0, 0.5])), f"Expected [0.0, 0.5], but got {res_none}"
+
+
 @pytest.mark.parametrize(
     ("metric", "kwargs", "base_metric"),
     [