diff --git a/CHANGELOG.md b/CHANGELOG.md
index a0bc7c284d3..13f09f6dcf8 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -53,6 +53,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Fixed
 
 
+- Fixed `torch.sort` currently does not support bool dtype on CUDA ([#665](https://github.com/PyTorchLightning/metrics/pull/665))
+
+
 
 ## [0.6.1] - 2021-12-06
 
diff --git a/tests/detection/test_map.py b/tests/detection/test_map.py
index 43c586cee28..83d850c8d4b 100644
--- a/tests/detection/test_map.py
+++ b/tests/detection/test_map.py
@@ -215,6 +215,19 @@ def test_empty_preds():
     metric.compute()
 
 
+_gpu_test_condition = not torch.cuda.is_available()
+
+
+@pytest.mark.skipif(_pytest_condition, reason="test requires that torchvision=>0.8.0 is installed")
+@pytest.mark.skipif(_gpu_test_condition, reason="test requires CUDA availability")
+def test_map_gpu():
+    """Test predictions on single gpu."""
+    metric = MAP()
+    metric = metric.to("cuda")
+    metric.update(_inputs.preds[0], _inputs.target[0])
+    metric.compute()
+
+
 @pytest.mark.skipif(_pytest_condition, reason="test requires that pycocotools and torchvision=>0.8.0 is installed")
 def test_empty_metric():
     """Test empty metric."""
diff --git a/torchmetrics/detection/map.py b/torchmetrics/detection/map.py
index 4d18f5be2cd..d40370857d7 100644
--- a/torchmetrics/detection/map.py
+++ b/torchmetrics/detection/map.py
@@ -407,7 +407,9 @@ def _evaluate_image(
         ignore_area = (areas < area_range[0]) | (areas > area_range[1])
 
         # sort dt highest score first, sort gt ignore last
-        ignore_area_sorted, gtind = torch.sort(ignore_area)
+        ignore_area_sorted, gtind = torch.sort(ignore_area.to(torch.uint8))
+        # Convert to uint8 temporarily and back to bool, because "Sort currently does not support bool dtype on CUDA"
+        ignore_area_sorted = ignore_area_sorted.to(torch.bool)
         gt = gt[gtind]
         scores = self.detection_scores[id]
         scores_filtered = scores[det_label_mask]
@@ -429,7 +431,7 @@ def _evaluate_image(
             for idx_iou, t in enumerate(self.iou_thresholds):
                 for idx_det in range(nb_det):
                     m = MAP._find_best_gt_match(t, nb_gt, gt_matches, idx_iou, gt_ignore, ious, idx_det)
-                    if m is not -1:
+                    if m != -1:
                         det_ignore[idx_iou, idx_det] = gt_ignore[m]
                         det_matches[idx_iou, idx_det] = True
                         gt_matches[idx_iou, m] = True