ultralytics 8.0.188 fix .grad attribute leaf Tensor Warning (#5094)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

tests/test_cuda.py

@@ -16,6 +16,7 @@ DATASETS_DIR = Path(SETTINGS['datasets_dir'])
 WEIGHTS_DIR = Path(SETTINGS['weights_dir'])
 MODEL = WEIGHTS_DIR / 'path with spaces' / 'yolov8n.pt'  # test spaces in path
 DATA = 'coco8.yaml'
+BUS = ASSETS / 'bus.jpg'
 
 
 def test_checks():
@@ -29,6 +30,30 @@ def test_train():
     YOLO(MODEL).train(data=DATA, imgsz=64, epochs=1, device=device)  # requires imgsz>=64
 
 
+@pytest.mark.skipif(not CUDA_IS_AVAILABLE, reason='CUDA is not available')
+def test_predict_multiple_devices():
+    model = YOLO('yolov8n.pt')
+    model = model.cpu()
+    assert str(model.device) == 'cpu'
+    _ = model(BUS)  # CPU inference
+    assert str(model.device) == 'cpu'
+
+    model = model.to('cuda:0')
+    assert str(model.device) == 'cuda:0'
+    _ = model(BUS)  # CUDA inference
+    assert str(model.device) == 'cuda:0'
+
+    model = model.cpu()
+    assert str(model.device) == 'cpu'
+    _ = model(BUS)  # CPU inference
+    assert str(model.device) == 'cpu'
+
+    model = model.cuda()
+    assert str(model.device) == 'cuda:0'
+    _ = model(BUS)  # CUDA inference
+    assert str(model.device) == 'cuda:0'
+
+
 @pytest.mark.skipif(not CUDA_IS_AVAILABLE, reason='CUDA is not available')
 def test_autobatch():
     from ultralytics.utils.autobatch import check_train_batch_size
@@ -57,10 +82,10 @@ def test_predict_sam():
     model.info()
 
     # Run inference
-    model(ASSETS / 'bus.jpg', device=0)
+    model(BUS, device=0)
 
     # Run inference with bboxes prompt
-    model(ASSETS / 'zidane.jpg', bboxes=[439, 437, 524, 709], device=0)
+    model(BUS, bboxes=[439, 437, 524, 709], device=0)
 
     # Run inference with points prompt
     model(ASSETS / 'zidane.jpg', points=[900, 370], labels=[1], device=0)