Fix device placement when .cuda() called without specifying index (L…

…ightning-AI#14128)

src/pytorch_lightning/CHANGELOG.md

@@ -82,6 +82,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed a bug that caused `ddp_find_unused_parameters` to be set `False`, whereas the intended default is `True` ([#14095](https://github.com/Lightning-AI/lightning/pull/14095))
 
 
+- Fixed the device placement when `LightningModule.cuda()` gets called without specifying a device index and the current cuda device was not 0 ([#14128](https://github.com/Lightning-AI/lightning/pull/14128))
+
+
 ## [1.7.0] - 2022-08-02
 
 ### Added

src/pytorch_lightning/core/mixins/device_dtype_mixin.py

@@ -116,14 +116,16 @@ def cuda(self, device: Optional[Union[torch.device, int]] = None) -> Self:  # ty
         while being optimized.
 
         Arguments:
-            device: if specified, all parameters will be
-                copied to that device
+            device: If specified, all parameters will be copied to that device. If `None`, the current CUDA device
+                index will be used.
 
         Returns:
             Module: self
         """
-        if device is None or isinstance(device, int):
-            device = torch.device("cuda", index=(device or 0))
+        if device is None:
+            device = torch.device("cuda", torch.cuda.current_device())
+        elif isinstance(device, int):
+            device = torch.device("cuda", index=device)
         self.__update_properties(device=device)
         return super().cuda(device=device)
 

tests/tests_pytorch/utilities/test_dtype_device_mixin.py

@@ -113,7 +113,7 @@ def test_submodules_multi_gpu_ddp_spawn(tmpdir):
     ],
 )
 @RunIf(min_cuda_gpus=1)
-def test_gpu_cuda_device(device):
+def test_cuda_device(device):
     model = TopModule()
 
     model.cuda(device)
@@ -122,3 +122,25 @@ def test_gpu_cuda_device(device):
     assert device.type == "cuda"
     assert device.index is not None
     assert device.index == torch.cuda.current_device()
+
+
+@RunIf(min_cuda_gpus=2)
+def test_cuda_current_device():
+    """Test that calling .cuda() moves the model to the correct device and respects current cuda device setting."""
+
+    class CudaModule(DeviceDtypeModuleMixin):
+        def __init__(self):
+            super().__init__()
+            self.layer = nn.Linear(1, 1)
+
+    model = CudaModule()
+
+    torch.cuda.set_device(0)
+    model.cuda(1)
+    assert model.device == torch.device("cuda", 1)
+    assert model.layer.weight.device == torch.device("cuda", 1)
+
+    torch.cuda.set_device(1)
+    model.cuda()  # model is already on device 1, and calling .cuda() without device index should not move model
+    assert model.device == torch.device("cuda", 1)
+    assert model.layer.weight.device == torch.device("cuda", 1)