deprecate trainer.gpus

Author: DuYicong515

pytorch_lightning/trainer/trainer.py

@@ -2181,6 +2181,10 @@ def scaler(self) -> Optional[Any]:
 
     @property
     def gpus(self) -> Optional[Union[List[int], str, int]]:
+        rank_zero_deprecation(
+            "`Trainer.gpus` was deprecated in v1.6 and will be removed in v1.8."
+            " Please use `Trainer.num_devices` or `Trainer.device_ids` to get device information instead."
+        )
         return self._accelerator_connector.gpus
 
     @property

tests/accelerators/test_accelerator_connector.py

@@ -545,7 +545,19 @@ def test_accelerator_gpu_with_devices(devices, plugin):
 def test_accelerator_auto_with_devices_gpu():
     trainer = Trainer(accelerator="auto", devices=1)
     assert isinstance(trainer.accelerator, GPUAccelerator)
-    assert trainer.gpus == 1
+    assert trainer.num_devices == 1
+
+
+@RunIf(min_gpus=1)
+def test_accelerator_gpu_with_gpus_priority():
+    """Test for checking `gpus` flag takes priority over `devices`."""
+
+    gpus = 1
+    with pytest.warns(UserWarning, match="The flag `devices=4` will be ignored,"):
+        trainer = Trainer(accelerator="gpu", devices=4, gpus=gpus)
+
+    assert isinstance(trainer.accelerator, GPUAccelerator)
+    assert trainer.num_devices == gpus
 
 
 def test_validate_accelerator_and_devices():
@@ -934,8 +946,8 @@ def test_devices_auto_choice_cpu(is_ipu_available_mock, is_tpu_available_mock, i
 @mock.patch("torch.cuda.device_count", return_value=2)
 def test_devices_auto_choice_gpu(is_gpu_available_mock, device_count_mock):
     trainer = Trainer(accelerator="auto", devices="auto")
+    assert isinstance(trainer.accelerator, GPUAccelerator)
     assert trainer.num_devices == 2
-    assert trainer.gpus == 2
 
 
 @pytest.mark.parametrize(

tests/models/test_gpu.py

@@ -23,6 +23,7 @@
 import tests.helpers.pipelines as tpipes
 import tests.helpers.utils as tutils
 from pytorch_lightning import Trainer
+from pytorch_lightning.accelerators import CPUAccelerator, GPUAccelerator
 from pytorch_lightning.plugins.environments import TorchElasticEnvironment
 from pytorch_lightning.utilities import device_parser
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
@@ -190,10 +191,12 @@ def test_torchelastic_gpu_parsing(mocked_device_count, mocked_is_available, gpus
     sanitizing the gpus as only one of the GPUs is visible."""
     trainer = Trainer(gpus=gpus)
     assert isinstance(trainer._accelerator_connector.cluster_environment, TorchElasticEnvironment)
-    assert trainer.gpus == gpus
     # when use gpu
     if device_parser.parse_gpu_ids(gpus) is not None:
         assert trainer.device_ids == device_parser.parse_gpu_ids(gpus)
+        assert isinstance(trainer.accelerator, GPUAccelerator)
+    else:
+        assert isinstance(trainer.accelerator, CPUAccelerator)
 
 
 @RunIf(min_gpus=1)