Deprecate Trainer.root_gpu

CHANGELOG.md

@@ -354,6 +354,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Deprecated `Trainer.lr_schedulers` in favor of `Trainer.lr_scheduler_configs` which returns a list of dataclasses instead of dictionaries ([#11443](https://github.com/PyTorchLightning/pytorch-lightning/pull/11443))
 
+- Deprecated `Trainer.root_gpu` in favor of `Trainer.strategy.root_device` ([#11994](https://github.com/PyTorchLightning/pytorch-lightning/pull/11994))
 
 - Deprecated `Trainer.verbose_evaluate` in favor of `EvaluationLoop(verbose=...)` ([#10931](https://github.com/PyTorchLightning/pytorch-lightning/pull/10931))
 

pytorch_lightning/trainer/trainer.py

@@ -2022,7 +2022,10 @@ def num_processes(self) -> int:
 
     @property
     def root_gpu(self) -> Optional[int]:
-        return self._accelerator_connector.root_gpu
+        rank_zero_deprecation(
+            "Method `trainer.root_gpu` is deprecated please use `trainer.strategy.root_device.index`", stacklevel=5
+        )
+        return self._strategy.root_device.index
 
     @property
     def tpu_cores(self) -> int:

tests/models/data/horovod/train_default_model.py

@@ -102,7 +102,7 @@ def training_epoch_end(self, outputs) -> None:
     if on_gpu:
         trainer = Trainer(gpus=1, strategy="horovod", max_epochs=1)
         # Test the root_gpu property
-        assert trainer.root_gpu == hvd.local_rank()
+        assert trainer.strategy.root_device.index == hvd.local_rank()
 
 
 if __name__ == "__main__":

tests/models/test_gpu.py

@@ -129,8 +129,8 @@ def test_trainer_num_gpu_0(mocked_device_count_0, gpus, expected_num_gpus, strat
         pytest.param(3, 0, "ddp", id="3 gpus, expect gpu root device to be 0.(backend:ddp)"),
     ],
 )
-def test_root_gpu_property(mocked_device_count, gpus, expected_root_gpu, strategy):
-    assert Trainer(gpus=gpus, strategy=strategy).root_gpu == expected_root_gpu
+def test_root_device_property(mocked_device_count, gpus, expected_root_gpu, strategy):
+    assert Trainer(gpus=gpus, strategy=strategy).strategy.root_device.index == expected_root_gpu
 
 
 @pytest.mark.parametrize(
@@ -141,8 +141,8 @@ def test_root_gpu_property(mocked_device_count, gpus, expected_root_gpu, strateg
         pytest.param(0, None, "ddp", id="None is None"),
     ],
 )
-def test_root_gpu_property_0_passing(mocked_device_count_0, gpus, expected_root_gpu, strategy):
-    assert Trainer(gpus=gpus, strategy=strategy).root_gpu == expected_root_gpu
+def test_root_device_property_0_passing(mocked_device_count_0, gpus, expected_root_gpu, strategy):
+    assert Trainer(gpus=gpus, strategy=strategy).strategy.root_device.index == expected_root_gpu
 
 
 # Asking for a gpu when non are available will result in a MisconfigurationException