Set devices to 1 when it's just Trainer(accelerator='auto')

pytorch_lightning/trainer/connectors/accelerator_connector.py

@@ -461,19 +461,19 @@ def _set_devices_to_cpu_num_processes(self) -> None:
             self._map_devices_to_accelerator(DeviceType.CPU)
 
     def _map_devices_to_accelerator(self, accelerator: str) -> bool:
-        if self.devices is None:
-            return False
         if accelerator == DeviceType.TPU and _TPU_AVAILABLE:
+            self.devices = self.devices or 1
             self.tpu_cores = device_parser.parse_tpu_cores(self.devices)
             return True
         if accelerator == DeviceType.IPU and _IPU_AVAILABLE:
-            self.ipus = self.devices
+            self.ipus = self.devices = self.devices or 1
             return True
         if accelerator == DeviceType.GPU and torch.cuda.is_available():
-            self.gpus = self.devices
-            self.parallel_device_ids = device_parser.parse_gpu_ids(self.devices)
+            self.gpus = self.devices = self.devices or 1
+            self.parallel_device_ids = device_parser.parse_gpu_ids(self.gpus)
             return True
         if accelerator == DeviceType.CPU:
+            self.devices = self.devices or 1
             if not isinstance(self.devices, int):
                 raise MisconfigurationException(
                     "The flag `devices` must be an int with `accelerator='cpu'`,"

tests/accelerators/test_accelerator_connector.py

@@ -43,7 +43,7 @@
     SLURMEnvironment,
     TorchElasticEnvironment,
 )
-from pytorch_lightning.utilities import DeviceType, DistributedType
+from pytorch_lightning.utilities import _IPU_AVAILABLE, _TPU_AVAILABLE, DeviceType, DistributedType
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers.boring_model import BoringModel
 from tests.helpers.runif import RunIf
@@ -1005,3 +1005,17 @@ def test_unsupported_ipu_choice(monkeypatch):
         Trainer(accelerator="ipu", precision="bf16")
     with pytest.raises(MisconfigurationException, match=r"accelerator='ipu', precision=64\)` is not supported"):
         Trainer(accelerator="ipu", precision=64)
+
+
+@pytest.mark.skipif(torch.cuda.is_available() or _TPU_AVAILABLE or _IPU_AVAILABLE, reason="test requires to run on CPU")
+def test_accelerator_auto_choice_and_devices_cpu():
+    trainer = Trainer(accelerator="auto")
+    assert trainer.devices == 1
+    assert trainer.num_processes == 1
+
+
+@RunIf(min_gpus=1)
+def test_accelerator_auto_choice_and_devices_gpu():
+    trainer = Trainer(accelerator="auto")
+    assert trainer.devices == 1
+    assert trainer.gpus == 1

tests/accelerators/test_ipu.py

@@ -543,3 +543,10 @@ def test_device_type_when_training_plugin_ipu_passed(tmpdir):
     assert isinstance(trainer.training_type_plugin, IPUPlugin)
     assert trainer._device_type == DeviceType.IPU
     assert isinstance(trainer.accelerator, IPUAccelerator)
+
+
+@RunIf(ipu=True)
+def test_accelerator_auto_choice_and_devices_ipu():
+    trainer = Trainer(accelerator="auto")
+    assert trainer.devices == 1
+    assert trainer.ipus == 1

tests/accelerators/test_tpu.py

@@ -310,3 +310,10 @@ def test_mp_device_dataloader_attribute(_):
     dataloader = TPUSpawnPlugin().process_dataloader(DataLoader(dataset))
 
     assert dataloader.dataset == dataset
+
+
+@RunIf(tpu=True)
+def test_accelerator_auto_choice_and_devices_tpu():
+    trainer = Trainer(accelerator="auto")
+    assert trainer.devices == 1
+    assert trainer.tpu_cores == 1