Avoid fallback on CPU if no devices are provided (#12410)

CHANGELOG.md

@@ -393,8 +393,13 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - The strategies that support `sync_batchnorm` now only apply it when fitting ([#11919](https://github.com/PyTorchLightning/pytorch-lightning/pull/11919))
 
+
+- Avoided fallback on CPU if no devices are provided for other accelerators ([#12410](https://github.com/PyTorchLightning/pytorch-lightning/pull/12410))
+
+
 - Modified `supporters.py` so that in the accumulator element (for loss) is created directly on the device ([#12430](https://github.com/PyTorchLightning/pytorch-lightning/pull/12430))
 
+
 - Removed `EarlyStopping.on_save_checkpoint` and `EarlyStopping.on_load_checkpoint` in favor of `EarlyStopping.state_dict` and `EarlyStopping.load_state_dict` ([#11887](https://github.com/PyTorchLightning/pytorch-lightning/pull/11887))
 
 

docs/source/accelerators/gpu.rst

@@ -223,15 +223,10 @@ a comma separated list of GPU ids:
     Trainer(accelerator="gpu", devices=-1)
 
 The table below lists examples of possible input formats and how they are interpreted by Lightning.
-Note in particular the difference between ``devices=0``, ``devices=[0]`` and ``devices="0"``.
 
 +------------------+-----------+---------------------+---------------------------------+
 | `devices`        | Type      | Parsed              | Meaning                         |
 +==================+===========+=====================+=================================+
-| None             | NoneType  | None                | CPU                             |
-+------------------+-----------+---------------------+---------------------------------+
-| 0                | int       | None                | CPU                             |
-+------------------+-----------+---------------------+---------------------------------+
 | 3                | int       | [0, 1, 2]           | first 3 GPUs                    |
 +------------------+-----------+---------------------+---------------------------------+
 | -1               | int       | [0, 1, 2, ...]      | all available GPUs              |
@@ -240,8 +235,6 @@ Note in particular the difference between ``devices=0``, ``devices=[0]`` and ``d
 +------------------+-----------+---------------------+---------------------------------+
 | [1, 3]           | list      | [1, 3]              | GPUs 1 and 3                    |
 +------------------+-----------+---------------------+---------------------------------+
-| "0"              | str       | None                | CPU                             |
-+------------------+-----------+---------------------+---------------------------------+
 | "3"              | str       | [0, 1, 2]           | first 3 GPUs                    |
 +------------------+-----------+---------------------+---------------------------------+
 | "1, 3"           | str       | [1, 3]              | GPUs 1 and 3                    |

pytorch_lightning/trainer/connectors/accelerator_connector.py

@@ -424,10 +424,6 @@ class AcceleratorConnector:
             devices, num_processes, gpus, ipus, tpu_cores
         )
 
-        if self._devices_flag in ([], 0, "0"):
-            rank_zero_warn(f"You passed `devices={devices}`, switching to `cpu` accelerator")
-            self._accelerator_flag = "cpu"
-
         if self._devices_flag == "auto" and self._accelerator_flag is None:
             raise MisconfigurationException(
                 f"You passed `devices={devices}` but haven't specified"

tests/accelerators/test_accelerator_connector.py

@@ -506,6 +506,15 @@ def test_accelerator_cpu(_):
         trainer = Trainer(accelerator="cpu", gpus=1)
 
 
+@mock.patch("torch.cuda.is_available", return_value=False)
+@pytest.mark.parametrize("devices", ["0", 0, []])
+def test_passing_zero_and_empty_list_to_devices_flag(_, devices):
+    with pytest.raises(
+        MisconfigurationException, match="can not run on your system since the accelerator is not available."
+    ):
+        Trainer(accelerator="gpu", devices=devices)
+
+
 @RunIf(min_gpus=1)
 def test_accelerator_gpu():
     trainer = Trainer(accelerator="gpu", gpus=1)
@@ -950,14 +959,6 @@ def test_parallel_devices_in_strategy_confilict_with_accelerator(parallel_device
         Trainer(strategy=DDPStrategy(parallel_devices=parallel_devices), accelerator=accelerator)
 
 
-def test_passing_zero_and_empty_list_to_devices_flag():
-    with pytest.warns(UserWarning, match=r"switching to `cpu` accelerator"):
-        Trainer(accelerator="gpu", devices=0)
-
-    with pytest.warns(UserWarning, match=r"switching to `cpu` accelerator"):
-        Trainer(accelerator="gpu", devices=[])
-
-
 @pytest.mark.parametrize("deterministic", [True, False])
 def test_deterministic_init(deterministic):
     trainer = Trainer(accelerator="auto", deterministic=deterministic)

tests/deprecated_api/test_remove_1-8.py

@@ -1038,7 +1038,6 @@ def test_trainer_num_processes(monkeypatch, trainer_kwargs, expected_num_process
         ({"accelerator": "gpu", "devices": 1}, [0]),
         ({"accelerator": "gpu", "devices": 2}, [0, 1]),
         ({"accelerator": "gpu", "devices": [1]}, [1]),
-        ({"accelerator": "gpu", "devices": "0"}, None),
         ({"accelerator": "gpu", "devices": "0,"}, [0]),
     ],
 )