Check parallel_devices passed through strategy is consistent with the accelerator flag

pytorch_lightning/trainer/connectors/accelerator_connector.py

@@ -348,13 +348,21 @@ def _check_config_and_set_final_flags(
                 else:
                     self._cluster_environment_flag = getattr(self._strategy_flag, "cluster_environment")
 
-            # TODO: RFC existing accel_conn doesn't handle this, should we add conflict check?
-            #   eg: parallel_device is torch.device(cpu) but accelerator=gpu
             if hasattr(self._strategy_flag, "parallel_devices"):
                 if self._strategy_flag.parallel_devices:
                     if self._strategy_flag.parallel_devices[0].type == "cpu":
+                        if self._accelerator_flag and self._accelerator_flag not in ("auto", "cpu"):
+                            raise MisconfigurationException(
+                                f"CPU parallel_devices set through {self._strategy_flag.__class__.__name__} class,"
+                                f" but accelerator set to {self._accelerator_flag}, please choose one device type"
+                            )
                         self._accelerator_flag = "cpu"
                     if self._strategy_flag.parallel_devices[0].type == "cuda":
+                        if self._accelerator_flag and self._accelerator_flag not in ("auto", "gpu"):
+                            raise MisconfigurationException(
+                                f"GPU parallel_devices set through {self._strategy_flag.__class__.__name__} class,"
+                                f" but accelerator set to {self._accelerator_flag}, please choose one device type"
+                            )
                         self._accelerator_flag = "gpu"
 
         amp_type = amp_type if isinstance(amp_type, str) else None

tests/accelerators/test_accelerator_connector.py

@@ -933,6 +933,15 @@ def test_devices_auto_choice_gpu(is_gpu_available_mock, device_count_mock):
     assert trainer.gpus == 2
 
 
+@pytest.mark.parametrize(
+    ["parallel_devices", "accelerator"],
+    [([torch.device("cpu")], "gpu"), ([torch.device("cuda", i) for i in range(8)], ("tpu"))],
+)
+def test_parallel_devices_in_strategy_confilict_with_accelerator(parallel_devices, accelerator):
+    with pytest.raises(MisconfigurationException, match=r"parallel_devices set through"):
+        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)

tests/strategies/test_ddp_strategy.py

@@ -115,6 +115,7 @@ def test_ddp_configure_ddp():
     # in DDPStrategy configure_ddp(), model wrapped by DistributedDataParallel
     assert isinstance(trainer.model, DistributedDataParallel)
 
+    ddp_strategy = DDPStrategy()
     trainer = Trainer(
         max_epochs=1,
         strategy=ddp_strategy,