Generalize internal checks for Accelerator in Trainer

Author: four4fish

pytorch_lightning/trainer/trainer.py

@@ -27,7 +27,7 @@
 from torch.optim import Optimizer
 
 import pytorch_lightning as pl
-from pytorch_lightning.accelerators import Accelerator, IPUAccelerator
+from pytorch_lightning.accelerators import Accelerator, GPUAccelerator, IPUAccelerator, TPUAccelerator
 from pytorch_lightning.callbacks import Callback, EarlyStopping, ModelCheckpoint, ProgressBarBase
 from pytorch_lightning.callbacks.prediction_writer import BasePredictionWriter
 from pytorch_lightning.core.datamodule import LightningDataModule
@@ -1650,33 +1650,31 @@ def __setup_profiler(self) -> None:
         self.profiler.setup(stage=self.state.fn._setup_fn, local_rank=local_rank, log_dir=self.log_dir)
 
     def _log_device_info(self) -> None:
-        rank_zero_info(f"GPU available: {torch.cuda.is_available()}, used: {self._device_type == _AcceleratorType.GPU}")
+        rank_zero_info(
+            f"GPU available: {torch.cuda.is_available()}, used: {isinstance(self.accelerator, GPUAccelerator)}"
+        )
 
         num_tpu_cores = (
-            self.tpu_cores if self.tpu_cores is not None and self._device_type == _AcceleratorType.TPU else 0
+            self.tpu_cores if self.tpu_cores is not None and isinstance(self.accelerator, TPUAccelerator) else 0
         )
         rank_zero_info(f"TPU available: {_TPU_AVAILABLE}, using: {num_tpu_cores} TPU cores")
 
         num_ipus = self.ipus if self.ipus is not None else 0
         rank_zero_info(f"IPU available: {_IPU_AVAILABLE}, using: {num_ipus} IPUs")
 
-        if torch.cuda.is_available() and self._device_type != _AcceleratorType.GPU:
+        if torch.cuda.is_available() and isinstance(self.accelerator, GPUAccelerator):
             rank_zero_warn(
                 "GPU available but not used. Set the gpus flag in your trainer `Trainer(gpus=1)` or script `--gpus=1`.",
                 category=PossibleUserWarning,
             )
 
-        if _TPU_AVAILABLE and self._device_type != _AcceleratorType.TPU:
+        if _TPU_AVAILABLE and isinstance(self.accelerator, TPUAccelerator):
             rank_zero_warn(
                 "TPU available but not used. Set the `tpu_cores` flag in your trainer"
                 " `Trainer(tpu_cores=8)` or script `--tpu_cores=8`."
             )
 
-        if (
-            _IPU_AVAILABLE
-            and self._device_type != _AcceleratorType.IPU
-            and not isinstance(self.accelerator, IPUAccelerator)
-        ):
+        if _IPU_AVAILABLE and not isinstance(self.accelerator, IPUAccelerator):
             rank_zero_warn(
                 "IPU available but not used. Set the `ipus` flag in your trainer"
                 " `Trainer(ipus=8)` or script `--ipus=8`."