Add name to accelerator interface

src/lightning/fabric/accelerators/accelerator.py

@@ -56,6 +56,12 @@ def auto_device_count() -> int:
     def is_available() -> bool:
         """Detect if the hardware is available."""
 
+    @staticmethod
+    @abstractmethod
+    def name() -> str:
+        """The name of the accelerator."""
+
     @classmethod
     def register_accelerators(cls, accelerator_registry: _AcceleratorRegistry) -> None:
+        """Register the accelerator with the registry."""
         pass

src/lightning/fabric/accelerators/cpu.py

@@ -62,11 +62,16 @@ def is_available() -> bool:
         """CPU is always available for execution."""
         return True
 
+    @staticmethod
+    @override
+    def name() -> str:
+        return "cpu"
+
     @classmethod
     @override
     def register_accelerators(cls, accelerator_registry: _AcceleratorRegistry) -> None:
         accelerator_registry.register(
-            "cpu",
+            cls.name(),
             cls,
             description=cls.__name__,
         )

src/lightning/fabric/accelerators/cuda.py

@@ -66,11 +66,16 @@ def auto_device_count() -> int:
     def is_available() -> bool:
         return num_cuda_devices() > 0
 
+    @staticmethod
+    @override
+    def name() -> str:
+        return "cuda"
+
     @classmethod
     @override
     def register_accelerators(cls, accelerator_registry: _AcceleratorRegistry) -> None:
         accelerator_registry.register(
-            "cuda",
+            cls.name(),
             cls,
             description=cls.__name__,
         )

src/lightning/fabric/accelerators/mps.py

@@ -74,11 +74,16 @@ def is_available() -> bool:
         mps_disabled = os.getenv("DISABLE_MPS", "0") == "1"
         return not mps_disabled and torch.backends.mps.is_available() and platform.processor() in ("arm", "arm64")
 
+    @staticmethod
+    @override
+    def name() -> str:
+        return "mps"
+
     @classmethod
     @override
     def register_accelerators(cls, accelerator_registry: _AcceleratorRegistry) -> None:
         accelerator_registry.register(
-            "mps",
+            cls.name(),
             cls,
             description=cls.__name__,
         )

src/lightning/fabric/accelerators/xla.py

@@ -93,10 +93,19 @@ def is_available() -> bool:
             # when `torch_xla` is imported but not used
             return False
 
+    @staticmethod
+    @override
+    def name() -> str:
+        return "tpu"
+
     @classmethod
     @override
     def register_accelerators(cls, accelerator_registry: _AcceleratorRegistry) -> None:
-        accelerator_registry.register("tpu", cls, description=cls.__name__)
+        accelerator_registry.register(
+            cls.name(),
+            cls,
+            description=cls.__name__,
+        )
 
 
 # PJRT support requires this minimum version

src/lightning/pytorch/CHANGELOG.md

@@ -32,6 +32,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Add MPS accelerator support for mixed precision ([#21209](https://github.com/Lightning-AI/pytorch-lightning/pull/21209))
 
+- Add `name()` function to accelerator interface (([#21325](https://github.com/Lightning-AI/pytorch-lightning/pull/21325)))
+
 
 ### Removed
 

src/lightning/pytorch/accelerators/cpu.py

@@ -17,8 +17,8 @@
 from lightning_utilities.core.imports import RequirementCache
 from typing_extensions import override
 
-from lightning.fabric.accelerators import _AcceleratorRegistry
 from lightning.fabric.accelerators.cpu import _parse_cpu_cores
+from lightning.fabric.accelerators.registry import _AcceleratorRegistry
 from lightning.fabric.utilities.types import _DEVICE
 from lightning.pytorch.accelerators.accelerator import Accelerator
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
@@ -71,11 +71,16 @@ def is_available() -> bool:
         """CPU is always available for execution."""
         return True
 
+    @staticmethod
+    @override
+    def name() -> str:
+        return "cpu"
+
     @classmethod
     @override
     def register_accelerators(cls, accelerator_registry: _AcceleratorRegistry) -> None:
         accelerator_registry.register(
-            "cpu",
+            cls.name(),
             cls,
             description=cls.__name__,
         )

src/lightning/pytorch/accelerators/cuda.py

@@ -21,8 +21,8 @@
 from typing_extensions import override
 
 import lightning.pytorch as pl
-from lightning.fabric.accelerators import _AcceleratorRegistry
 from lightning.fabric.accelerators.cuda import _check_cuda_matmul_precision, _clear_cuda_memory, num_cuda_devices
+from lightning.fabric.accelerators.registry import _AcceleratorRegistry
 from lightning.fabric.utilities.device_parser import _parse_gpu_ids
 from lightning.fabric.utilities.types import _DEVICE
 from lightning.pytorch.accelerators.accelerator import Accelerator
@@ -104,11 +104,16 @@ def auto_device_count() -> int:
     def is_available() -> bool:
         return num_cuda_devices() > 0
 
+    @staticmethod
+    @override
+    def name() -> str:
+        return "cuda"
+
     @classmethod
     @override
     def register_accelerators(cls, accelerator_registry: _AcceleratorRegistry) -> None:
         accelerator_registry.register(
-            "cuda",
+            cls.name(),
             cls,
             description=cls.__name__,
         )

src/lightning/pytorch/accelerators/mps.py

@@ -16,8 +16,8 @@
 import torch
 from typing_extensions import override
 
-from lightning.fabric.accelerators import _AcceleratorRegistry
 from lightning.fabric.accelerators.mps import MPSAccelerator as _MPSAccelerator
+from lightning.fabric.accelerators.registry import _AcceleratorRegistry
 from lightning.fabric.utilities.device_parser import _parse_gpu_ids
 from lightning.fabric.utilities.types import _DEVICE
 from lightning.pytorch.accelerators.accelerator import Accelerator
@@ -78,11 +78,16 @@ def is_available() -> bool:
         """MPS is only available on a machine with the ARM-based Apple Silicon processors."""
         return _MPSAccelerator.is_available()
 
+    @staticmethod
+    @override
+    def name() -> str:
+        return "mps"
+
     @classmethod
     @override
     def register_accelerators(cls, accelerator_registry: _AcceleratorRegistry) -> None:
         accelerator_registry.register(
-            "mps",
+            cls.name(),
             cls,
             description=cls.__name__,
         )

src/lightning/pytorch/accelerators/xla.py

@@ -15,7 +15,7 @@
 
 from typing_extensions import override
 
-from lightning.fabric.accelerators import _AcceleratorRegistry
+from lightning.fabric.accelerators.registry import _AcceleratorRegistry
 from lightning.fabric.accelerators.xla import XLAAccelerator as FabricXLAAccelerator
 from lightning.fabric.utilities.types import _DEVICE
 from lightning.pytorch.accelerators.accelerator import Accelerator
@@ -49,7 +49,16 @@ def get_device_stats(self, device: _DEVICE) -> dict[str, Any]:
             "avg. peak memory (MB)": peak_memory,
         }
 
+    @staticmethod
+    @override
+    def name() -> str:
+        return "tpu"
+
     @classmethod
     @override
     def register_accelerators(cls, accelerator_registry: _AcceleratorRegistry) -> None:
-        accelerator_registry.register("tpu", cls, description=cls.__name__)
+        accelerator_registry.register(
+            cls.name(),
+            cls,
+            description=cls.__name__,
+        )

tests/tests_fabric/accelerators/test_registry.py

@@ -49,6 +49,10 @@ def auto_device_count():
     def is_available():
         return True
 
+    @staticmethod
+    def name():
+        return "test_accelerator"
+
 
 def test_accelerator_registry_with_new_accelerator():
     accelerator_name = "custom_accelerator"
@@ -85,6 +89,10 @@ def auto_device_count():
         def is_available():
             return True
 
+        @staticmethod
+        def name():
+            return "custom_accelerator"
+
     ACCELERATOR_REGISTRY.register(
         accelerator_name, CustomAccelerator, description=accelerator_description, param1="abc", param2=123
     )