# Copyright The PyTorch Lightning team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from typing import Any, Dict, List, Optional, Union import torch from pytorch_lightning.accelerators.accelerator import Accelerator from pytorch_lightning.utilities import _HPU_AVAILABLE, device_parser from pytorch_lightning.utilities.exceptions import MisconfigurationException from pytorch_lightning.utilities.rank_zero import rank_zero_debug class HPUAccelerator(Accelerator): """Accelerator for HPU devices.""" def setup_environment(self, root_device: torch.device) -> None: """ Raises: MisconfigurationException: If the selected device is not HPU. """ super().setup_environment(root_device) if root_device.type != "hpu": raise MisconfigurationException(f"Device should be HPU, got {root_device} instead.") def get_device_stats(self, device: Union[str, torch.device]) -> Dict[str, Any]: """HPU device stats aren't supported yet.""" rank_zero_debug("HPU device stats aren't supported yet.") return {} @staticmethod def parse_devices(devices: Union[int, str, List[int]]) -> Optional[int]: """Accelerator device parsing logic.""" return device_parser.parse_hpus(devices) @staticmethod def get_parallel_devices(devices: int) -> List[torch.device]: """Gets parallel devices for the Accelerator.""" return [torch.device("hpu")] * devices @staticmethod def auto_device_count() -> int: """Get the devices when set to auto.""" # TODO(@kaushikb11): Update this when api is exposed by the Habana team return 8 @staticmethod def is_available() -> bool: return _HPU_AVAILABLE @classmethod def register_accelerators(cls, accelerator_registry: Dict) -> None: accelerator_registry.register( "hpu", cls, description=f"{cls.__class__.__name__}", )