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Source code for pytorch_lightning.accelerators.cpu

# Copyright The Lightning AI 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
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# 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
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from typing import Any, Dict, List, Union

import torch
from lightning_utilities.core.imports import RequirementCache

from lightning_fabric.accelerators.cpu import _parse_cpu_cores
from lightning_fabric.utilities.types import _DEVICE
from pytorch_lightning.accelerators.accelerator import Accelerator
from pytorch_lightning.utilities.exceptions import MisconfigurationException


[docs]class CPUAccelerator(Accelerator): """Accelerator for CPU devices."""
[docs] def setup_device(self, device: torch.device) -> None: """ Raises: MisconfigurationException: If the selected device is not CPU. """ if device.type != "cpu": raise MisconfigurationException(f"Device should be CPU, got {device} instead.")
[docs] def get_device_stats(self, device: _DEVICE) -> Dict[str, Any]: """Get CPU stats from ``psutil`` package.""" return get_cpu_stats()
[docs] def teardown(self) -> None: pass
[docs] @staticmethod def parse_devices(devices: Union[int, str, List[int]]) -> int: """Accelerator device parsing logic.""" devices = _parse_cpu_cores(devices) return devices
[docs] @staticmethod def get_parallel_devices(devices: Union[int, str, List[int]]) -> List[torch.device]: """Gets parallel devices for the Accelerator.""" devices = _parse_cpu_cores(devices) return [torch.device("cpu")] * devices
[docs] @staticmethod def auto_device_count() -> int: """Get the devices when set to auto.""" return 1
[docs] @staticmethod def is_available() -> bool: """CPU is always available for execution.""" return True
@classmethod def register_accelerators(cls, accelerator_registry: Dict) -> None: accelerator_registry.register( "cpu", cls, description=f"{cls.__class__.__name__}", )
# CPU device metrics _CPU_VM_PERCENT = "cpu_vm_percent" _CPU_PERCENT = "cpu_percent" _CPU_SWAP_PERCENT = "cpu_swap_percent" _PSUTIL_AVAILABLE = RequirementCache("psutil") def get_cpu_stats() -> Dict[str, float]: if not _PSUTIL_AVAILABLE: raise ModuleNotFoundError( f"Fetching CPU device stats requires `psutil` to be installed. {str(_PSUTIL_AVAILABLE)}" ) import psutil return { _CPU_VM_PERCENT: psutil.virtual_memory().percent, _CPU_PERCENT: psutil.cpu_percent(), _CPU_SWAP_PERCENT: psutil.swap_memory().percent, }

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