a d@sddlmZmZmZmZmZddlZddlmZddl m Z ddl m Z ddl mZddlmZedZerdd lmZeZnd ZerddlmmZGd d d e Zeeeeeefeed ddZdS))AnyDictListOptionalUnionN)package_available)_DEVICE) Accelerator)MisconfigurationException)rank_zero_debugZhabana_frameworks)is_habana_availableFc@seZdZdZejddddZeee e fdddZ ddd d Z e eee eefeed d d Ze eeejd ddZe edddZe edddZe e dddZeeddddZdS)HPUAcceleratorzAccelerator for HPU devices.N)devicereturncCs|jdkrtd|ddS)zs Raises: MisconfigurationException: If the selected device is not HPU. hpuzDevice should be HPU, got z instead.N)typer selfrrk/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/pytorch_lightning/accelerators/hpu.py setup_device)s zHPUAccelerator.setup_devicec Cs6ztj|WSttfy0tdiYS0dS)anReturns a map of the following metrics with their values: - Limit: amount of total memory on HPU device. - InUse: amount of allocated memory at any instance. - MaxInUse: amount of total active memory allocated. - NumAllocs: number of allocations. - NumFrees: number of freed chunks. - ActiveAllocs: number of active allocations. - MaxAllocSize: maximum allocated size. - TotalSystemAllocs: total number of system allocations. - TotalSystemFrees: total number of system frees. - TotalActiveAllocs: total number of active allocations. zHPU `get_device_stats` failedN) torch_hpurZ memory_statsAttributeError NameErrorr rrrrget_device_stats2s zHPUAccelerator.get_device_stats)rcCsdS)Nr)rrrrteardownFszHPUAccelerator.teardowndevicesrcCst|S)z!Accelerator device parsing logic.) _parse_hpusrrrr parse_devicesIszHPUAccelerator.parse_devicescCstdg|S)z*Gets parallel devices for the Accelerator.r)torchrrrrrget_parallel_devicesNsz#HPUAccelerator.get_parallel_devicesc Cs0z tWSttfy*tdYdS0dS)zBReturns the number of HPU devices when the devices is set to auto.z=HPU `auto_device_count` failed, returning default count of 8.N)rZ device_countrrr rrrrauto_device_countSs  z HPUAccelerator.auto_device_countc Cs(z tWSttfy"YdS0dS)z8Returns a bool indicating if HPU is currently available.FN)r is_availablerrrrrrr%\s zHPUAccelerator.is_availablec Cs(z tWSttfy"YdS0dS)z#Returns the name of the HPU device.N)rget_device_namerrrrrrr'ds zHPUAccelerator.get_device_name)accelerator_registryrcCs|jd||jjddS)Nr) description)register __class____name__)clsr(rrrregister_acceleratorsls z$HPUAccelerator.register_accelerators)r, __module__ __qualname____doc__r!rrrrstrrrr staticmethodrintrrr r"r$boolr%r' classmethodr.rrrrr &s  $r rcCs4|durt|ttfstdt|tr0t|S|S)a Parses the hpus given in the format as accepted by the :class:`~pytorch_lightning.trainer.Trainer` for the `devices` flag. Args: devices: An integer that indicates the number of Gaudi devices to be used Returns: Either an integer or ``None`` if no devices were requested Raises: MisconfigurationException: If devices aren't of type `int` or `str` Nz;`devices` for `HPUAccelerator` must be int, string or None.) isinstancer4r2r rrrrrusr)typingrrrrrr!Z lightning_utilities.core.importsrZ lightning_fabric.utilities.typesrZ*pytorch_lightning.accelerators.acceleratorr Z&pytorch_lightning.utilities.exceptionsr Z%pytorch_lightning.utilities.rank_zeror Z_HABANA_FRAMEWORK_AVAILABLEZ,habana_frameworks.torch.utils.library_loaderr Z_HPU_AVAILABLEZhabana_frameworks.torch.hpurrr r4r2rrrrrs      O