HPUAccelerator

class pytorch_lightning.accelerators.HPUAccelerator

Bases: pytorch_lightning.accelerators.accelerator.Accelerator

Accelerator for HPU devices.

static auto_device_count()

Returns the number of HPU devices when the devices is set to auto.

Return type:

int

static get_device_name()

Returns the name of the HPU device.

Return type:

str

get_device_stats(device)

Returns 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.

Return type:

Dict[str, Any]

static get_parallel_devices(devices)

Gets parallel devices for the Accelerator.

Return type:

List[device]

static is_available()

Returns a bool indicating if HPU is currently available.

Return type:

bool

static parse_devices(devices)

Accelerator device parsing logic.

Return type:

Optional[int]

setup_environment(root_device)

Raises:

MisconfigurationException – If the selected device is not HPU.

Return type:

None