CUDAAccelerator

class pytorch_lightning.accelerators.CUDAAccelerator[source]

Bases: pytorch_lightning.accelerators.accelerator.Accelerator

Accelerator for NVIDIA CUDA devices.

static auto_device_count()[source]

Get the devices when set to auto.

Return type:

int

get_device_stats(device)[source]

Gets stats for the given GPU device.

Parameters:

device (Union[device, str, int]) – GPU device for which to get stats

Return type:

Dict[str, Any]

Returns:

A dictionary mapping the metrics to their values.

Raises:

FileNotFoundError – If nvidia-smi installation not found

static get_parallel_devices(devices)[source]

Gets parallel devices for the Accelerator.

Return type:

List[device]

static is_available()[source]

Detect if the hardware is available.

Return type:

bool

static parse_devices(devices)[source]

Accelerator device parsing logic.

Return type:

Optional[List[int]]

setup(trainer)[source]

Setup plugins for the trainer fit and creates optimizers.

Parameters:

trainer (Trainer) – the trainer instance

Return type:

None

setup_environment(root_device)[source]

Raises:

MisconfigurationException – If the selected device is not GPU.

Return type:

None

teardown()[source]

Clean up any state created by the accelerator.

Return type:

None