Uses of Class org.bytedeco.pytorch.global.torch.DeviceType (JavaCPP Presets for PyTorch 2.1.2-1.5.10 API)

Methods in org.bytedeco.pytorch that return torch.DeviceType
Modifier and Type	Method and Description
`torch.DeviceType`	StorageImpl.`device_type()`
`torch.DeviceType`	StreamData3.`device_type()`
`torch.DeviceType`	TensorIteratorBase.`device_type()`
`torch.DeviceType`	TensorImpl.`device_type()` The device type of a Tensor, e.g., DeviceType::CPU or DeviceType::CUDA.
`static torch.DeviceType`	CPUGeneratorImpl.`device_type()`
`torch.DeviceType`	Storage.`device_type()`
`torch.DeviceType`	Stream.`device_type()`
`torch.DeviceType`	TensorIteratorBase.`device_type(int arg)`
`torch.DeviceType`	DeviceTypeSet.`front()`
`torch.DeviceType`	DeviceTypeSet.Iterator.`get()`
`torch.DeviceType`	DeviceGuardImplInterface.`type()` Return the type of device managed by this guard implementation.
`torch.DeviceType`	Device.`type()` Returns the type of device this is.

Methods in org.bytedeco.pytorch with parameters of type torch.DeviceType
Modifier and Type	Method and Description
`StreamData3`	StreamData3.`device_type(torch.DeviceType setter)`
`void`	DeviceTypeSet.`erase(torch.DeviceType value)`
`Device`	Context.`getDeviceFromPtr(Pointer data, torch.DeviceType device_type)`
`void`	DeviceTypeSet.`insert(torch.DeviceType value)`
`StreamOptional`	Node.`stream(torch.DeviceType device_type)` Note: Function Streams A function's stream (for a given device type) is the stream of the first element of its input buffer on a device of that type.
`static Stream`	Stream.`unpack3(long stream_id, byte device_index, torch.DeviceType device_type)`

Constructors in org.bytedeco.pytorch with parameters of type torch.DeviceType
Constructor and Description
`Device(torch.DeviceType type)`
`Device(torch.DeviceType type, byte index)` Constructs a new `Device` from a `DeviceType` and an optional device index.
`DeviceGuardImplRegistrar(torch.DeviceType arg0, DeviceGuardImplInterface arg1)`

Methods in org.bytedeco.pytorch.cuda that return torch.DeviceType
Modifier and Type	Method and Description
`torch.DeviceType`	CUDAStream.`device_type()` Used to avoid baking in device type explicitly to Python-side API.

Methods in org.bytedeco.pytorch.cuda with parameters of type torch.DeviceType
Modifier and Type	Method and Description
`static CUDAStream`	CUDAStream.`unpack3(long stream_id, byte device_index, torch.DeviceType device_type)`

Methods in org.bytedeco.pytorch.global that return torch.DeviceType
Modifier and Type	Method and Description
`static torch.DeviceType`	torch.`backendToDeviceType(torch.Backend b)`
`static torch.DeviceType`	torch.`dispatchKeyToDeviceType(torch.DispatchKey dispatch_key)`
`torch.DeviceType`	torch.DeviceType.`intern()`
`static torch.DeviceType`	torch.`kCPU()`
`static torch.DeviceType`	torch.`kCUDA()`
`static torch.DeviceType`	torch.`kFPGA()`
`static torch.DeviceType`	torch.`kHIP()`
`static torch.DeviceType`	torch.`kHPU()`
`static torch.DeviceType`	torch.`kIPU()`
`static torch.DeviceType`	torch.`kLazy()`
`static torch.DeviceType`	torch.`kMeta()`
`static torch.DeviceType`	torch.`kMetal()`
`static torch.DeviceType`	torch.`kMPS()`
`static torch.DeviceType`	torch.`kMTIA()`
`static torch.DeviceType`	torch.`kORT()`
`static torch.DeviceType`	torch.`kPrivateUse1()`
`static torch.DeviceType`	torch.`kVE()`
`static torch.DeviceType`	torch.`kVulkan()`
`static torch.DeviceType`	torch.`kXLA()`
`static torch.DeviceType`	torch.`kXPU()`
`static torch.DeviceType`	torch.DeviceType.`valueOf(String name)` Returns the enum constant of this type with the specified name.
`static torch.DeviceType[]`	torch.DeviceType.`values()` Returns an array containing the constants of this enum type, in the order they are declared.

Methods in org.bytedeco.pytorch.global with parameters of type torch.DeviceType
Modifier and Type	Method and Description
`static void`	torch.`checkDeviceType(BytePointer c, TensorArrayRef tensors, torch.DeviceType device_type)`
`static void`	torch.`checkDeviceType(String c, TensorVector tensors, torch.DeviceType device_type)`
`static TensorImplVector`	torch.`checked_dense_tensor_list_unwrap(TensorArrayRef tensors, BytePointer name, int pos, torch.DeviceType device_type, torch.ScalarType scalar_type)`
`static BytePointer`	torch.`DeviceTypeName(torch.DeviceType d)`
`static BytePointer`	torch.`DeviceTypeName(torch.DeviceType d, boolean lower_case)`
`static Allocator`	torch.`GetAllocator(torch.DeviceType t)`
`static DeviceGuardImplInterface`	torch.`getDeviceGuardImpl(torch.DeviceType type)`
`static StorageImplPtr`	torch.`GetStorageImplCreate(torch.DeviceType t)`
`static boolean`	torch.`hasDeviceGuardImpl(torch.DeviceType type)`
`static boolean`	torch.`isValidDeviceType(torch.DeviceType d)`
`static void`	torch.`SetAllocator(torch.DeviceType t, Allocator alloc)`
`static void`	torch.`SetAllocator(torch.DeviceType t, Allocator alloc, byte priority)` Set the allocator for DeviceType `t`.
`static void`	torch.`SetStorageImplCreate(torch.DeviceType t, StorageImplPtr fptr)`
`static Pointer`	torch.`shiftLeft(Pointer stream, torch.DeviceType type)`
`static void`	torch.`TensorBackendMetaRegistry(torch.DeviceType t, Pointer get_fptr, Pointer set_fptr)`

Uses of Classorg.bytedeco.pytorch.global.torch.DeviceType