ai.djl.pytorch.jni

Class JniUtils

java.lang.Object

ai.djl.pytorch.jni.JniUtils

public final class JniUtils
extends java.lang.Object

A class containing utilities to interact with the PyTorch Engine's Java Native Interface (JNI) layer.

Method Summary

Modifier and Type	Method and Description
static PtNDArray	abs(PtNDArray ndArray)
static PtNDArray	acos(PtNDArray ndArray)
static PtNDArray	add(PtNDArray ndArray1, PtNDArray ndArray2)
static void	addi(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	all(PtNDArray ndArray)
static PtNDArray	any(PtNDArray ndArray)
static PtNDArray	arange(PtNDManager manager, float start, float stop, float step, ai.djl.ndarray.types.DataType dType, ai.djl.Device device, ai.djl.ndarray.types.SparseFormat fmt)
static PtNDArray	argMax(PtNDArray ndArray)
static PtNDArray	argMax(PtNDArray ndArray, long dim, boolean keepDim)
static PtNDArray	argMin(PtNDArray ndArray)
static PtNDArray	argMin(PtNDArray ndArray, long dim, boolean keepDim)
static PtNDArray	argSort(PtNDArray ndArray, long dim, boolean keepDim)
static PtNDArray	asin(PtNDArray ndArray)
static PtNDArray	atan(PtNDArray ndArray)
static PtNDArray	booleanMask(PtNDArray ndArray, PtNDArray indicesNd)
static PtNDArray	broadcast(PtNDArray ndArray, ai.djl.ndarray.types.Shape shape)
static PtNDArray	cat(ai.djl.ndarray.NDArray[] arrays, long dim)
static PtNDArray	ceil(PtNDArray ndArray)
static PtNDArray	clip(PtNDArray ndArray, java.lang.Number min, java.lang.Number max)
static PtNDArray	clone(PtNDArray ndArray)
static boolean	contentEqual(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	cos(PtNDArray ndArray)
static PtNDArray	cosh(PtNDArray ndArray)
static PtNDArray	createEmptyNdArray(PtNDManager manager, ai.djl.ndarray.types.Shape shape, ai.djl.ndarray.types.DataType dType, ai.djl.Device device, ai.djl.ndarray.types.SparseFormat fmt)
static PtNDArray	createNdFromByteBuffer(PtNDManager manager, java.nio.ByteBuffer data, ai.djl.ndarray.types.Shape shape, ai.djl.ndarray.types.DataType dType, ai.djl.ndarray.types.SparseFormat fmt, ai.djl.Device device)
static PtNDArray	createOnesNdArray(PtNDManager manager, ai.djl.ndarray.types.Shape shape, ai.djl.ndarray.types.DataType dType, ai.djl.Device device, ai.djl.ndarray.types.SparseFormat fmt)
static PtNDArray	createZerosNdArray(PtNDManager manager, ai.djl.ndarray.types.Shape shape, ai.djl.ndarray.types.DataType dType, ai.djl.Device device, ai.djl.ndarray.types.SparseFormat fmt)
static void	deleteModule(PtSymbolBlock block)
static void	deleteNdArray(Pointer handle)
static PtNDArray	div(PtNDArray ndArray1, PtNDArray ndArray2)
static void	divi(PtNDArray ndArray1, PtNDArray ndArray2)
static void	enableInferenceMode(PtSymbolBlock block)
static PtNDArray	eq(PtNDArray self, PtNDArray other)
static PtNDArray	exp(PtNDArray ndArray)
static PtNDArray	eye(PtNDManager manager, int n, int m, ai.djl.ndarray.types.DataType dataType, ai.djl.Device device, ai.djl.ndarray.types.SparseFormat fmt)
static PtNDArray	flatten(PtNDArray ndArray, long startDim, long endDim)
static PtNDArray	floor(PtNDArray ndArray)
static java.nio.ByteBuffer	getByteBuffer(PtNDArray ndArray)
static ai.djl.ndarray.types.DataType	getDataType(PtNDArray ndArray)
static ai.djl.Device	getDevice(PtNDArray ndArray)
static java.util.Set<java.lang.String>	getFeatures()
static ai.djl.ndarray.types.Shape	getShape(PtNDArray ndArray)
static ai.djl.ndarray.types.SparseFormat	getSparseFormat(PtNDArray ndArray)
static PtNDArray	gt(PtNDArray self, PtNDArray other)
static PtNDArray	gte(PtNDArray self, PtNDArray other)
static PtNDArray	linspace(PtNDManager manager, float start, float stop, int step, ai.djl.ndarray.types.DataType dType, ai.djl.Device device, ai.djl.ndarray.types.SparseFormat fmt)
static PtSymbolBlock	loadModule(PtNDManager manager, java.nio.file.Path path, ai.djl.Device device)
static PtNDArray	log(PtNDArray ndArray)
static PtNDArray	log10(PtNDArray ndArray)
static PtNDArray	log2(PtNDArray ndArray)
static PtNDArray	logicalNot(PtNDArray ndArray)
static PtNDArray	logicalXor(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	lt(PtNDArray self, PtNDArray other)
static PtNDArray	lte(PtNDArray self, PtNDArray other)
static PtNDArray	matmul(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	max(PtNDArray ndArray)
static PtNDArray	max(PtNDArray ndArray, long dim, boolean keepDim)
static PtNDArray	max(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	mean(PtNDArray ndArray)
static PtNDArray	mean(PtNDArray ndArray, long dim, boolean keepDim)
static PtNDArray	min(PtNDArray ndArray)
static PtNDArray	min(PtNDArray ndArray, long dim, boolean keepDim)
static PtNDArray	min(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	mul(PtNDArray ndArray1, PtNDArray ndArray2)
static void	muli(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	neg(PtNDArray ndArray)
static void	negi(PtNDArray ndArray)
static PtNDArray	neq(PtNDArray self, PtNDArray other)
static PtNDArray	none(PtNDArray ndArray)
static PtNDArray	normal(PtNDManager manager, double mean, double std, ai.djl.ndarray.types.Shape size, ai.djl.ndarray.types.DataType dataType, ai.djl.Device device)
static PtNDArray	onesLike(PtNDArray array, ai.djl.ndarray.types.DataType dType, ai.djl.Device device, ai.djl.ndarray.types.SparseFormat fmt)
static PtNDArray	permute(PtNDArray ndArray, long[] dims)
static PtNDArray	pow(PtNDArray ndArray1, PtNDArray ndArray2)
static void	powi(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	remainder(PtNDArray ndArray1, PtNDArray ndArray2)
static void	remainderi(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	reshape(PtNDArray ndArray, long[] shape)
static PtNDArray	round(PtNDArray ndArray)
static void	setNumInteropThreads(int threads)
static void	setNumThreads(int threads)
static void	setSeed(long seed)
static PtNDArray	sin(PtNDArray ndArray)
static PtNDArray	sinh(PtNDArray ndArray)
static PtNDArray	slice(PtNDArray ndArray, long dim, long start, long stop, long step)
static PtNDArray	softmax(PtNDArray ndArray, long dim, ai.djl.ndarray.types.DataType dTpe)
static PtNDArray	sort(PtNDArray ndArray, long dim, boolean descending)
static ai.djl.ndarray.NDList	split(PtNDArray ndArray, long[] indices, long axis)
static ai.djl.ndarray.NDList	split(PtNDArray ndArray, long size, long axis)
static PtNDArray	sqrt(PtNDArray ndArray)
static PtNDArray	squeeze(PtNDArray ndArray)
static PtNDArray	squeeze(PtNDArray ndArray, long dim)
static PtNDArray	stack(ai.djl.ndarray.NDArray[] arrays, int dim)
static PtNDArray	sub(PtNDArray ndArray1, PtNDArray ndArray2)
static void	subi(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	sum(PtNDArray ndArray)
static PtNDArray	sum(PtNDArray ndArray, long[] dims, boolean keepDim)
static PtNDArray	tan(PtNDArray ndArray)
static PtNDArray	tanh(PtNDArray ndArray)
static PtNDArray	to(PtNDArray ndArray, ai.djl.ndarray.types.DataType dataType, ai.djl.Device device, boolean copy)
static PtNDArray	transpose(PtNDArray ndArray, long dim1, long dim2)
static PtNDArray	trunc(PtNDArray ndArray)
static PtNDArray	uniform(PtNDManager manager, double low, double high, ai.djl.ndarray.types.Shape size, ai.djl.ndarray.types.DataType dataType, ai.djl.Device device)
static PtNDArray	unsqueeze(PtNDArray ndArray, long dim)
static PtNDArray	upsampleBilinear2d(PtNDArray ndArray, long[] size, boolean alignCorners)
static PtNDArray	zerosLike(PtNDArray array, ai.djl.ndarray.types.DataType dType, ai.djl.Device device, ai.djl.ndarray.types.SparseFormat fmt)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

setNumInteropThreads

public static void setNumInteropThreads(int threads)

setNumThreads

public static void setNumThreads(int threads)

getFeatures

public static java.util.Set<java.lang.String> getFeatures()

setSeed

public static void setSeed(long seed)

createNdFromByteBuffer

public static PtNDArray createNdFromByteBuffer(PtNDManager manager,
                                               java.nio.ByteBuffer data,
                                               ai.djl.ndarray.types.Shape shape,
                                               ai.djl.ndarray.types.DataType dType,
                                               ai.djl.ndarray.types.SparseFormat fmt,
                                               ai.djl.Device device)

createEmptyNdArray

public static PtNDArray createEmptyNdArray(PtNDManager manager,
                                           ai.djl.ndarray.types.Shape shape,
                                           ai.djl.ndarray.types.DataType dType,
                                           ai.djl.Device device,
                                           ai.djl.ndarray.types.SparseFormat fmt)

createZerosNdArray

public static PtNDArray createZerosNdArray(PtNDManager manager,
                                           ai.djl.ndarray.types.Shape shape,
                                           ai.djl.ndarray.types.DataType dType,
                                           ai.djl.Device device,
                                           ai.djl.ndarray.types.SparseFormat fmt)

createOnesNdArray

public static PtNDArray createOnesNdArray(PtNDManager manager,
                                          ai.djl.ndarray.types.Shape shape,
                                          ai.djl.ndarray.types.DataType dType,
                                          ai.djl.Device device,
                                          ai.djl.ndarray.types.SparseFormat fmt)

zerosLike

public static PtNDArray zerosLike(PtNDArray array,
                                  ai.djl.ndarray.types.DataType dType,
                                  ai.djl.Device device,
                                  ai.djl.ndarray.types.SparseFormat fmt)

onesLike

public static PtNDArray onesLike(PtNDArray array,
                                 ai.djl.ndarray.types.DataType dType,
                                 ai.djl.Device device,
                                 ai.djl.ndarray.types.SparseFormat fmt)

arange

public static PtNDArray arange(PtNDManager manager,
                               float start,
                               float stop,
                               float step,
                               ai.djl.ndarray.types.DataType dType,
                               ai.djl.Device device,
                               ai.djl.ndarray.types.SparseFormat fmt)

linspace

public static PtNDArray linspace(PtNDManager manager,
                                 float start,
                                 float stop,
                                 int step,
                                 ai.djl.ndarray.types.DataType dType,
                                 ai.djl.Device device,
                                 ai.djl.ndarray.types.SparseFormat fmt)

to

public static PtNDArray to(PtNDArray ndArray,
                           ai.djl.ndarray.types.DataType dataType,
                           ai.djl.Device device,
                           boolean copy)

broadcast

public static PtNDArray broadcast(PtNDArray ndArray,
                                  ai.djl.ndarray.types.Shape shape)

slice

public static PtNDArray slice(PtNDArray ndArray,
                              long dim,
                              long start,
                              long stop,
                              long step)

booleanMask

public static PtNDArray booleanMask(PtNDArray ndArray,
                                    PtNDArray indicesNd)

clone

public static PtNDArray clone(PtNDArray ndArray)

reshape

public static PtNDArray reshape(PtNDArray ndArray,
                                long[] shape)

stack

public static PtNDArray stack(ai.djl.ndarray.NDArray[] arrays,
                              int dim)

cat

public static PtNDArray cat(ai.djl.ndarray.NDArray[] arrays,
                            long dim)

softmax

public static PtNDArray softmax(PtNDArray ndArray,
                                long dim,
                                ai.djl.ndarray.types.DataType dTpe)

argMax

public static PtNDArray argMax(PtNDArray ndArray)

argMax

public static PtNDArray argMax(PtNDArray ndArray,
                               long dim,
                               boolean keepDim)

argMin

public static PtNDArray argMin(PtNDArray ndArray)

argMin

public static PtNDArray argMin(PtNDArray ndArray,
                               long dim,
                               boolean keepDim)

argSort

public static PtNDArray argSort(PtNDArray ndArray,
                                long dim,
                                boolean keepDim)

sort

public static PtNDArray sort(PtNDArray ndArray,
                             long dim,
                             boolean descending)

permute

public static PtNDArray permute(PtNDArray ndArray,
                                long[] dims)

transpose

public static PtNDArray transpose(PtNDArray ndArray,
                                  long dim1,
                                  long dim2)

contentEqual

public static boolean contentEqual(PtNDArray ndArray1,
                                   PtNDArray ndArray2)

add

public static PtNDArray add(PtNDArray ndArray1,
                            PtNDArray ndArray2)

addi

public static void addi(PtNDArray ndArray1,
                        PtNDArray ndArray2)

sub

public static PtNDArray sub(PtNDArray ndArray1,
                            PtNDArray ndArray2)

subi

public static void subi(PtNDArray ndArray1,
                        PtNDArray ndArray2)

mul

public static PtNDArray mul(PtNDArray ndArray1,
                            PtNDArray ndArray2)

muli

public static void muli(PtNDArray ndArray1,
                        PtNDArray ndArray2)

div

public static PtNDArray div(PtNDArray ndArray1,
                            PtNDArray ndArray2)

divi

public static void divi(PtNDArray ndArray1,
                        PtNDArray ndArray2)

remainder

public static PtNDArray remainder(PtNDArray ndArray1,
                                  PtNDArray ndArray2)

remainderi

public static void remainderi(PtNDArray ndArray1,
                              PtNDArray ndArray2)

pow

public static PtNDArray pow(PtNDArray ndArray1,
                            PtNDArray ndArray2)

powi

public static void powi(PtNDArray ndArray1,
                        PtNDArray ndArray2)

logicalXor

public static PtNDArray logicalXor(PtNDArray ndArray1,
                                   PtNDArray ndArray2)

logicalNot

public static PtNDArray logicalNot(PtNDArray ndArray)

matmul

public static PtNDArray matmul(PtNDArray ndArray1,
                               PtNDArray ndArray2)

max

public static PtNDArray max(PtNDArray ndArray1,
                            PtNDArray ndArray2)

max

public static PtNDArray max(PtNDArray ndArray)

max

public static PtNDArray max(PtNDArray ndArray,
                            long dim,
                            boolean keepDim)

min

public static PtNDArray min(PtNDArray ndArray1,
                            PtNDArray ndArray2)

min

public static PtNDArray min(PtNDArray ndArray)

min

public static PtNDArray min(PtNDArray ndArray,
                            long dim,
                            boolean keepDim)

mean

public static PtNDArray mean(PtNDArray ndArray)

mean

public static PtNDArray mean(PtNDArray ndArray,
                             long dim,
                             boolean keepDim)

sum

public static PtNDArray sum(PtNDArray ndArray)

sum

public static PtNDArray sum(PtNDArray ndArray,
                            long[] dims,
                            boolean keepDim)

split

public static ai.djl.ndarray.NDList split(PtNDArray ndArray,
                                          long size,
                                          long axis)

split

public static ai.djl.ndarray.NDList split(PtNDArray ndArray,
                                          long[] indices,
                                          long axis)

squeeze

public static PtNDArray squeeze(PtNDArray ndArray)

squeeze

public static PtNDArray squeeze(PtNDArray ndArray,
                                long dim)

unsqueeze

public static PtNDArray unsqueeze(PtNDArray ndArray,
                                  long dim)

flatten

public static PtNDArray flatten(PtNDArray ndArray,
                                long startDim,
                                long endDim)

abs

public static PtNDArray abs(PtNDArray ndArray)

floor

public static PtNDArray floor(PtNDArray ndArray)

ceil

public static PtNDArray ceil(PtNDArray ndArray)

round

public static PtNDArray round(PtNDArray ndArray)

trunc

public static PtNDArray trunc(PtNDArray ndArray)

clip

public static PtNDArray clip(PtNDArray ndArray,
                             java.lang.Number min,
                             java.lang.Number max)

exp

public static PtNDArray exp(PtNDArray ndArray)

log

public static PtNDArray log(PtNDArray ndArray)

log10

public static PtNDArray log10(PtNDArray ndArray)

log2

public static PtNDArray log2(PtNDArray ndArray)

sin

public static PtNDArray sin(PtNDArray ndArray)

cos

public static PtNDArray cos(PtNDArray ndArray)

tan

public static PtNDArray tan(PtNDArray ndArray)

asin

public static PtNDArray asin(PtNDArray ndArray)

acos

public static PtNDArray acos(PtNDArray ndArray)

atan

public static PtNDArray atan(PtNDArray ndArray)

sqrt

public static PtNDArray sqrt(PtNDArray ndArray)

sinh

public static PtNDArray sinh(PtNDArray ndArray)

cosh

public static PtNDArray cosh(PtNDArray ndArray)

tanh

public static PtNDArray tanh(PtNDArray ndArray)

all

public static PtNDArray all(PtNDArray ndArray)

any

public static PtNDArray any(PtNDArray ndArray)

none

public static PtNDArray none(PtNDArray ndArray)

eq

public static PtNDArray eq(PtNDArray self,
                           PtNDArray other)

neq

public static PtNDArray neq(PtNDArray self,
                            PtNDArray other)

gt

public static PtNDArray gt(PtNDArray self,
                           PtNDArray other)

gte

public static PtNDArray gte(PtNDArray self,
                            PtNDArray other)

lt

public static PtNDArray lt(PtNDArray self,
                           PtNDArray other)

lte

public static PtNDArray lte(PtNDArray self,
                            PtNDArray other)

neg

public static PtNDArray neg(PtNDArray ndArray)

negi

public static void negi(PtNDArray ndArray)

normal

public static PtNDArray normal(PtNDManager manager,
                               double mean,
                               double std,
                               ai.djl.ndarray.types.Shape size,
                               ai.djl.ndarray.types.DataType dataType,
                               ai.djl.Device device)

uniform

public static PtNDArray uniform(PtNDManager manager,
                                double low,
                                double high,
                                ai.djl.ndarray.types.Shape size,
                                ai.djl.ndarray.types.DataType dataType,
                                ai.djl.Device device)

eye

public static PtNDArray eye(PtNDManager manager,
                            int n,
                            int m,
                            ai.djl.ndarray.types.DataType dataType,
                            ai.djl.Device device,
                            ai.djl.ndarray.types.SparseFormat fmt)

upsampleBilinear2d

public static PtNDArray upsampleBilinear2d(PtNDArray ndArray,
                                           long[] size,
                                           boolean alignCorners)

getDataType

public static ai.djl.ndarray.types.DataType getDataType(PtNDArray ndArray)

getDevice

public static ai.djl.Device getDevice(PtNDArray ndArray)

getSparseFormat

public static ai.djl.ndarray.types.SparseFormat getSparseFormat(PtNDArray ndArray)

getShape

public static ai.djl.ndarray.types.Shape getShape(PtNDArray ndArray)

getByteBuffer

public static java.nio.ByteBuffer getByteBuffer(PtNDArray ndArray)

deleteNdArray

public static void deleteNdArray(Pointer handle)

deleteModule

public static void deleteModule(PtSymbolBlock block)

loadModule

public static PtSymbolBlock loadModule(PtNDManager manager,
                                       java.nio.file.Path path,
                                       ai.djl.Device device)

enableInferenceMode

public static void enableInferenceMode(PtSymbolBlock block)