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 void	adamUpdate(PtNDArray weight, PtNDArray grad, PtNDArray mean, PtNDArray variance, float lr, float wd, float rescaleGrad, float clipGrad, float beta1, float beta2, float eps)
static PtNDArray	adaptiveAvgPool(PtNDArray ndArray, ai.djl.ndarray.types.Shape outputSize)
static PtNDArray	adaptiveMaxPool(PtNDArray ndArray, ai.djl.ndarray.types.Shape outputSize)
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 void	attachGradient(PtNDArray ndArray)
static PtNDArray	avgPool(PtNDArray ndArray, ai.djl.ndarray.types.Shape kernelSize, ai.djl.ndarray.types.Shape stride, ai.djl.ndarray.types.Shape padding, boolean ceilMode, boolean countIncludePad)
static void	backward(PtNDArray ndArray, PtNDArray gradNd, boolean keepGraph, boolean createGraph)
static PtNDArray	batchNorm(PtNDArray ndArray, PtNDArray gamma, PtNDArray beta, PtNDArray runningMean, PtNDArray runningVar, boolean isTraining, double momentum, double eps)
static PtNDArray	booleanMask(PtNDArray ndArray, PtNDArray indicesNd)
static void	booleanMaskSet(PtNDArray ndArray, PtNDArray value, PtNDArray indicesNd)
static PtNDArray	broadcast(PtNDArray ndArray, ai.djl.ndarray.types.Shape shape)
static PtNDArray	cat(PtNDArray[] 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	convolution(PtNDArray ndArray, PtNDArray weight, PtNDArray bias, ai.djl.ndarray.types.Shape stride, ai.djl.ndarray.types.Shape padding, ai.djl.ndarray.types.Shape dilation, int groups)
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	createSparseCoo(PtNDArray indices, PtNDArray values, ai.djl.ndarray.types.Shape shape)
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 PtNDArray	cumSum(PtNDArray ndArray, long dim)
static void	deleteModule(long pointer)
static void	deleteNDArray(long handle)
static PtNDArray	detachGradient(PtNDArray ndArray)
static PtNDArray	div(PtNDArray ndArray1, PtNDArray ndArray2)
static void	divi(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	dot(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	dropout(PtNDArray ndArray, double prob, boolean training)
static PtNDArray	elu(PtNDArray ndArray, double alpha)
static void	enableInferenceMode(PtSymbolBlock block)
static void	enableTrainingMode(PtSymbolBlock block)
static PtNDArray	eq(PtNDArray self, PtNDArray other)
static PtNDArray	erfinv(PtNDArray ndArray)
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	flip(PtNDArray ndArray, long[] dims)
static PtNDArray	floor(PtNDArray ndArray)
static PtNDArray	full(PtNDManager manager, ai.djl.ndarray.types.Shape shape, double fillValue, ai.djl.ndarray.types.DataType dType, ai.djl.Device device, ai.djl.ndarray.types.SparseFormat fmt)
static PtNDArray	gelu(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 PtNDArray	getGradient(PtNDArray ndArray)
static java.lang.String	getGradientFunctionNames(PtNDArray ndArray)
static PtNDArray	getItem(PtNDArray ndArray, long[] indices)
static int	getLayout(PtNDArray array)
static int	getNumInteropThreads()
static int	getNumThreads()
static ai.djl.ndarray.types.Shape	getShape(PtNDArray ndArray)
static ai.djl.ndarray.types.SparseFormat	getSparseFormat(PtNDArray ndArray)
static ai.djl.ndarray.NDList	gru(PtNDArray input, PtNDArray hx, ai.djl.ndarray.NDList params, boolean hasBiases, int numLayers, double dropRate, boolean training, boolean bidirectional, boolean batchFirst)
static PtNDArray	gt(PtNDArray self, PtNDArray other)
static PtNDArray	gte(PtNDArray self, PtNDArray other)
static PtNDArray	index(PtNDArray ndArray, long[] minIndices, long[] maxIndices, long[] stepIndices)
static void	indexSet(PtNDArray ndArray, PtNDArray value, long[] minIndices, long[] maxIndices, long[] stepIndices)
static PtNDArray	interpolate(PtNDArray ndArray, long[] size, int mode, boolean alignCorners)
static PtNDArray	isInf(PtNDArray ndArray)
static PtNDArray	isNaN(PtNDArray ndArray)
static PtNDArray	leakyRelu(PtNDArray ndArray, double negativeSlope)
static PtNDArray	linear(PtNDArray input, PtNDArray weight, PtNDArray bias)
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, java.lang.String[] extraFileKeys, java.lang.String[] extraFileValues)
static PtNDArray	log(PtNDArray ndArray)
static PtNDArray	log10(PtNDArray ndArray)
static PtNDArray	log2(PtNDArray ndArray)
static PtNDArray	logicalAnd(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	logicalNot(PtNDArray ndArray)
static PtNDArray	logicalOr(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	logicalXor(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	logSoftmax(PtNDArray ndArray, long dim, ai.djl.ndarray.types.DataType dTpe)
static PtNDArray	lpPool(PtNDArray ndArray, double normType, ai.djl.ndarray.types.Shape kernelSize, ai.djl.ndarray.types.Shape stride, boolean ceilMode)
static ai.djl.ndarray.NDList	lstm(PtNDArray input, ai.djl.ndarray.NDList hx, ai.djl.ndarray.NDList params, boolean hasBiases, int numLayers, double dropRate, boolean training, boolean bidirectional, boolean batchFirst)
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	maxPool(PtNDArray ndArray, ai.djl.ndarray.types.Shape kernelSize, ai.djl.ndarray.types.Shape stride, ai.djl.ndarray.types.Shape padding, boolean ceilMode)
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	pick(PtNDArray ndArray, PtNDArray index, long dim)
static PtNDArray	pow(PtNDArray ndArray1, PtNDArray ndArray2)
static void	powi(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	prod(PtNDArray ndArray)
static PtNDArray	prod(PtNDArray ndArray, long dim, boolean keepDim)
static PtNDArray	randint(PtNDManager manager, long low, long high, ai.djl.ndarray.types.Shape size, ai.djl.ndarray.types.DataType dataType, ai.djl.Device device)
static PtNDArray	relu(PtNDArray ndArray)
static PtNDArray	remainder(PtNDArray ndArray1, PtNDArray ndArray2)
static void	remainderi(PtNDArray ndArray1, PtNDArray ndArray2)
static PtNDArray	repeat(PtNDArray ndArray, long repeat, long dim)
static boolean	requiresGrad(PtNDArray ndArray)
static PtNDArray	reshape(PtNDArray ndArray, long[] shape)
static ai.djl.ndarray.NDList	rnn(PtNDArray input, PtNDArray hx, ai.djl.ndarray.NDList params, boolean hasBiases, int numLayers, ai.djl.nn.recurrent.RNN.Activation activation, double dropRate, boolean training, boolean bidirectional, boolean batchFirst)
static PtNDArray	rot90(PtNDArray ndArray, int times, int[] axes)
static PtNDArray	round(PtNDArray ndArray)
static PtNDArray	selu(PtNDArray ndArray)
static void	set(PtNDArray self, java.nio.ByteBuffer data)
static void	setNumInteropThreads(int threads)
static void	setNumThreads(int threads)
static void	setSeed(long seed)
static void	sgdUpdate(PtNDArray weight, PtNDArray grad, PtNDArray state, float lr, float wd, float rescaleGrad, float clipGrad, float momentum)
static PtNDArray	sigmoid(PtNDArray ndArray)
static PtNDArray	sign(PtNDArray ndArray)
static void	signi(PtNDArray ndArray)
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	softPlus(PtNDArray ndArray)
static PtNDArray	softSign(PtNDArray ndArray)
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	square(PtNDArray ndArray)
static PtNDArray	squeeze(PtNDArray ndArray)
static PtNDArray	squeeze(PtNDArray ndArray, long dim)
static PtNDArray	stack(PtNDArray[] arrays, int dim)
static void	startProfile(boolean useCuda, boolean recordShape, boolean profileMemory) Calls this method to start profile the area you are interested in.
static void	stopProfile(java.lang.String outputFile)
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	tile(PtNDArray ndArray, long[] repeats)
static PtNDArray	to(PtNDArray ndArray, ai.djl.ndarray.types.DataType dataType, ai.djl.Device device, boolean copy)
static PtNDArray	toDense(PtNDArray ndArray)
static PtNDArray	toSparse(PtNDArray ndArray)
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	where(PtNDArray condition, PtNDArray self, PtNDArray other)
static void	zeroGrad(PtNDArray weight)
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

getNumInteropThreads

public static int getNumInteropThreads()

getNumThreads

public static int getNumThreads()

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)

startProfile

public static void startProfile(boolean useCuda,
                                boolean recordShape,
                                boolean profileMemory)

Calls this method to start profile the area you are interested in.

Example usage

      JniUtils.startProfile(false, true, true);
      Predictor.predict(img);
      JniUtils.stopProfile(outputFile)
 

Parameters:

useCuda - Enables timing of CUDA events as well using the cudaEvent API.

recordShape - If shapes recording is set, information about input dimensions will be collected

profileMemory - Whether to report memory usage

stopProfile

public static void stopProfile(java.lang.String outputFile)

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)

full

public static PtNDArray full(PtNDManager manager,
                             ai.djl.ndarray.types.Shape shape,
                             double fillValue,
                             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)

createSparseCoo

public static PtNDArray createSparseCoo(PtNDArray indices,
                                        PtNDArray values,
                                        ai.djl.ndarray.types.Shape shape)

to

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

toSparse

public static PtNDArray toSparse(PtNDArray ndArray)

toDense

public static PtNDArray toDense(PtNDArray ndArray)

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)

index

public static PtNDArray index(PtNDArray ndArray,
                              long[] minIndices,
                              long[] maxIndices,
                              long[] stepIndices)

indexSet

public static void indexSet(PtNDArray ndArray,
                            PtNDArray value,
                            long[] minIndices,
                            long[] maxIndices,
                            long[] stepIndices)

set

public static void set(PtNDArray self,
                       java.nio.ByteBuffer data)

pick

public static PtNDArray pick(PtNDArray ndArray,
                             PtNDArray index,
                             long dim)

where

public static PtNDArray where(PtNDArray condition,
                              PtNDArray self,
                              PtNDArray other)

booleanMask

public static PtNDArray booleanMask(PtNDArray ndArray,
                                    PtNDArray indicesNd)

booleanMaskSet

public static void booleanMaskSet(PtNDArray ndArray,
                                  PtNDArray value,
                                  PtNDArray indicesNd)

getItem

public static PtNDArray getItem(PtNDArray ndArray,
                                long[] indices)

clone

public static PtNDArray clone(PtNDArray ndArray)

reshape

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

stack

public static PtNDArray stack(PtNDArray[] arrays,
                              int dim)

cat

public static PtNDArray cat(PtNDArray[] arrays,
                            long dim)

tile

public static PtNDArray tile(PtNDArray ndArray,
                             long[] repeats)

repeat

public static PtNDArray repeat(PtNDArray ndArray,
                               long repeat,
                               long dim)

softmax

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

logSoftmax

public static PtNDArray logSoftmax(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)

flip

public static PtNDArray flip(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)

sign

public static PtNDArray sign(PtNDArray ndArray)

signi

public static void signi(PtNDArray ndArray)

logicalAnd

public static PtNDArray logicalAnd(PtNDArray ndArray1,
                                   PtNDArray ndArray2)

logicalOr

public static PtNDArray logicalOr(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)

dot

public static PtNDArray dot(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)

rot90

public static PtNDArray rot90(PtNDArray ndArray,
                              int times,
                              int[] axes)

sum

public static PtNDArray sum(PtNDArray ndArray)

sum

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

prod

public static PtNDArray prod(PtNDArray ndArray)

prod

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

cumSum

public static PtNDArray cumSum(PtNDArray ndArray,
                               long dim)

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)

square

public static PtNDArray square(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)

sigmoid

public static PtNDArray sigmoid(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)

isNaN

public static PtNDArray isNaN(PtNDArray ndArray)

isInf

public static PtNDArray isInf(PtNDArray ndArray)

randint

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

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)

erfinv

public static PtNDArray erfinv(PtNDArray ndArray)

interpolate

public static PtNDArray interpolate(PtNDArray ndArray,
                                    long[] size,
                                    int mode,
                                    boolean alignCorners)

linear

public static PtNDArray linear(PtNDArray input,
                               PtNDArray weight,
                               PtNDArray bias)

relu

public static PtNDArray relu(PtNDArray ndArray)

softPlus

public static PtNDArray softPlus(PtNDArray ndArray)

softSign

public static PtNDArray softSign(PtNDArray ndArray)

leakyRelu

public static PtNDArray leakyRelu(PtNDArray ndArray,
                                  double negativeSlope)

elu

public static PtNDArray elu(PtNDArray ndArray,
                            double alpha)

selu

public static PtNDArray selu(PtNDArray ndArray)

gelu

public static PtNDArray gelu(PtNDArray ndArray)

convolution

public static PtNDArray convolution(PtNDArray ndArray,
                                    PtNDArray weight,
                                    PtNDArray bias,
                                    ai.djl.ndarray.types.Shape stride,
                                    ai.djl.ndarray.types.Shape padding,
                                    ai.djl.ndarray.types.Shape dilation,
                                    int groups)

batchNorm

public static PtNDArray batchNorm(PtNDArray ndArray,
                                  PtNDArray gamma,
                                  PtNDArray beta,
                                  PtNDArray runningMean,
                                  PtNDArray runningVar,
                                  boolean isTraining,
                                  double momentum,
                                  double eps)

dropout

public static PtNDArray dropout(PtNDArray ndArray,
                                double prob,
                                boolean training)

rnn

public static ai.djl.ndarray.NDList rnn(PtNDArray input,
                                        PtNDArray hx,
                                        ai.djl.ndarray.NDList params,
                                        boolean hasBiases,
                                        int numLayers,
                                        ai.djl.nn.recurrent.RNN.Activation activation,
                                        double dropRate,
                                        boolean training,
                                        boolean bidirectional,
                                        boolean batchFirst)

gru

public static ai.djl.ndarray.NDList gru(PtNDArray input,
                                        PtNDArray hx,
                                        ai.djl.ndarray.NDList params,
                                        boolean hasBiases,
                                        int numLayers,
                                        double dropRate,
                                        boolean training,
                                        boolean bidirectional,
                                        boolean batchFirst)

lstm

public static ai.djl.ndarray.NDList lstm(PtNDArray input,
                                         ai.djl.ndarray.NDList hx,
                                         ai.djl.ndarray.NDList params,
                                         boolean hasBiases,
                                         int numLayers,
                                         double dropRate,
                                         boolean training,
                                         boolean bidirectional,
                                         boolean batchFirst)

avgPool

public static PtNDArray avgPool(PtNDArray ndArray,
                                ai.djl.ndarray.types.Shape kernelSize,
                                ai.djl.ndarray.types.Shape stride,
                                ai.djl.ndarray.types.Shape padding,
                                boolean ceilMode,
                                boolean countIncludePad)

maxPool

public static PtNDArray maxPool(PtNDArray ndArray,
                                ai.djl.ndarray.types.Shape kernelSize,
                                ai.djl.ndarray.types.Shape stride,
                                ai.djl.ndarray.types.Shape padding,
                                boolean ceilMode)

adaptiveMaxPool

public static PtNDArray adaptiveMaxPool(PtNDArray ndArray,
                                        ai.djl.ndarray.types.Shape outputSize)

adaptiveAvgPool

public static PtNDArray adaptiveAvgPool(PtNDArray ndArray,
                                        ai.djl.ndarray.types.Shape outputSize)

lpPool

public static PtNDArray lpPool(PtNDArray ndArray,
                               double normType,
                               ai.djl.ndarray.types.Shape kernelSize,
                               ai.djl.ndarray.types.Shape stride,
                               boolean ceilMode)

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(long handle)

requiresGrad

public static boolean requiresGrad(PtNDArray ndArray)

getGradientFunctionNames

public static java.lang.String getGradientFunctionNames(PtNDArray ndArray)

attachGradient

public static void attachGradient(PtNDArray ndArray)

detachGradient

public static PtNDArray detachGradient(PtNDArray ndArray)

getGradient

public static PtNDArray getGradient(PtNDArray ndArray)

backward

public static void backward(PtNDArray ndArray,
                            PtNDArray gradNd,
                            boolean keepGraph,
                            boolean createGraph)

deleteModule

public static void deleteModule(long pointer)

loadModule

public static PtSymbolBlock loadModule(PtNDManager manager,
                                       java.nio.file.Path path,
                                       ai.djl.Device device,
                                       java.lang.String[] extraFileKeys,
                                       java.lang.String[] extraFileValues)

enableInferenceMode

public static void enableInferenceMode(PtSymbolBlock block)

enableTrainingMode

public static void enableTrainingMode(PtSymbolBlock block)

zeroGrad

public static void zeroGrad(PtNDArray weight)

adamUpdate

public static void adamUpdate(PtNDArray weight,
                              PtNDArray grad,
                              PtNDArray mean,
                              PtNDArray variance,
                              float lr,
                              float wd,
                              float rescaleGrad,
                              float clipGrad,
                              float beta1,
                              float beta2,
                              float eps)

sgdUpdate

public static void sgdUpdate(PtNDArray weight,
                             PtNDArray grad,
                             PtNDArray state,
                             float lr,
                             float wd,
                             float rescaleGrad,
                             float clipGrad,
                             float momentum)

getLayout

public static int getLayout(PtNDArray array)