public class PtNDArrayEx
extends java.lang.Object
implements ai.djl.ndarray.internal.NDArrayEx
PtNDArrayEx is the PyTorch implementation of the NDArrayEx.| Modifier and Type | Method and Description |
|---|---|
void |
adamUpdate(ai.djl.ndarray.NDList inputs,
ai.djl.ndarray.NDList weights,
float learningRate,
float weightDecay,
float rescaleGrad,
float clipGrad,
float beta1,
float beta2,
float epsilon,
boolean lazyUpdate) |
PtNDArray |
avgPool(ai.djl.ndarray.types.Shape kernel,
ai.djl.ndarray.types.Shape stride,
ai.djl.ndarray.types.Shape pad,
ai.djl.nn.pooling.PoolingConvention poolingConvention,
boolean countIncludePad) |
ai.djl.ndarray.NDList |
batchNorm(ai.djl.ndarray.NDList inputs,
float epsilon,
float momentum,
int axis,
boolean center,
boolean scale,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional) |
PtNDArray |
concat(ai.djl.ndarray.NDList list,
int axis) |
ai.djl.ndarray.NDList |
convolution(ai.djl.ndarray.NDList inputs,
ai.djl.ndarray.types.Shape kernel,
ai.djl.ndarray.types.Shape stride,
ai.djl.ndarray.types.Shape pad,
ai.djl.ndarray.types.Shape dilate,
int numFilters,
int numGroups,
java.lang.String layout,
boolean noBias,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional) |
ai.djl.ndarray.NDList |
dropout(ai.djl.ndarray.NDList inputs,
float probability,
int[] sharedAxes,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional) |
PtNDArray |
elu(float alpha) |
ai.djl.ndarray.NDList |
embedding(ai.djl.ndarray.NDList inputs,
int numItems,
int embeddingSize,
ai.djl.ndarray.types.DataType dataType,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional) |
ai.djl.ndarray.NDList |
fullyConnected(ai.djl.ndarray.NDList inputs,
long outChannels,
boolean flatten,
boolean noBias,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional) |
PtNDArray |
gelu() |
PtNDArray |
getArray() |
PtNDArray |
globalAvgPool() |
PtNDArray |
globalLpPool(int pValue) |
PtNDArray |
globalMaxPool() |
PtNDArray |
globalSumPool() |
PtNDArray |
leakyRelu(float alpha) |
PtNDArray |
lpPool(ai.djl.ndarray.types.Shape kernel,
ai.djl.ndarray.types.Shape stride,
ai.djl.ndarray.types.Shape pad,
ai.djl.nn.pooling.PoolingConvention poolingConvention,
int pValue) |
ai.djl.ndarray.NDList |
lstm(ai.djl.ndarray.NDList inputs,
long stateSize,
float dropRate,
int numStackedLayers,
boolean useSequenceLength,
boolean useBidirectional,
boolean stateOutputs,
double lstmStateClipMin,
double lstmStateClipMax,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional) |
PtNDArray |
maxPool(ai.djl.ndarray.types.Shape kernel,
ai.djl.ndarray.types.Shape stride,
ai.djl.ndarray.types.Shape pad,
ai.djl.nn.pooling.PoolingConvention poolingConvention) |
ai.djl.ndarray.NDList |
multiBoxDetection(ai.djl.ndarray.NDList inputs,
boolean clip,
float threshold,
int backgroundId,
float nmsThreshold,
boolean forceSuppress,
int nmsTopK) |
ai.djl.ndarray.NDList |
multiBoxPrior(java.util.List<java.lang.Float> sizes,
java.util.List<java.lang.Float> ratios,
java.util.List<java.lang.Float> steps,
java.util.List<java.lang.Float> offsets,
boolean clip) |
ai.djl.ndarray.NDList |
multiBoxTarget(ai.djl.ndarray.NDList inputs,
float iouThreshold,
float ignoreLabel,
float negativeMiningRatio,
float negativeMiningThreshold,
int minNegativeSamples) |
void |
nagUpdate(ai.djl.ndarray.NDList inputs,
ai.djl.ndarray.NDList weights,
float learningRate,
float weightDecay,
float rescaleGrad,
float clipGrad,
float momentum) |
PtNDArray |
pick(ai.djl.ndarray.NDArray index,
int axis,
boolean keepDims,
java.lang.String mode) |
ai.djl.ndarray.NDList |
prelu(ai.djl.ndarray.NDList inputs,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional) |
PtNDArray |
rdiv(ai.djl.ndarray.NDArray b) |
PtNDArray |
rdiv(java.lang.Number n) |
PtNDArray |
rdivi(ai.djl.ndarray.NDArray b) |
PtNDArray |
rdivi(java.lang.Number n) |
PtNDArray |
relu() |
PtNDArray |
resize(int width,
int height) |
PtNDArray |
rmod(ai.djl.ndarray.NDArray b) |
PtNDArray |
rmod(java.lang.Number n) |
PtNDArray |
rmodi(ai.djl.ndarray.NDArray b) |
PtNDArray |
rmodi(java.lang.Number n) |
ai.djl.ndarray.NDList |
rnn(ai.djl.ndarray.NDList inputs,
java.lang.String mode,
long stateSize,
float dropRate,
int numStackedLayers,
boolean useSequenceLength,
boolean useBidirectional,
boolean stateOutputs,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional) |
PtNDArray |
rpow(java.lang.Number n) |
PtNDArray |
rpowi(java.lang.Number n) |
PtNDArray |
rsub(ai.djl.ndarray.NDArray b) |
PtNDArray |
rsub(java.lang.Number n) |
PtNDArray |
rsubi(ai.djl.ndarray.NDArray b) |
PtNDArray |
rsubi(java.lang.Number n) |
PtNDArray |
selu() |
void |
sgdUpdate(ai.djl.ndarray.NDList inputs,
ai.djl.ndarray.NDList weights,
float learningRate,
float weightDecay,
float rescaleGrad,
float clipGrad,
float momentum,
boolean lazyUpdate) |
PtNDArray |
sigmoid() |
PtNDArray |
softrelu() |
PtNDArray |
softsign() |
PtNDArray |
stack(ai.djl.ndarray.NDList arrays,
int axis) |
PtNDArray |
sumPool(ai.djl.ndarray.types.Shape kernel,
ai.djl.ndarray.types.Shape stride,
ai.djl.ndarray.types.Shape pad,
ai.djl.nn.pooling.PoolingConvention poolingConvention) |
PtNDArray |
tanh() |
PtNDArray |
where(ai.djl.ndarray.NDArray condition,
ai.djl.ndarray.NDArray other) |
public PtNDArray rdiv(java.lang.Number n)
rdiv in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rdiv(ai.djl.ndarray.NDArray b)
rdiv in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rdivi(java.lang.Number n)
rdivi in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rdivi(ai.djl.ndarray.NDArray b)
rdivi in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rsub(java.lang.Number n)
rsub in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rsub(ai.djl.ndarray.NDArray b)
rsub in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rsubi(java.lang.Number n)
rsubi in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rsubi(ai.djl.ndarray.NDArray b)
rsubi in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rmod(java.lang.Number n)
rmod in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rmod(ai.djl.ndarray.NDArray b)
rmod in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rmodi(java.lang.Number n)
rmodi in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rmodi(ai.djl.ndarray.NDArray b)
rmodi in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rpow(java.lang.Number n)
rpow in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray rpowi(java.lang.Number n)
rpowi in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray relu()
relu in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray sigmoid()
sigmoid in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray tanh()
tanh in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray softrelu()
softrelu in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray softsign()
softsign in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray leakyRelu(float alpha)
leakyRelu in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray elu(float alpha)
elu in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray selu()
selu in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray gelu()
gelu in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray maxPool(ai.djl.ndarray.types.Shape kernel, ai.djl.ndarray.types.Shape stride, ai.djl.ndarray.types.Shape pad, ai.djl.nn.pooling.PoolingConvention poolingConvention)
maxPool in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray globalMaxPool()
globalMaxPool in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray sumPool(ai.djl.ndarray.types.Shape kernel, ai.djl.ndarray.types.Shape stride, ai.djl.ndarray.types.Shape pad, ai.djl.nn.pooling.PoolingConvention poolingConvention)
sumPool in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray globalSumPool()
globalSumPool in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray avgPool(ai.djl.ndarray.types.Shape kernel, ai.djl.ndarray.types.Shape stride, ai.djl.ndarray.types.Shape pad, ai.djl.nn.pooling.PoolingConvention poolingConvention, boolean countIncludePad)
avgPool in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray globalAvgPool()
globalAvgPool in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray lpPool(ai.djl.ndarray.types.Shape kernel, ai.djl.ndarray.types.Shape stride, ai.djl.ndarray.types.Shape pad, ai.djl.nn.pooling.PoolingConvention poolingConvention, int pValue)
lpPool in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray globalLpPool(int pValue)
globalLpPool in interface ai.djl.ndarray.internal.NDArrayExpublic void adamUpdate(ai.djl.ndarray.NDList inputs,
ai.djl.ndarray.NDList weights,
float learningRate,
float weightDecay,
float rescaleGrad,
float clipGrad,
float beta1,
float beta2,
float epsilon,
boolean lazyUpdate)
adamUpdate in interface ai.djl.ndarray.internal.NDArrayExpublic void nagUpdate(ai.djl.ndarray.NDList inputs,
ai.djl.ndarray.NDList weights,
float learningRate,
float weightDecay,
float rescaleGrad,
float clipGrad,
float momentum)
nagUpdate in interface ai.djl.ndarray.internal.NDArrayExpublic void sgdUpdate(ai.djl.ndarray.NDList inputs,
ai.djl.ndarray.NDList weights,
float learningRate,
float weightDecay,
float rescaleGrad,
float clipGrad,
float momentum,
boolean lazyUpdate)
sgdUpdate in interface ai.djl.ndarray.internal.NDArrayExpublic ai.djl.ndarray.NDList convolution(ai.djl.ndarray.NDList inputs,
ai.djl.ndarray.types.Shape kernel,
ai.djl.ndarray.types.Shape stride,
ai.djl.ndarray.types.Shape pad,
ai.djl.ndarray.types.Shape dilate,
int numFilters,
int numGroups,
java.lang.String layout,
boolean noBias,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional)
convolution in interface ai.djl.ndarray.internal.NDArrayExpublic ai.djl.ndarray.NDList fullyConnected(ai.djl.ndarray.NDList inputs,
long outChannels,
boolean flatten,
boolean noBias,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional)
fullyConnected in interface ai.djl.ndarray.internal.NDArrayExpublic ai.djl.ndarray.NDList embedding(ai.djl.ndarray.NDList inputs,
int numItems,
int embeddingSize,
ai.djl.ndarray.types.DataType dataType,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional)
embedding in interface ai.djl.ndarray.internal.NDArrayExpublic ai.djl.ndarray.NDList prelu(ai.djl.ndarray.NDList inputs,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional)
prelu in interface ai.djl.ndarray.internal.NDArrayExpublic ai.djl.ndarray.NDList dropout(ai.djl.ndarray.NDList inputs,
float probability,
int[] sharedAxes,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional)
dropout in interface ai.djl.ndarray.internal.NDArrayExpublic ai.djl.ndarray.NDList batchNorm(ai.djl.ndarray.NDList inputs,
float epsilon,
float momentum,
int axis,
boolean center,
boolean scale,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional)
batchNorm in interface ai.djl.ndarray.internal.NDArrayExpublic ai.djl.ndarray.NDList rnn(ai.djl.ndarray.NDList inputs,
java.lang.String mode,
long stateSize,
float dropRate,
int numStackedLayers,
boolean useSequenceLength,
boolean useBidirectional,
boolean stateOutputs,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional)
rnn in interface ai.djl.ndarray.internal.NDArrayExpublic ai.djl.ndarray.NDList lstm(ai.djl.ndarray.NDList inputs,
long stateSize,
float dropRate,
int numStackedLayers,
boolean useSequenceLength,
boolean useBidirectional,
boolean stateOutputs,
double lstmStateClipMin,
double lstmStateClipMax,
ai.djl.util.PairList<java.lang.String,java.lang.Object> additional)
lstm in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray resize(int width, int height)
resize in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray pick(ai.djl.ndarray.NDArray index, int axis, boolean keepDims, java.lang.String mode)
pick in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray where(ai.djl.ndarray.NDArray condition, ai.djl.ndarray.NDArray other)
where in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray stack(ai.djl.ndarray.NDList arrays, int axis)
stack in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray concat(ai.djl.ndarray.NDList list, int axis)
concat in interface ai.djl.ndarray.internal.NDArrayExpublic ai.djl.ndarray.NDList multiBoxTarget(ai.djl.ndarray.NDList inputs,
float iouThreshold,
float ignoreLabel,
float negativeMiningRatio,
float negativeMiningThreshold,
int minNegativeSamples)
multiBoxTarget in interface ai.djl.ndarray.internal.NDArrayExpublic ai.djl.ndarray.NDList multiBoxPrior(java.util.List<java.lang.Float> sizes,
java.util.List<java.lang.Float> ratios,
java.util.List<java.lang.Float> steps,
java.util.List<java.lang.Float> offsets,
boolean clip)
multiBoxPrior in interface ai.djl.ndarray.internal.NDArrayExpublic ai.djl.ndarray.NDList multiBoxDetection(ai.djl.ndarray.NDList inputs,
boolean clip,
float threshold,
int backgroundId,
float nmsThreshold,
boolean forceSuppress,
int nmsTopK)
multiBoxDetection in interface ai.djl.ndarray.internal.NDArrayExpublic PtNDArray getArray()
getArray in interface ai.djl.ndarray.internal.NDArrayEx