Index (Deep Java Library 0.26.0

A B C D F G I L M N O R S T U V Y
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form

A

ai.djl.basicmodelzoo - package ai.djl.basicmodelzoo: Contains the built-in BasicModelZoo.
ai.djl.basicmodelzoo.basic - package ai.djl.basicmodelzoo.basic: Contains the basic built-in models.
ai.djl.basicmodelzoo.cv.classification - package ai.djl.basicmodelzoo.cv.classification: Contains classes for the Application.CV.IMAGE_CLASSIFICATION models in the BasicModelZoo.
ai.djl.basicmodelzoo.cv.object_detection.ssd - package ai.djl.basicmodelzoo.cv.object_detection.ssd: Contains classes for the Application.CV.OBJECT_DETECTION models in the BasicModelZoo.
ai.djl.basicmodelzoo.cv.object_detection.yolo - package ai.djl.basicmodelzoo.cv.object_detection.yolo: Contains classes for the Application.CV.OBJECT_DETECTION models in the BasicModelZoo.
ai.djl.basicmodelzoo.nlp - package ai.djl.basicmodelzoo.nlp: Contains classes for the natural language processing section (Application.NLP) of the BasicModelZoo.
ai.djl.basicmodelzoo.tabular - package ai.djl.basicmodelzoo.tabular: Contains classes for the tabular section (Application.Tabular) of the BasicModelZoo.
alexNet(AlexNet.Builder) - Static method in class ai.djl.basicmodelzoo.cv.classification.AlexNet: Creates a AlexNet network block with the help of the AlexNet Builder.
AlexNet - Class in ai.djl.basicmodelzoo.cv.classification: AlexNet contains a generic implementation of AlexNet adapted from [torchvision implmentation](https://github.com/pytorch/vision/blob/master/torchvision/models/alexnet.py)
AlexNet.Builder - Class in ai.djl.basicmodelzoo.cv.classification: The Builder to construct a AlexNet object.

B

basicBlock(int, float, float) - Static method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3: Builds a Block that a basic residual block unit used in DarkNet53.
BasicModelZoo - Class in ai.djl.basicmodelzoo: Model Zoo is a repository that contains all models for DJL.
BasicZooProvider - Class in ai.djl.basicmodelzoo: An imperative model zoo provider implements the ZooProvider interface.
BasicZooProvider() - Constructor for class ai.djl.basicmodelzoo.BasicZooProvider
build() - Method in class ai.djl.basicmodelzoo.cv.classification.AlexNet.Builder: Builds a AlexNet block.
build() - Method in class ai.djl.basicmodelzoo.cv.classification.GoogLeNet.Builder: Builds a GoogLeNet block.
build() - Method in class ai.djl.basicmodelzoo.cv.classification.LeNet.Builder: Builds a LeNet block.
build() - Method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV1.Builder: Builds a MobileNetV1 block.
build() - Method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2.Builder: Builds a MobileNetV2 block.
build() - Method in class ai.djl.basicmodelzoo.cv.classification.NiN.Builder: Builds a NiN block.
build() - Method in class ai.djl.basicmodelzoo.cv.classification.ResNetV1.Builder: Builds a ResNetV1 block.
build() - Method in class ai.djl.basicmodelzoo.cv.classification.VGG.Builder: Builds a VGG block.
build() - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection.Builder: Builds a SingleShotDetection block.
build() - Method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3.Builder: Builds a YOLOV3 block.
build() - Method in class ai.djl.basicmodelzoo.tabular.TabNet.Builder: Builds a TabNet with given Builder.
buildAttentionTransformer(int) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.Builder: Builds an attentionTransformer with given parameter for test.
buildDarkNet() - Method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3.Builder: Builds a Block that represents the backbone of yolov3, which is called DarkNet53.
builder() - Static method in class ai.djl.basicmodelzoo.cv.classification.AlexNet: Creates a builder to build a AlexNet.
builder() - Static method in class ai.djl.basicmodelzoo.cv.classification.GoogLeNet: Creates a builder to build a GoogLeNet.
builder() - Static method in class ai.djl.basicmodelzoo.cv.classification.LeNet: Creates a builder to build a LeNet.
builder() - Static method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV1: Creates a builder to build a MobileNetV1.
builder() - Static method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2: Creates a builder to build a MobileNetV2.
builder() - Static method in class ai.djl.basicmodelzoo.cv.classification.NiN: Creates a builder to build a NiN.
builder() - Static method in class ai.djl.basicmodelzoo.cv.classification.ResNetV1: Creates a builder to build a ResNetV1.
builder() - Static method in class ai.djl.basicmodelzoo.cv.classification.VGG: Creates a builder to build a VGG.
builder() - Static method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection: Creates a builder to build a SingleShotDetection.
builder() - Static method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3: Creates a builder to build a YOLOV3.
builder() - Static method in class ai.djl.basicmodelzoo.tabular.TabNet: Creates a builder to build a TabNet.
Builder() - Constructor for class ai.djl.basicmodelzoo.cv.classification.VGG.Builder
Builder() - Constructor for class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3.Builder
Builder() - Constructor for class ai.djl.basicmodelzoo.tabular.TabNet.Builder

C

convolutionBlock(int, int, float, float) - Static method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3: Builds a Block that represents a conv-bn-leakyRelu unit for darkNet53.

D

DecisionStep(int, int, int, List<Block>, int, int, float) - Constructor for class ai.djl.basicmodelzoo.tabular.TabNet.DecisionStep: Creates a TabNet.DecisionStep with given parameters.
depthSeparableConv2d(int, int, int, MobileNetV1.Builder) - Static method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV1: Builds a Block that represent a depthWise-pointWise Unit used in the implementation of the MobileNet Model.

F

featureTransformer(List<Block>, int, int, int, float) - Static method in class ai.djl.basicmodelzoo.tabular.TabNet: Creates a featureTransformer Block.
FILTERLENGTH - Static variable in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.basicmodelzoo.nlp.SimpleTextDecoder
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.AttentionTransformer
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.DecisionStep
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.basicmodelzoo.tabular.TabNet

G

getAnchorPredictionBlock(int) - Static method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection: Creates a anchor prediction block used in an SSD.
getClassPredictionBlock(int, int) - Static method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection: Creates a class prediction block used in an SSD.
getDownSamplingBlock(int) - Static method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection: Creates a Block that reduces the size of a convolutional block by half.
getGroupId() - Method in class ai.djl.basicmodelzoo.BasicModelZoo
getModelZoo() - Method in class ai.djl.basicmodelzoo.BasicZooProvider
getOutputShapes(Shape[]) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection
getOutputShapes(Shape[]) - Method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3
getOutputShapes(Shape[]) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.AttentionTransformer
getOutputShapes(Shape[]) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.DecisionStep
getOutputShapes(Shape[]) - Method in class ai.djl.basicmodelzoo.tabular.TabNet
getStates(NDList) - Method in class ai.djl.basicmodelzoo.nlp.SimpleTextEncoder
getSupportedEngines() - Method in class ai.djl.basicmodelzoo.BasicModelZoo
gluBlock(Block, int, int, float) - Static method in class ai.djl.basicmodelzoo.tabular.TabNet: Creates a FC-BN-GLU block used in tabNet.
googLeNet(GoogLeNet.Builder) - Static method in class ai.djl.basicmodelzoo.cv.classification.GoogLeNet: Creates a GoogLeNet network block with the help of the GoogLeNet Builder.
GoogLeNet - Class in ai.djl.basicmodelzoo.cv.classification: GoogLeNet uses a stack of a total of 9 inception blocks and global average pooling to generate its estimates.
GoogLeNet.Builder - Class in ai.djl.basicmodelzoo.cv.classification: The Builder to construct a GoogLeNet object.
GROUP_ID - Static variable in class ai.djl.basicmodelzoo.BasicModelZoo

I

inceptionBlock(int, int[], int[], int) - Method in class ai.djl.basicmodelzoo.cv.classification.GoogLeNet: Creates a constituent inception block that becomes a part of the whole GoogLeNet model.
initialize(NDManager, DataType, Shape...) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.AttentionTransformer
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.DecisionStep
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.basicmodelzoo.tabular.TabNet

L

leNet(LeNet.Builder) - Static method in class ai.djl.basicmodelzoo.cv.classification.LeNet: Creates a LeNet network block with the help of the LeNet Builder.
LeNet - Class in ai.djl.basicmodelzoo.cv.classification: The model was introduced (and named for) Yann Lecun, for the purpose of recognizing handwritten digits in images [LeNet5](http://yann.lecun.com/exdb/lenet/).
LeNet.Builder - Class in ai.djl.basicmodelzoo.cv.classification: The Builder to construct a LeNet object.
linearBottleNeck(int, int, int, int, float) - Static method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2: Builds a Block that represent an inverted residual Unit used in the implementation of the MobileNetV2 Model.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection

M

makeLastLayers(int, int, float, float) - Static method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3: Builds a Block that represents the feature head in yolov3.
makeLayer(int, int, float, float) - Static method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3: Creates repeated Residual Blocks used in DarkNet53.
makeOutputLayers(int, int, float, float) - Static method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3: Builds a Block that represents the output layer of yolov3.
makeStage(int, int, int, int, int, float) - Static method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2: Builds a Block that represent multiple repeats of an inverted residual Unit.
Mlp - Class in ai.djl.basicmodelzoo.basic: Multilayer Perceptron (MLP) NeuralNetworks.
Mlp(int, int, int[]) - Constructor for class ai.djl.basicmodelzoo.basic.Mlp: Create an MLP NeuralNetwork using RELU.
Mlp(int, int, int[], Function<NDList, NDList>) - Constructor for class ai.djl.basicmodelzoo.basic.Mlp: Create an MLP NeuralNetwork.
MlpBlockFactory - Class in ai.djl.basicmodelzoo.basic: A BlockFactory class that creates MLP block.
MlpBlockFactory() - Constructor for class ai.djl.basicmodelzoo.basic.MlpBlockFactory
mobilenet(MobileNetV1.Builder) - Static method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV1: Creates a new Block of MobileNetV1 with the arguments from the given MobileNetV1.Builder.
MobileNetV1 - Class in ai.djl.basicmodelzoo.cv.classification: MobileNetV1 contains a generic implementation of Mobilenet adapted from https://github.com/weiaicunzai/pytorch-cifar100/blob/master/models/mobilenet.py (Original author weiaicunzai).
MobileNetV1.Builder - Class in ai.djl.basicmodelzoo.cv.classification: The Builder to construct a MobileNetV1 object.
mobilenetV2(MobileNetV2.Builder) - Static method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2: Creates a new Block of MobileNetV2 with the arguments from the given MobileNetV2.Builder.
MobileNetV2 - Class in ai.djl.basicmodelzoo.cv.classification: MobileNetV2 contains a generic implementation of MobilenetV2 adapted from https://github.com/weiaicunzai/pytorch-cifar100/blob/master/models/mobilenetv2.py (Original author weiaicunzai).
MobileNetV2.Builder - Class in ai.djl.basicmodelzoo.cv.classification: The Builder to construct a MobileNetV2 object.
MULTILENGTH - Static variable in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2

N

newBlock(Model, Path, Map<String, ?>) - Method in class ai.djl.basicmodelzoo.basic.MlpBlockFactory
newBlock(Model, Path, Map<String, ?>) - Method in class ai.djl.basicmodelzoo.cv.classification.ResnetBlockFactory
newBlock(Model, Path, Map<String, ?>) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SsdBlockFactory
niN(NiN.Builder) - Static method in class ai.djl.basicmodelzoo.cv.classification.NiN: The NiN block consists of one convolutional layer followed by two 1×1 convolutional layers that act as per-pixel fully-connected layers with ReLU activations.
NiN - Class in ai.djl.basicmodelzoo.cv.classification: NiN uses convolutional layers with window shapes of 11×11 , 5×5 , and 3×3 , and the corresponding numbers of output channels are the same as in AlexNet.
NiN.Builder - Class in ai.djl.basicmodelzoo.cv.classification: The Builder to construct a NiN object.
niNBlock(int, Shape, Shape, Shape) - Method in class ai.djl.basicmodelzoo.cv.classification.NiN: Creates a constituent NiN block that becomes a part of the whole NiN model.

O

optBatchNormMomentum(float) - Method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV1.Builder: Sets the momentum of batchNorm layer.
optBatchNormMomentum(float) - Method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2.Builder: Sets the momentum of batchNorm layer.
optBatchNormMomentum(float) - Method in class ai.djl.basicmodelzoo.cv.classification.ResNetV1.Builder: Sets the momentum of batchNorm layer.
optBatchNormMomentum(float) - Method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3.Builder: Sets the momentum for batchNorm layer.
optBatchNormMomentum(float) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.Builder: Sets the momentum for batchNorm layer.
optDarkNetOutSize(int) - Method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3.Builder: Sets the out size of darkNet for testing.
optFeatures(List<Block>) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection.Builder: Sets the Conv2d blocks to be appended to the network to get multi-output network.
optFilters(int[]) - Method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2.Builder: Sets the filters(the value c defined in the paper) of customized MobileNetV2.
optGlobalPool(boolean) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection.Builder: Sets the boolean whether to attach a global average pooling layer as the last output layer.
optLeakyAlpha(float) - Method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3.Builder: Sets the alpha for leakyRelu activation.
optMultiTimes(int[]) - Method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2.Builder: Sets the multiTimes(the value t defined in the paper) of each bottleNeck of MobileNetV2.
optNumA(int) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.Builder: Sets the number of dimension for attentionTransformer.
optNumD(int) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.Builder: Sets the number of dimension except attentionTransformer.
optNumIndependent(int) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.Builder: Sets the number of independent fullyConnected layers.
optNumShared(int) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.Builder: Sets the number of shared fullyConnected layers.
optNumSteps(int) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.Builder: Sets the number of decision steps for tabNet.
optRepeatTimes(int[]) - Method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2.Builder: Sets the repeatTimes(the value n defined in the paper) of each block of MobileNetV2.
optStrides(int[]) - Method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2.Builder: Sets the strides(the value s defined in the paper) of each block of MobileNetV2.
optVirtualBatchSize(int) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.Builder: Sets the virtual batch size for ghost batch norm.
optWidthMultiplier(float) - Method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV1.Builder: Sets the widthMultiplier of MobileNet.

R

REPEATLENGTH - Static variable in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2
residualUnit(int, Shape, boolean, boolean, float) - Static method in class ai.djl.basicmodelzoo.cv.classification.ResNetV1: Builds a Block that represents a residual unit used in the implementation of the Resnet model.
resnet(ResNetV1.Builder) - Static method in class ai.djl.basicmodelzoo.cv.classification.ResNetV1: Creates a new Block of ResNetV1 with the arguments from the given ResNetV1.Builder.
ResnetBlockFactory - Class in ai.djl.basicmodelzoo.cv.classification: A BlockFactory class that creates ResNetV1 block.
ResnetBlockFactory() - Constructor for class ai.djl.basicmodelzoo.cv.classification.ResnetBlockFactory
ResNetV1 - Class in ai.djl.basicmodelzoo.cv.classification: ResNetV1 contains a generic implementation of ResNet adapted from https://github.com/tornadomeet/ResNet/blob/master/symbol_resnet.py (Original author Wei Wu) by Antti-Pekka Hynninen.
ResNetV1.Builder - Class in ai.djl.basicmodelzoo.cv.classification: The Builder to construct a ResNetV1 object.

S

setBaseNetwork(Block) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection.Builder: Sets the base network for the SSD framework.
setConvArch(int[][]) - Method in class ai.djl.basicmodelzoo.cv.classification.VGG.Builder: Sets the number of blocks according to the user.
setDropOutRate(float) - Method in class ai.djl.basicmodelzoo.cv.classification.AlexNet.Builder: Sets the dropout rate in the network.
setDropOutRate(float) - Method in class ai.djl.basicmodelzoo.cv.classification.NiN.Builder: Sets the dropout rate in the network.
setImageShape(Shape) - Method in class ai.djl.basicmodelzoo.cv.classification.ResNetV1.Builder: Sets the shape of the image.
setInputDim(int) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.Builder: Sets the input dimension of TabNet.
setNumChannels(int[]) - Method in class ai.djl.basicmodelzoo.cv.classification.AlexNet.Builder: Sets the number of channels for the AlexNet blocks.
setNumChannels(int[]) - Method in class ai.djl.basicmodelzoo.cv.classification.LeNet.Builder: Sets the number of channels for the LeNet blocks.
setNumChannels(int[]) - Method in class ai.djl.basicmodelzoo.cv.classification.NiN.Builder: Sets the number of channels for the niN blocks.
setNumClasses(int) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection.Builder: Sets the number of classes of objects to be detected.
setNumClasses(int) - Method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3.Builder: Sets the number of classes for yolov3.
setNumFeatures(int) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection.Builder: Sets the number of down sampling blocks to be applied.
setNumLayers(int) - Method in class ai.djl.basicmodelzoo.cv.classification.ResNetV1.Builder: Sets the number of layers in the network.
setNumLayers(int) - Method in class ai.djl.basicmodelzoo.cv.classification.VGG.Builder: Sets the number of layers.
setOutDim(int) - Method in class ai.djl.basicmodelzoo.tabular.TabNet.Builder: Sets the output dimension for TabNet.
setOutSize(long) - Method in class ai.djl.basicmodelzoo.cv.classification.AlexNet.Builder: Sets the size of the output.
setOutSize(long) - Method in class ai.djl.basicmodelzoo.cv.classification.GoogLeNet.Builder: Sets the size of the output.
setOutSize(long) - Method in class ai.djl.basicmodelzoo.cv.classification.LeNet.Builder: Sets the size of the output.
setOutSize(long) - Method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV1.Builder: Sets the size of the output.
setOutSize(long) - Method in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2.Builder: Sets the size of the output.
setOutSize(long) - Method in class ai.djl.basicmodelzoo.cv.classification.ResNetV1.Builder: Sets the size of the output.
setOutSize(long) - Method in class ai.djl.basicmodelzoo.cv.classification.VGG.Builder: Sets the size of the output.
setRatios(List<List<Float>>) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection.Builder: Sets the list of aspect ratios of generated anchor boxes.
setSizes(List<List<Float>>) - Method in class ai.djl.basicmodelzoo.cv.object_detection.ssd.SingleShotDetection.Builder: Sets the list of sizes of generated anchor boxes.
SimpleTextDecoder - Class in ai.djl.basicmodelzoo.nlp: SimpleTextDecoder implements a Decoder that employs a RecurrentBlock to decode text input.
SimpleTextDecoder(TrainableTextEmbedding, RecurrentBlock, long) - Constructor for class ai.djl.basicmodelzoo.nlp.SimpleTextDecoder: Contructs a new instance of SimpleTextDecoder with the given RecurrentBlock.
SimpleTextDecoder(RecurrentBlock, int) - Constructor for class ai.djl.basicmodelzoo.nlp.SimpleTextDecoder: Contructs a new instance of SimpleTextDecoder with the given RecurrentBlock.
SimpleTextEncoder - Class in ai.djl.basicmodelzoo.nlp: SimpleTextEncoder implements a Encoder that employs a RecurrentBlock to encode text input.
SimpleTextEncoder(TrainableTextEmbedding, RecurrentBlock) - Constructor for class ai.djl.basicmodelzoo.nlp.SimpleTextEncoder: Contructs a new instance of SimpleTextEncoder with the given RecurrentBlock and TrainableTextEmbedding.
SimpleTextEncoder(RecurrentBlock) - Constructor for class ai.djl.basicmodelzoo.nlp.SimpleTextEncoder: Contructs a new instance of SimpleTextEncoder with the given RecurrentBlock.
SingleShotDetection - Class in ai.djl.basicmodelzoo.cv.object_detection.ssd: SingleShotDetection is an implementation of Block that implements a Single Shot Detection (SSD) model for object detection.
SingleShotDetection.Builder - Class in ai.djl.basicmodelzoo.cv.object_detection.ssd: The Builder to construct a SingleShotDetection.
squeezenet(int) - Static method in class ai.djl.basicmodelzoo.cv.classification.SqueezeNet: Construct squeezenet v1.1.
SqueezeNet - Class in ai.djl.basicmodelzoo.cv.classification: SqueezeNet contains a generic implementation of Squeezenet adapted from [torchvision implmentation](https://github.com/pytorch/vision/blob/master/torchvision/models/squeezenet.py)
SsdBlockFactory - Class in ai.djl.basicmodelzoo.cv.object_detection.ssd: A BlockFactory class that creates SingleShotDetection block.
SsdBlockFactory() - Constructor for class ai.djl.basicmodelzoo.cv.object_detection.ssd.SsdBlockFactory
STRIDELENGTH - Static variable in class ai.djl.basicmodelzoo.cv.classification.MobileNetV2

T

TabNet - Class in ai.djl.basicmodelzoo.tabular: TabNet contains a generic implementation of TabNet adapted from https://towardsdatascience.com/implementing-tabnet-in-pytorch-fc977c383279 (Original author Samrat Thapa)
TabNet.AttentionTransformer - Class in ai.djl.basicmodelzoo.tabular: AttentionTransformer is where the tabNet models learn the relationship between relevant features, and decides which features to pass on to the feature transformer of the current decision step.
TabNet.Builder - Class in ai.djl.basicmodelzoo.tabular: The Builder to construct a TabNet object.
TabNet.DecisionStep - Class in ai.djl.basicmodelzoo.tabular: DecisionStep is just combining featureTransformer and attentionTransformer together.
tabNetGLU(NDArray, int) - Static method in class ai.djl.basicmodelzoo.tabular.TabNet: Applies tabNetGLU activation(which is mostly used in tabNet) on the input NDArray.
tabNetGLU(NDList, int) - Static method in class ai.djl.basicmodelzoo.tabular.TabNet: Applies tabNetGLU activation(which is mostly used in tabNet) on the input singleton NDList.
tabNetGLUBlock(int) - Static method in class ai.djl.basicmodelzoo.tabular.TabNet: Creates a LambdaBlock that applies the TabNet.tabNetGLU(NDArray, int) activation function in its forward function.

U

upSampleBlockNearest() - Static method in class ai.djl.basicmodelzoo.cv.object_detection.yolo.YOLOV3: Builds a Block that represents an upSampleLayer(the nearest mode) for yolov3.

V

vgg(VGG.Builder) - Static method in class ai.djl.basicmodelzoo.cv.classification.VGG: Creates a VGG block with the help of the VGG Builder.
VGG - Class in ai.djl.basicmodelzoo.cv.classification: VGG model from the "Very Deep Convolutional Networks for Large-Scale Image Recognition" https://arxiv.org/abs/1409.1556 paper.
VGG.Builder - Class in ai.djl.basicmodelzoo.cv.classification: The Builder to construct a VGG object.
vggBlock(int, int) - Method in class ai.djl.basicmodelzoo.cv.classification.VGG: Creates a constituent VGG block that becomes a part of the whole VGG model.

Y

YOLOV3 - Class in ai.djl.basicmodelzoo.cv.object_detection.yolo: YOLOV3 contains a generic implementation of yolov3 (Original author bubbliiiing).
YOLOV3.Builder - Class in ai.djl.basicmodelzoo.cv.object_detection.yolo: The Builder to construct a YOLOV3 object.

A B C D F G I L M N O R S T U V Y
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form