Index (Deep Java Library 0.17.0 API specification)

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
All Classes All Packages

A

abs() - Method in interface ai.djl.ndarray.NDArray: Returns the absolute value of this NDArray element-wise.
abs() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the absolute value of this NDArray element-wise.
AbstractAccuracy - Class in ai.djl.training.evaluator: Accuracy is an Evaluator that computes the accuracy score.
AbstractAccuracy(String) - Constructor for class ai.djl.training.evaluator.AbstractAccuracy: Creates an accuracy evaluator that computes accuracy across axis 1.
AbstractAccuracy(String, int) - Constructor for class ai.djl.training.evaluator.AbstractAccuracy: Creates an accuracy evaluator.
AbstractBaseBlock - Class in ai.djl.nn: This provides shared functionality for both the DJL-based AbstractBlocks and the imported AbstractSymbolBlocks.
AbstractBaseBlock() - Constructor for class ai.djl.nn.AbstractBaseBlock: Constructs a new AbstractBaseBlock instance.
AbstractBaseBlock(byte) - Constructor for class ai.djl.nn.AbstractBaseBlock: Builds an empty block with the given version for parameter serialization.
AbstractBlock - Class in ai.djl.nn: AbstractBlock is an abstract implementation of Block.
AbstractBlock() - Constructor for class ai.djl.nn.AbstractBlock: Constructs a new AbstractBlock instance.
AbstractBlock(byte) - Constructor for class ai.djl.nn.AbstractBlock: Builds an empty block with the given version for parameter serialization.
AbstractCompositeLoss - Class in ai.djl.training.loss: AbstractCompositeLoss is a Loss class that can combine other Losses together to make a larger loss.
AbstractCompositeLoss(String) - Constructor for class ai.djl.training.loss.AbstractCompositeLoss: Constructs a composite loss with the given name.
AbstractEmbedding<T> - Interface in ai.djl.nn.core: An Embedding maps elements of type T to a 1-Dimensional representative NDArrays.
AbstractIndexedEmbedding<T> - Interface in ai.djl.nn.core: An AbstractEmbedding where each embedded item can be assigned an integer index.
AbstractRepository - Class in ai.djl.repository: The AbstractRepository is the shared base for implementers of the Repository interface.
AbstractRepository(String, URI) - Constructor for class ai.djl.repository.AbstractRepository
AbstractSymbolBlock - Class in ai.djl.nn: AbstractSymbolBlock is an abstract implementation of SymbolBlock.
AbstractSymbolBlock() - Constructor for class ai.djl.nn.AbstractSymbolBlock: Constructs a new AbstractSymbolBlock instance.
AbstractSymbolBlock(byte) - Constructor for class ai.djl.nn.AbstractSymbolBlock: Builds an empty block with the given version for parameter serialization.
accuracy(NDList, NDList) - Method in class ai.djl.nn.transformer.BertMaskedLanguageModelLoss: Calculates the percentage of correctly predicted masked tokens.
accuracy(NDList, NDList) - Method in class ai.djl.nn.transformer.BertNextSentenceLoss: Calculates the fraction of correct predictions.
Accuracy - Class in ai.djl.training.evaluator: Accuracy is the AbstractAccuracy with multiple classes.
Accuracy() - Constructor for class ai.djl.training.evaluator.Accuracy: Creates a multiclass accuracy evaluator that computes accuracy across axis 1 along the 0th index.
Accuracy(String) - Constructor for class ai.djl.training.evaluator.Accuracy: Creates a multiclass accuracy evaluator that computes accuracy across axis 1 along the 0th index.
Accuracy(String, int) - Constructor for class ai.djl.training.evaluator.Accuracy: Creates a multiclass accuracy evaluator.
accuracyHelper(NDList, NDList) - Method in class ai.djl.training.evaluator.AbstractAccuracy: A helper for classes extending AbstractAccuracy.
accuracyHelper(NDList, NDList) - Method in class ai.djl.training.evaluator.Accuracy: A helper for classes extending AbstractAccuracy.
accuracyHelper(NDList, NDList) - Method in class ai.djl.training.evaluator.BinaryAccuracy: A helper for classes extending AbstractAccuracy.
accuracyHelper(NDList, NDList) - Method in class ai.djl.training.evaluator.SingleShotDetectionAccuracy: A helper for classes extending AbstractAccuracy.
accuracyHelper(NDList, NDList) - Method in class ai.djl.training.evaluator.TopKAccuracy: A helper for classes extending AbstractAccuracy.
acos() - Method in interface ai.djl.ndarray.NDArray: Returns the inverse trigonometric cosine of this NDArray element-wise.
acos() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the inverse trigonometric cosine of this NDArray element-wise.
acosh() - Method in interface ai.djl.ndarray.NDArray: Returns the inverse hyperbolic cosine of this NDArray element-wise.
acosh() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the inverse hyperbolic cosine of this NDArray element-wise.
ACTION_RECOGNITION - Static variable in interface ai.djl.Application.CV: An application that accepts an image or video and classifies the action being done in it.
ActionSpace - Class in ai.djl.modality.rl: Contains the available actions that can be taken in an RlEnv.
ActionSpace() - Constructor for class ai.djl.modality.rl.ActionSpace
activation - Variable in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder
Activation - Class in ai.djl.nn: Utility class that provides activation functions and blocks.
adadelta() - Static method in class ai.djl.training.optimizer.Optimizer: Returns a new instance of Adadelta.Builder that can build an Adadelta optimizer.
Adadelta - Class in ai.djl.training.optimizer: Adadelta is an Adadelta Optimizer.
Adadelta(Adadelta.Builder) - Constructor for class ai.djl.training.optimizer.Adadelta: Creates a new instance of Adadelta.
Adadelta.Builder - Class in ai.djl.training.optimizer: The Builder to construct an Adadelta object.
adagrad() - Static method in class ai.djl.training.optimizer.Optimizer: Returns a new instance of Adagrad.Builder that can build an Adagrad optimizer.
Adagrad - Class in ai.djl.training.optimizer: Adagrad is an AdaGrad Optimizer.
Adagrad(Adagrad.Builder) - Constructor for class ai.djl.training.optimizer.Adagrad: Creates a new instance of Adam optimizer.
Adagrad.Builder - Class in ai.djl.training.optimizer: The Builder to construct an Adagrad object.
adam() - Static method in class ai.djl.training.optimizer.Optimizer: Returns a new instance of Adam.Builder that can build an Adam optimizer.
Adam - Class in ai.djl.training.optimizer: Adam is a generalization of the AdaGrad Optimizer.
Adam(Adam.Builder) - Constructor for class ai.djl.training.optimizer.Adam: Creates a new instance of Adam optimizer.
Adam.Builder - Class in ai.djl.training.optimizer: The Builder to construct an Adam object.
add(byte[]) - Method in class ai.djl.modality.Input: Appends an item at the end of the input.
add(int, Transform) - Method in class ai.djl.translate.Pipeline: Adds the given Transform to the list of transforms to be applied on the NDArray at the given index in the input NDList.
add(int, String, BytesSupplier) - Method in class ai.djl.modality.Input: Inserts the specified element at the specified position in the input.
add(long...) - Method in class ai.djl.ndarray.types.Shape: Joins this shape with axes.
add(BytesSupplier) - Method in class ai.djl.modality.Input: Appends an item at the end of the input.
add(NDArray) - Method in interface ai.djl.ndarray.NDArray: Adds other NDArrays to this NDArray element-wise.
add(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Adds other NDArrays to this NDArray element-wise.
add(NDArray...) - Static method in class ai.djl.ndarray.NDArrays: Adds a NDArray to a NDArray element-wise.
add(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Adds a number to the NDArray element-wise.
add(Block) - Method in class ai.djl.nn.ParallelBlock: Adds the given Block to the block, which is one parallel branch.
add(Block) - Method in class ai.djl.nn.SequentialBlock: Adds the given Block to the block to be executed in order.
add(Hyperparameter<?>) - Method in class ai.djl.training.hyperparameter.param.HpSet: Adds a hyperparameter to the set.
add(Transform) - Method in class ai.djl.translate.Pipeline: Adds the given Transform to the list of transforms to be applied on the input when the transform method is called on this object.
add(Number) - Method in interface ai.djl.ndarray.NDArray: Adds a number to this NDArray element-wise.
add(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Adds a number to this NDArray element-wise.
add(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Adds a NDArray to a number element-wise.
add(String) - Method in class ai.djl.modality.Input: Appends an item at the end of the input.
add(String, byte[]) - Method in class ai.djl.modality.Input: Adds a key/value pair to the input content.
add(String, BytesSupplier) - Method in class ai.djl.modality.Input: Adds a key/value pair to the input content.
add(String, Transform) - Method in class ai.djl.translate.Pipeline: Adds the given Transform to the list of transforms to be applied on the NDArray with the given key as name in the input NDList.
add(String, String) - Method in class ai.djl.modality.Input: Adds a key/value pair to the input content.
add(Function<NDList, NDList>) - Method in class ai.djl.nn.ParallelBlock: Adds a LambdaBlock, that applies the given function, to the list of parallel branches.
add(Function<NDList, NDList>) - Method in class ai.djl.nn.SequentialBlock: Adds a LambdaBlock that applies the given function to the sequence of blocks.
add(List<String>) - Method in class ai.djl.modality.nlp.DefaultVocabulary.Builder: Adds the given sentence to the DefaultVocabulary.
addAccumulator(String) - Method in class ai.djl.training.evaluator.AbstractAccuracy: Adds an accumulator for the results of the evaluation with the given key.
addAccumulator(String) - Method in class ai.djl.training.evaluator.BoundingBoxError: Adds an accumulator for the results of the evaluation with the given key.
addAccumulator(String) - Method in class ai.djl.training.evaluator.Evaluator: Adds an accumulator for the results of the evaluation with the given key.
addAccumulator(String) - Method in class ai.djl.training.evaluator.IndexEvaluator: Adds an accumulator for the results of the evaluation with the given key.
addAccumulator(String) - Method in class ai.djl.training.loss.AbstractCompositeLoss: Adds an accumulator for the results of the evaluation with the given key.
addAccumulator(String) - Method in class ai.djl.training.loss.Loss: Adds an accumulator for the results of the evaluation with the given key.
addAll(NDList) - Method in class ai.djl.ndarray.NDList: Appends all of the NDArrays in the specified NDList to the end of this NDList, in the order that they are returned by the specified NDList's iterator.
addAll(Shape) - Method in class ai.djl.ndarray.types.Shape: Joins this shape with specified other shape.
addAll(Block...) - Method in class ai.djl.nn.ParallelBlock: Adds an array of blocks, each of which is a parallel branch.
addAll(Block...) - Method in class ai.djl.nn.SequentialBlock: Adds an array of blocks to be executed in sequence, in order.
addAll(Collection<Block>) - Method in class ai.djl.nn.ParallelBlock: Adds a Collection of blocks, each of which is a parallel branch.
addAll(Collection<Block>) - Method in class ai.djl.nn.SequentialBlock: Adds a Collection of blocks to be executed in sequence, in order.
addAll(List<List<String>>) - Method in class ai.djl.modality.nlp.DefaultVocabulary.Builder: Adds the given list of sentences to the DefaultVocabulary.
addAllDim() - Method in class ai.djl.ndarray.index.NDIndex: Appends a new index to get all values in the dimension.
addAllDim(int) - Method in class ai.djl.ndarray.index.NDIndex: Appends multiple new index to get all values in the dimension.
addArtifact(Artifact) - Method in class ai.djl.repository.Metadata: Adds one artifact for the metadata.
addBooleanIndex(NDArray) - Method in class ai.djl.ndarray.index.NDIndex: Updates the NDIndex by appending a boolean NDArray.
addChildBlock(String, B) - Method in class ai.djl.nn.AbstractBlock: Use this to add a child block to this block.
addEvaluator(Evaluator) - Method in class ai.djl.training.DefaultTrainingConfig: Adds an Evaluator that needs to be computed during training.
addEvaluators(Collection<T>) - Method in class ai.djl.training.DefaultTrainingConfig: Adds multiple Evaluators that needs to be computed during training.
addFromCustomizedFile(URL, Function<URL, List<String>>) - Method in class ai.djl.modality.nlp.DefaultVocabulary.Builder: Adds a customized vocabulary to the DefaultVocabulary.
addFromTextFile(URL) - Method in class ai.djl.modality.nlp.DefaultVocabulary.Builder: Adds a text vocabulary to the DefaultVocabulary.
addFromTextFile(Path) - Method in class ai.djl.modality.nlp.DefaultVocabulary.Builder: Adds a text vocabulary to the DefaultVocabulary.
addi(NDArray) - Method in interface ai.djl.ndarray.NDArray: Adds other NDArrays to this NDArray element-wise in place.
addi(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Adds other NDArrays to this NDArray element-wise in place.
addi(NDArray...) - Static method in class ai.djl.ndarray.NDArrays: Adds all of the NDArrays together element-wise in place.
addi(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Adds a number to the NDArray element-wise in place.
addi(Number) - Method in interface ai.djl.ndarray.NDArray: Adds a number to this NDArray element-wise in place.
addi(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Adds a number to this NDArray element-wise in place.
addi(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Adds a NDArray to a number element-wise in place.
addIndices(long...) - Method in class ai.djl.ndarray.index.NDIndex: Updates the NDIndex by appending indices as specified values on the NDArray.
addIndices(String, Object...) - Method in class ai.djl.ndarray.index.NDIndex: Updates the NDIndex by appending indices to the array.
addLicense(License) - Method in class ai.djl.repository.Metadata: Adds one License.
addLoss(Loss) - Method in class ai.djl.training.loss.SimpleCompositeLoss: Adds a Loss that applies to all labels and predictions to this composite loss.
addMetric(Metric) - Method in class ai.djl.metric.Metrics: Adds a Metric to the collection.
addMetric(String, long) - Method in class ai.djl.training.Trainer: Helper to add a metric for a time difference.
addMetric(String, Number) - Method in class ai.djl.metric.Metrics: Adds a Metric given the metric's name and value.
addMetric(String, Number, Unit) - Method in class ai.djl.metric.Metrics: Adds a Metric given the metric's name, value, and unit.
addPad(int, int, NDArraySupplier) - Method in class ai.djl.translate.PaddingStackBatchifier.Builder: Adds a new dimension to be padded in the input NDList.
addPad(int, int, NDArraySupplier, int) - Method in class ai.djl.translate.PaddingStackBatchifier.Builder: Adds a new dimension to be padded in the input NDList.
addParameter(P) - Method in class ai.djl.nn.AbstractBlock: Adds a parameter to this block.
addPickDim(NDArray) - Method in class ai.djl.ndarray.index.NDIndex: Appends a picking index that gets values by index in the axis.
addProperty(String, String) - Method in class ai.djl.modality.Input: Adds a property to the input.
addResource(MRL) - Method in class ai.djl.repository.AbstractRepository: Adds resource to the repository.
addResource(MRL) - Method in class ai.djl.repository.RemoteRepository: Adds resource to the repository.
addResource(MRL) - Method in interface ai.djl.repository.Repository: Adds resource to the repository.
addSingleton(Function<NDArray, NDArray>) - Method in class ai.djl.nn.SequentialBlock: Adds a LambdaBlock.singleton(Function) that applies the given function to the sequence of blocks.
addSliceDim(long, long) - Method in class ai.djl.ndarray.index.NDIndex: Appends a new index to slice the dimension and returns a range of values.
addSliceDim(long, long, long) - Method in class ai.djl.ndarray.index.NDIndex: Appends a new index to slice the dimension and returns a range of values.
addStep(RlEnv.Step) - Method in class ai.djl.modality.rl.LruReplayBuffer: Adds a new step to the buffer.
addStep(RlEnv.Step) - Method in interface ai.djl.modality.rl.ReplayBuffer: Adds a new step to the buffer.
addTargetTransform(Transform) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Adds the Transform to the target Pipeline to be applied on the labels.
addTrainingListeners(TrainingListener...) - Method in class ai.djl.training.DefaultTrainingConfig: Adds TrainingListeners for training.
addTransform(Transform) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder: Adds the Transform to the Pipeline use for pre-processing the image.
addTransform(Transform) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Adds the Transform to the Pipeline to be applied on the data.
ai.djl - package ai.djl: Contains top level, engine-agnostic classes for both inference and training.
ai.djl.engine - package ai.djl.engine: Contains classes responsible for loading a deep learning engine.
ai.djl.inference - package ai.djl.inference: Contains classes to implement inference tasks.
ai.djl.metric - package ai.djl.metric: Contains classes to collect metrics information.
ai.djl.modality - package ai.djl.modality: Contains utility classes for each of the predefined modalities.
ai.djl.modality.cv - package ai.djl.modality.cv: Contains utility classes for computer vision tasks and image processing.
ai.djl.modality.cv.output - package ai.djl.modality.cv.output: Contains output types used in various computer vision applications.
ai.djl.modality.cv.transform - package ai.djl.modality.cv.transform: Contains Transforms for working with Images.
ai.djl.modality.cv.translator - package ai.djl.modality.cv.translator: Contains translators used for computer vision applications.
ai.djl.modality.cv.translator.wrapper - package ai.djl.modality.cv.translator.wrapper: Contains wrappers to for multiple input formats to a BaseImageTranslator.
ai.djl.modality.cv.util - package ai.djl.modality.cv.util: Contains utility classes for image manipulation.
ai.djl.modality.nlp - package ai.djl.modality.nlp: Contains utility classes for natural language processing tasks.
ai.djl.modality.nlp.bert - package ai.djl.modality.nlp.bert: Contains classes that deal with BERT for natural language pre-processing tasks.
ai.djl.modality.nlp.embedding - package ai.djl.modality.nlp.embedding: Contains classes that deal with word embeddings for natural language pre-processing tasks.
ai.djl.modality.nlp.preprocess - package ai.djl.modality.nlp.preprocess: Contains utility classes for natural language pre-processing tasks.
ai.djl.modality.nlp.qa - package ai.djl.modality.nlp.qa: Contains utility classes for question and answer processing.
ai.djl.modality.nlp.translator - package ai.djl.modality.nlp.translator: Contains utility classes for each of the predefined translator.
ai.djl.modality.rl - package ai.djl.modality.rl: Contains utility classes for reinforcement learning.
ai.djl.modality.rl.agent - package ai.djl.modality.rl.agent: Contains agents to learn using reinforcement learning.
ai.djl.modality.rl.env - package ai.djl.modality.rl.env: Contains environments to train reinforcement learning in.
ai.djl.ndarray - package ai.djl.ndarray: Contains classes and interfaces that define an n-dimensional array.
ai.djl.ndarray.index - package ai.djl.ndarray.index: Contains classes that help access NDArray's indices.
ai.djl.ndarray.index.dim - package ai.djl.ndarray.index.dim: Contains classes that represent an index element in a NDArray's indices.
ai.djl.ndarray.index.full - package ai.djl.ndarray.index.full: Contains classes that represent simplified representations of an NDArray's indices.
ai.djl.ndarray.types - package ai.djl.ndarray.types: Contains classes that define n-dimensional array data types.
ai.djl.nn - package ai.djl.nn: Contains classes to construct neural networks.
ai.djl.nn.convolutional - package ai.djl.nn.convolutional: Contains classes that define convolutional operations extending Convolution and Deconvolution.
ai.djl.nn.core - package ai.djl.nn.core: Contains classes that define simple neural network operations.
ai.djl.nn.norm - package ai.djl.nn.norm: Contains classes that define normalizing neural network operations.
ai.djl.nn.pooling - package ai.djl.nn.pooling: Contains pooling neural network operations in Pool and helpers for it.
ai.djl.nn.recurrent - package ai.djl.nn.recurrent: Contains classes for recurrent neural network operations.
ai.djl.nn.transformer - package ai.djl.nn.transformer: Contains blocks for transformer models.
ai.djl.repository - package ai.djl.repository: Contains a Maven-based Repository format for creating repositories of artifacts such as datasets and model zoos.
ai.djl.repository.zoo - package ai.djl.repository.zoo: Contains classes for working with model zoo repositories.
ai.djl.training - package ai.djl.training: Contains classes and implementations to train a neural network.
ai.djl.training.dataset - package ai.djl.training.dataset: Contains classes to download and prepare training and testing data.
ai.djl.training.evaluator - package ai.djl.training.evaluator: Contains classes for evaluating the effectiveness of models.
ai.djl.training.hyperparameter - package ai.djl.training.hyperparameter: Contains utilities to train, describe, and manipulate Hyperparameters.
ai.djl.training.hyperparameter.optimizer - package ai.djl.training.hyperparameter.optimizer: Contains classes to optimize Hyperparameters.
ai.djl.training.hyperparameter.param - package ai.djl.training.hyperparameter.param: Contains different types of Hyperparameters.
ai.djl.training.initializer - package ai.djl.training.initializer: Contains classes for initializing a Block's Parameters.
ai.djl.training.listener - package ai.djl.training.listener: Contains classes providing functionality during training through TrainingListener.
ai.djl.training.loss - package ai.djl.training.loss: Contains classes for measuring the Loss of a model.
ai.djl.training.optimizer - package ai.djl.training.optimizer: Contains classes for optimizing a neural network Block.
ai.djl.training.tracker - package ai.djl.training.tracker: Contains classes for having a gradually changing hyper-parameter.
ai.djl.training.util - package ai.djl.training.util: Contains utilities to use during training.
ai.djl.translate - package ai.djl.translate: Contains classes and interfaces that translate between java objects and NDArrays.
all() - Method in interface ai.djl.ndarray.NDArray: Returns true if all elements within this NDArray are non-zero or true.
allClose(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns true if two NDArrays are element-wise equal within a tolerance.
allClose(NDArray, double, double, boolean) - Method in interface ai.djl.ndarray.NDArray: Returns true if two NDArray are element-wise equal within a tolerance.
allClose(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns true if two NDArray are element-wise equal within a tolerance.
allClose(NDArray, NDArray, double, double, boolean) - Static method in class ai.djl.ndarray.NDArrays: Returns true if two NDArray are element-wise equal within a tolerance.
allocateDirect(int) - Method in interface ai.djl.ndarray.NDManager: Allocates a new engine specific direct byte buffer.
alternativeManager - Variable in class ai.djl.ndarray.BaseNDManager
alternativeManager - Variable in class ai.djl.ndarray.NDArrayAdapter
any() - Method in interface ai.djl.ndarray.NDArray: Returns true if any of the elements within this NDArray are non-zero or true.
ANY - Static variable in interface ai.djl.Application.CV: Any computer vision application, including those in Application.CV.
ANY - Static variable in interface ai.djl.Application.NLP: Any NLP application, including those in Application.NLP.
ANY - Static variable in interface ai.djl.Application.Tabular: Any tabular application, including those in Application.Tabular.
apache() - Static method in class ai.djl.repository.License: The default Apache License.
Application - Class in ai.djl: A class contains common tasks that can be completed using deep learning.
Application.CV - Interface in ai.djl: The common set of applications for computer vision (image and video data).
Application.NLP - Interface in ai.djl: The common set of applications for natural language processing (text data).
Application.Tabular - Interface in ai.djl: The common set of applications for tabular data.
arange(float) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced values starting from 0.
arange(float, float) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced values within a given interval with step 1.
arange(float, float, float) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced values within a given interval.
arange(float, float, float, DataType) - Method in class ai.djl.ndarray.BaseNDManager: Returns evenly spaced values within a given interval.
arange(float, float, float, DataType) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced values within a given interval.
arange(float, float, float, DataType, Device) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced values within a given interval.
arange(int) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced values starting from 0.
arange(int, int) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced values within a given interval with step 1.
arange(int, int, int) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced values within a given interval.
arange(int, int, int, DataType) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced values within a given interval.
AREA - ai.djl.modality.cv.Image.Interpolation
argMax() - Method in interface ai.djl.ndarray.NDArray: Returns the indices of the maximum values into the flattened NDArray.
argMax() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the indices of the maximum values into the flattened NDArray.
argMax(int) - Method in interface ai.djl.ndarray.NDArray: Returns the indices of the maximum values along given axis.
argMax(int) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the indices of the maximum values along given axis.
argMin() - Method in interface ai.djl.ndarray.NDArray: Returns the indices of the minimum values into the flattened NDArray.
argMin() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the indices of the minimum values into the flattened NDArray.
argMin(int) - Method in interface ai.djl.ndarray.NDArray: Returns the indices of the minimum values along given axis.
argMin(int) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the indices of the minimum values along given axis.
argSort() - Method in interface ai.djl.ndarray.NDArray: Returns the indices that would sort this NDArray.
argSort(int) - Method in interface ai.djl.ndarray.NDArray: Returns the indices that would sort this NDArray given the axis.
argSort(int, boolean) - Method in interface ai.djl.ndarray.NDArray: Returns the indices that would sort this NDArray given the axis.
argSort(int, boolean) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the indices that would sort this NDArray given the axis.
arguments - Variable in class ai.djl.repository.AbstractRepository
ArgumentsUtil - Class in ai.djl.translate: A utility class to extract data from model's arguments.
ArrayDataset - Class in ai.djl.training.dataset: ArrayDataset is an implementation of RandomAccessDataset that consist entirely of large NDArrays.
ArrayDataset(RandomAccessDataset.BaseBuilder<?>) - Constructor for class ai.djl.training.dataset.ArrayDataset: Creates a new instance of ArrayDataset with the arguments in ArrayDataset.Builder.
ArrayDataset.Builder - Class in ai.djl.training.dataset: The Builder to construct an ArrayDataset.
Artifact - Class in ai.djl.repository: An Artifact is a set of data files such as a model or dataset.
Artifact() - Constructor for class ai.djl.repository.Artifact
Artifact.Item - Class in ai.djl.repository: A file (possibly compressed) within an Artifact.
Artifact.VersionComparator - Class in ai.djl.repository: A Comparator to compare artifacts based on their version numbers.
artifactId - Variable in class ai.djl.repository.Metadata
artifacts - Variable in class ai.djl.BaseModel
artifacts - Variable in class ai.djl.repository.Metadata
asDataType(ByteBuffer) - Method in enum ai.djl.ndarray.types.DataType: Converts a ByteBuffer to a buffer for this data type.
asin() - Method in interface ai.djl.ndarray.NDArray: Returns the inverse trigonometric sine of this NDArray element-wise.
asin() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the inverse trigonometric sine of this NDArray element-wise.
asinh() - Method in interface ai.djl.ndarray.NDArray: Returns the inverse hyperbolic sine of this NDArray element-wise.
asinh() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the inverse hyperbolic sine of this NDArray element-wise.
asNumpy() - Method in enum ai.djl.ndarray.types.DataType: Returns a numpy string value.
atan() - Method in interface ai.djl.ndarray.NDArray: Returns the inverse trigonometric tangent of this NDArray element-wise.
atan() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the inverse trigonometric tangent of this NDArray element-wise.
atanh() - Method in interface ai.djl.ndarray.NDArray: Returns the inverse hyperbolic tangent of this NDArray element-wise.
atanh() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the inverse hyperbolic tangent of this NDArray element-wise.
attach(NDManager) - Method in class ai.djl.ndarray.NDArrayAdapter: Attaches this NDResource to the specified NDManager.
attach(NDManager) - Method in class ai.djl.ndarray.NDList: Attaches this NDResource to the specified NDManager.
attach(NDManager) - Method in interface ai.djl.ndarray.NDResource: Attaches this NDResource to the specified NDManager.
attachAll(NDResource...) - Method in interface ai.djl.ndarray.NDManager: Attaches all resources to this manager.
attachInternal(String, AutoCloseable) - Method in class ai.djl.ndarray.BaseNDManager: Attaches a resource to this NDManager.
attachInternal(String, AutoCloseable) - Method in interface ai.djl.ndarray.NDManager: Attaches a resource to this NDManager.
AUTO - ai.djl.modality.cv.translator.YoloV5Translator.YoloOutputType
availableSize() - Method in class ai.djl.training.dataset.ArrayDataset: Returns the number of records available to be read in this Dataset.
availableSize() - Method in class ai.djl.training.dataset.RandomAccessDataset: Returns the number of records available to be read in this Dataset.
AVG - ai.djl.training.initializer.XavierInitializer.FactorType
avgPool1d(NDArray, Shape, Shape, Shape, boolean, boolean) - Static method in class ai.djl.nn.pooling.Pool: Performs 1-D Avg Pooling on the input.
avgPool1dBlock(Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool1dBlock pooling function in its forward function.
avgPool1dBlock(Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool1dBlock pooling function in its forward function.
avgPool1dBlock(Shape, Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool1dBlock pooling function in its forward function.
avgPool1dBlock(Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool1dBlock pooling function in its forward function.
avgPool1dBlock(Shape, Shape, Shape, boolean, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool1dBlock pooling function in its forward function.
avgPool2d(NDArray, Shape, Shape, Shape, boolean, boolean) - Static method in class ai.djl.nn.pooling.Pool: Performs 2-D Avg Pooling on the input.
avgPool2dBlock(Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool2dBlock pooling function in its forward function.
avgPool2dBlock(Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool2dBlock pooling function in its forward function.
avgPool2dBlock(Shape, Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool2dBlock pooling function in its forward function.
avgPool2dBlock(Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool2dBlock pooling function in its forward function.
avgPool2dBlock(Shape, Shape, Shape, boolean, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool2dBlock pooling function in its forward function.
avgPool3d(NDArray, Shape, Shape, Shape, boolean, boolean) - Static method in class ai.djl.nn.pooling.Pool: Performs 3-D Avg Pooling on the input.
avgPool3dBlock(Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool3dBlock pooling function in its forward function.
avgPool3dBlock(Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool3dBlock pooling function in its forward function.
avgPool3dBlock(Shape, Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool3dBlock pooling function in its forward function.
avgPool3dBlock(Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool3dBlock pooling function in its forward function.
avgPool3dBlock(Shape, Shape, Shape, boolean, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the avgPool3dBlock pooling function in its forward function.
axis - Variable in class ai.djl.training.evaluator.AbstractAccuracy
axis(int...) - Method in class ai.djl.nn.norm.LayerNorm.Builder: List the axis over which the mean and variance will be calculated (alternative to normalizedShape).

B

backward(NDArray) - Method in interface ai.djl.training.GradientCollector: Calculate the gradient w.r.t previously marked variable (head).
base() - Method in class ai.djl.nn.transformer.BertBlock.Builder: Sets this builder's params to the BASE config of the original BERT paper.
BaseBuilder() - Constructor for class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder
BaseBuilder() - Constructor for class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder
BaseBuilder() - Constructor for class ai.djl.nn.core.Embedding.BaseBuilder
BaseBuilder() - Constructor for class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder
BaseBuilder() - Constructor for class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder
BaseHpOptimizer - Class in ai.djl.training.hyperparameter.optimizer: A base containing shared implementations for HpOptimizers.
BaseHpOptimizer(HpSet) - Constructor for class ai.djl.training.hyperparameter.optimizer.BaseHpOptimizer: Constructs a BaseHpOptimizer.
BaseImageTranslator<T> - Class in ai.djl.modality.cv.translator: Built-in Translator that provides default image pre-processing.
BaseImageTranslator(BaseImageTranslator.BaseBuilder<?>) - Constructor for class ai.djl.modality.cv.translator.BaseImageTranslator: Constructs an ImageTranslator with the provided builder.
BaseImageTranslator.BaseBuilder<T extends BaseImageTranslator.BaseBuilder> - Class in ai.djl.modality.cv.translator: A builder to extend for all classes extending the BaseImageTranslator.
BaseImageTranslator.ClassificationBuilder<T extends BaseImageTranslator.BaseBuilder> - Class in ai.djl.modality.cv.translator: A Builder to construct a ImageClassificationTranslator.
BaseImageTranslator.SynsetLoader - Class in ai.djl.modality.cv.translator
BaseModel - Class in ai.djl: BaseModel is the basic implementation of Model.
BaseModel(String) - Constructor for class ai.djl.BaseModel
BaseModelLoader - Class in ai.djl.repository.zoo: Shared code for the ModelLoader implementations.
BaseModelLoader(MRL) - Constructor for class ai.djl.repository.zoo.BaseModelLoader: Constructs a ModelLoader given the repository, mrl, and version.
BaseNDManager - Class in ai.djl.ndarray: BaseNDManager is the default implementation of NDManager.
BaseNDManager(NDManager, Device) - Constructor for class ai.djl.ndarray.BaseNDManager
BaseNDManager.TempResource - Class in ai.djl.ndarray
basic() - Static method in interface ai.djl.training.listener.TrainingListener.Defaults: A basic TrainingListener set with minimal recommended functionality.
Batch - Class in ai.djl.training.dataset: A Batch is used to hold multiple items (data and label pairs) from a Dataset.
Batch(NDManager, NDList, NDList, int, Batchifier, Batchifier, long, long) - Constructor for class ai.djl.training.dataset.Batch: Creates a new instance of Batch with the given manager, data and labels.
BATCH - ai.djl.ndarray.types.LayoutType
BatchData(Batch, Map<Device, NDList>, Map<Device, NDList>) - Constructor for class ai.djl.training.listener.TrainingListener.BatchData: Constructs a new TrainingListener.BatchData.
batchDot(NDArray) - Method in interface ai.djl.ndarray.NDArray: Batchwise product of this NDArray and the other NDArray.
batchDot(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Batchwise product of this NDArray and the other NDArray.
batchFirst - Variable in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder
batchFirst - Variable in class ai.djl.nn.recurrent.RecurrentBlock
batchFlatten(NDArray) - Static method in class ai.djl.nn.Blocks: Inflates the NDArray provided as input to a 2-D NDArray of shape (batch, size).
batchFlatten(NDArray, long) - Static method in class ai.djl.nn.Blocks: Inflates the NDArray provided as input to a 2-D NDArray of shape (batch, size).
batchFlattenBlock() - Static method in class ai.djl.nn.Blocks: Creates a Block whose forward function applies the batchFlatten method.
batchFlattenBlock(long) - Static method in class ai.djl.nn.Blocks: Creates a Block whose forward function applies the batchFlatten method.
batchifier - Variable in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder
batchifier - Variable in class ai.djl.modality.nlp.translator.QATranslator
Batchifier - Interface in ai.djl.translate: An interface that provides methods to convert an un-batched NDList into a batched NDList and vice versa.
batchify(NDList[]) - Method in interface ai.djl.translate.Batchifier: Converts an array of NDList into an NDList.
batchify(NDList[]) - Method in class ai.djl.translate.PaddingStackBatchifier: Converts an array of NDList into an NDList.
batchify(NDList[]) - Method in class ai.djl.translate.StackBatchifier: Converts an array of NDList into an NDList.
batchNorm(NDArray, NDArray, NDArray) - Static method in class ai.djl.nn.norm.BatchNorm: Applies Batch Normalization for each channel across a batch of data.
batchNorm(NDArray, NDArray, NDArray, NDArray, NDArray) - Static method in class ai.djl.nn.norm.BatchNorm: Applies Batch Normalization for each channel across a batch of data.
batchNorm(NDArray, NDArray, NDArray, NDArray, NDArray, int) - Static method in class ai.djl.nn.norm.BatchNorm: Applies Batch Normalization for each channel across a batch of data.
batchNorm(NDArray, NDArray, NDArray, NDArray, NDArray, int, float, float, boolean) - Static method in class ai.djl.nn.norm.BatchNorm: Applies Batch Normalization for each channel across a batch of data.
BatchNorm - Class in ai.djl.nn.norm: In batch training (training with more than one samples per iteration), a batch normalization layer works by normalizing the values of input data to have mean of 0 and variance of 1.
BatchNorm.Builder - Class in ai.djl.nn.norm: The Builder to construct a BatchNorm.
batchPredict(List<I>) - Method in class ai.djl.inference.Predictor: Predicts a batch for inference.
BatchSampler - Class in ai.djl.training.dataset: BatchSampler is a Sampler that returns a single epoch over the data.
BatchSampler(Sampler.SubSampler, int) - Constructor for class ai.djl.training.dataset.BatchSampler: Creates a new instance of BatchSampler that samples from the given Sampler.SubSampler, and yields a mini-batch of indices.
BatchSampler(Sampler.SubSampler, int, boolean) - Constructor for class ai.djl.training.dataset.BatchSampler: Creates a new instance of BatchSampler that samples from the given Sampler.SubSampler, and yields a mini-batch of indices.
beforeInitialize(Shape...) - Method in class ai.djl.nn.AbstractBaseBlock: Performs any action necessary before initialization.
beforeInitialize(Shape...) - Method in class ai.djl.nn.convolutional.Convolution: Performs any action necessary before initialization.
beforeInitialize(Shape...) - Method in class ai.djl.nn.convolutional.Deconvolution: Performs any action necessary before initialization.
beforeInitialize(Shape...) - Method in class ai.djl.nn.core.Linear: Performs any action necessary before initialization.
beforeInitialize(Shape...) - Method in class ai.djl.nn.norm.BatchNorm: Performs any action necessary before initialization.
beforeInitialize(Shape...) - Method in class ai.djl.nn.norm.LayerNorm: Performs any action necessary before initialization.
beforeInitialize(Shape...) - Method in class ai.djl.nn.recurrent.RecurrentBlock: Performs any action necessary before initialization.
BertBlock - Class in ai.djl.nn.transformer: Implements the core bert model (without next sentence and masked language task) of bert.
BertBlock.Builder - Class in ai.djl.nn.transformer: The Builder to construct a BertBlock type of Block.
BertFullTokenizer - Class in ai.djl.modality.nlp.bert: BertFullTokenizer runs end to end tokenization of input text
BertFullTokenizer(Vocabulary, boolean) - Constructor for class ai.djl.modality.nlp.bert.BertFullTokenizer: Creates an instance of BertFullTokenizer.
BertMaskedLanguageModelBlock - Class in ai.djl.nn.transformer: Block for the bert masked language task.
BertMaskedLanguageModelBlock(BertBlock, Function<NDArray, NDArray>) - Constructor for class ai.djl.nn.transformer.BertMaskedLanguageModelBlock: Creates a new block that applies the masked language task.
BertMaskedLanguageModelLoss - Class in ai.djl.nn.transformer: The loss for the bert masked language model task.
BertMaskedLanguageModelLoss(int, int, int) - Constructor for class ai.djl.nn.transformer.BertMaskedLanguageModelLoss: Creates an MLM loss.
BertNextSentenceBlock - Class in ai.djl.nn.transformer: Block to perform the Bert next-sentence-prediction task.
BertNextSentenceBlock() - Constructor for class ai.djl.nn.transformer.BertNextSentenceBlock: Creates a next sentence block.
BertNextSentenceLoss - Class in ai.djl.nn.transformer: Calculates the loss for the next sentence prediction task.
BertNextSentenceLoss(int, int) - Constructor for class ai.djl.nn.transformer.BertNextSentenceLoss: Creates a new bert next sentence loss.
BertPretrainingBlock - Class in ai.djl.nn.transformer: Creates a block that performs all bert pretraining tasks (next sentence and masked language).
BertPretrainingBlock(BertBlock.Builder) - Constructor for class ai.djl.nn.transformer.BertPretrainingBlock: Creates a new Bert pretraining block fitting the given bert configuration.
BertPretrainingLoss - Class in ai.djl.nn.transformer: Loss that combines the next sentence and masked language losses of bert pretraining.
BertPretrainingLoss() - Constructor for class ai.djl.nn.transformer.BertPretrainingLoss: Creates a loss combining the next sentence and masked language loss for bert pretraining.
BertToken - Class in ai.djl.modality.nlp.bert: BertToken contains all the information for Bert model after encoding question and paragraph.
BertToken(List<String>, List<Long>, List<Long>, int) - Constructor for class ai.djl.modality.nlp.bert.BertToken: Creates an instance of BertToken which includes information for Bert model.
BertTokenizer - Class in ai.djl.modality.nlp.bert: BertTokenizer is a class to help you encode question and paragraph sentence.
BertTokenizer() - Constructor for class ai.djl.modality.nlp.bert.BertTokenizer
best() - Method in class ai.djl.modality.Classifications: Returns the most likely class for the classification.
BETA - ai.djl.nn.Parameter.Type
bias - Variable in class ai.djl.nn.convolutional.Convolution
bias - Variable in class ai.djl.nn.convolutional.Deconvolution
BIAS - ai.djl.nn.Parameter.Type
BICUBIC - ai.djl.modality.cv.Image.Interpolation
bidirectional - Variable in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder
bidirectional - Variable in class ai.djl.nn.recurrent.RecurrentBlock
BigGANTranslator - Class in ai.djl.modality.cv.translator: Built-in Translator that provides preprocessing and postprocessing for BigGAN.
BigGANTranslator(float) - Constructor for class ai.djl.modality.cv.translator.BigGANTranslator: Constructs a translator for BigGAN.
BigGANTranslatorFactory - Class in ai.djl.modality.cv.translator: A TranslatorFactory that creates a BigGANTranslator instance.
BigGANTranslatorFactory() - Constructor for class ai.djl.modality.cv.translator.BigGANTranslatorFactory
BILINEAR - ai.djl.modality.cv.Image.Interpolation
BinaryAccuracy - Class in ai.djl.training.evaluator: BinaryAccuracy is the AbstractAccuracy with two classes.
BinaryAccuracy() - Constructor for class ai.djl.training.evaluator.BinaryAccuracy: Creates a binary (two class) accuracy evaluator with 0 threshold.
BinaryAccuracy(float) - Constructor for class ai.djl.training.evaluator.BinaryAccuracy: Creates a binary (two class) accuracy evaluator that computes accuracy across axis 1 along the 0th index.
BinaryAccuracy(String, float) - Constructor for class ai.djl.training.evaluator.BinaryAccuracy: Creates a binary (two class) accuracy evaluator that computes accuracy across axis 1 along given index.
BinaryAccuracy(String, float, int) - Constructor for class ai.djl.training.evaluator.BinaryAccuracy: Creates a binary (two class) accuracy evaluator.
BITS - ai.djl.metric.Unit
BITS_PER_SECOND - ai.djl.metric.Unit
block - Variable in class ai.djl.BaseModel
block - Variable in class ai.djl.inference.Predictor
block - Variable in class ai.djl.modality.nlp.Decoder
block - Variable in class ai.djl.modality.nlp.Encoder
Block - Interface in ai.djl.nn: A Block is a composable function that forms a neural network.
BlockFactory - Interface in ai.djl.nn: Block factory is a component to make standard for block creating and saving procedure.
BlockList - Class in ai.djl.nn: Represents a set of names and Blocks.
BlockList() - Constructor for class ai.djl.nn.BlockList: Creates an empty BlockList.
BlockList(int) - Constructor for class ai.djl.nn.BlockList: Constructs an empty BlockList with the specified initial capacity.
BlockList(List<Pair<String, Block>>) - Constructor for class ai.djl.nn.BlockList: Constructs a BlockList containing the elements of the specified list of Pairs.
BlockList(List<String>, List<Block>) - Constructor for class ai.djl.nn.BlockList: Constructs a BlockList containing the elements of the specified keys and values.
BlockList(Map<String, Block>) - Constructor for class ai.djl.nn.BlockList: Constructs a BlockList containing the elements of the specified map.
Blocks - Class in ai.djl.nn: Utility class that provides some useful blocks.
BOOLEAN - ai.djl.ndarray.types.DataType
BOOLEAN - ai.djl.ndarray.types.DataType.Format
booleanMask(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns portion of this NDArray given the index boolean NDArray along first axis.
booleanMask(NDArray, int) - Method in interface ai.djl.ndarray.NDArray: Returns portion of this NDArray given the index boolean NDArray along given axis.
booleanMask(NDArray, int) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns portion of this NDArray given the index boolean NDArray along given axis.
booleanMask(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns portion of the NDArray given the index boolean NDArray along first axis.
booleanMask(NDArray, NDArray, int) - Static method in class ai.djl.ndarray.NDArrays: Returns portion of the NDArray given the index boolean NDArray along given axis.
booleanValue(Map<String, ?>, String) - Static method in class ai.djl.translate.ArgumentsUtil: Returns the boolean value from the arguments.
booleanValue(Map<String, ?>, String, boolean) - Static method in class ai.djl.translate.ArgumentsUtil: Returns the boolean value from the arguments.
BoundingBox - Interface in ai.djl.modality.cv.output: An interface representing a bounding box around an object inside an image.
BoundingBoxError - Class in ai.djl.training.evaluator: BoundingBoxError is an Evaluator that computes the error in the prediction of bounding boxes in SingleShotDetection model.
BoundingBoxError(String) - Constructor for class ai.djl.training.evaluator.BoundingBoxError: Creates an BoundingBoxError evaluator.
BOX - ai.djl.modality.cv.translator.YoloV5Translator.YoloOutputType
boxIntersection(Rectangle, Rectangle) - Method in class ai.djl.modality.cv.translator.YoloV5Translator
boxIou(Rectangle, Rectangle) - Method in class ai.djl.modality.cv.translator.YoloV5Translator
boxUnion(Rectangle, Rectangle) - Method in class ai.djl.modality.cv.translator.YoloV5Translator
broadcast(long...) - Method in interface ai.djl.ndarray.NDArray: Broadcasts this NDArray to be the given shape.
broadcast(Shape) - Method in interface ai.djl.ndarray.NDArray: Broadcasts this NDArray to be the given shape.
broadcast(Shape) - Method in class ai.djl.ndarray.NDArrayAdapter: Broadcasts this NDArray to be the given shape.
BufferedImageFactory - Class in ai.djl.modality.cv: BufferedImageFactory is the default implementation of ImageFactory.
BufferedImageFactory() - Constructor for class ai.djl.modality.cv.BufferedImageFactory
build() - Method in class ai.djl.modality.cv.MultiBoxDetection.Builder: Builds a MultiBoxDetection block.
build() - Method in class ai.djl.modality.cv.MultiBoxPrior.Builder: Builds a MultiBoxPrior block.
build() - Method in class ai.djl.modality.cv.MultiBoxTarget.Builder: Builds a MultiBoxTarget block.
build() - Method in class ai.djl.modality.cv.translator.ImageClassificationTranslator.Builder: Builds the ImageClassificationTranslator with the provided data.
build() - Method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslator.Builder: Builds the translator.
build() - Method in class ai.djl.modality.cv.translator.SimplePoseTranslator.Builder: Builds the translator.
build() - Method in class ai.djl.modality.cv.translator.SingleShotDetectionTranslator.Builder: Builds the translator.
build() - Method in class ai.djl.modality.cv.translator.YoloTranslator.Builder: Builds the translator.
build() - Method in class ai.djl.modality.cv.translator.YoloV5Translator.Builder: Builds the translator.
build() - Method in class ai.djl.modality.nlp.DefaultVocabulary.Builder: Builds the DefaultVocabulary object with the set arguments.
build() - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding.Builder: Builds a new instance of TrainableWordEmbedding based on the arguments in this builder.
build() - Method in class ai.djl.nn.convolutional.Conv1d.Builder: Builds a Conv1d block.
build() - Method in class ai.djl.nn.convolutional.Conv1dTranspose.Builder: Builds a Conv1dTranspose block.
build() - Method in class ai.djl.nn.convolutional.Conv2d.Builder: Builds a Conv2d block.
build() - Method in class ai.djl.nn.convolutional.Conv2dTranspose.Builder: Builds a Conv2dTranspose block.
build() - Method in class ai.djl.nn.convolutional.Conv3d.Builder: Builds a Conv3d block.
build() - Method in class ai.djl.nn.core.Linear.Builder: Returns the constructed Linear.
build() - Method in class ai.djl.nn.norm.BatchNorm.Builder: Builds a BatchNorm block.
build() - Method in class ai.djl.nn.norm.Dropout.Builder: Builds a Dropout block.
build() - Method in class ai.djl.nn.norm.LayerNorm.Builder: Builds a LayerNorm block.
build() - Method in class ai.djl.nn.Parameter.Builder: Builds a Parameter instance.
build() - Method in class ai.djl.nn.recurrent.GRU.Builder: Builds a GRU block.
build() - Method in class ai.djl.nn.recurrent.LSTM.Builder: Builds a LSTM block.
build() - Method in class ai.djl.nn.recurrent.RNN.Builder: Builds a RNN block.
build() - Method in class ai.djl.nn.transformer.BertBlock.Builder: Returns a new BertBlock with the parameters of this builder.
build() - Method in class ai.djl.nn.transformer.IdEmbedding.Builder: Builds the IdEmbedding.
build() - Method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock.Builder: Creates a new ScaledDotProductAttentionBlock with the current configuration.
build() - Method in class ai.djl.repository.zoo.Criteria.Builder: Builds a Criteria instance.
build() - Method in class ai.djl.training.dataset.ArrayDataset.Builder: Builds a new instance of ArrayDataset with the specified data and labels.
build() - Method in class ai.djl.training.optimizer.Adadelta.Builder: Builds a Adadelta block.
build() - Method in class ai.djl.training.optimizer.Adagrad.Builder: Builds a Adagrad block.
build() - Method in class ai.djl.training.optimizer.Adam.Builder: Builds a Adam block.
build() - Method in class ai.djl.training.optimizer.Nag.Builder: Builds a Nag block.
build() - Method in class ai.djl.training.optimizer.RmsProp.Builder: Builds a RmsProp block.
build() - Method in class ai.djl.training.optimizer.Sgd.Builder: Builds a Sgd block.
build() - Method in class ai.djl.training.tracker.CosineTracker.Builder: Builds a CosineTracker block.
build() - Method in class ai.djl.training.tracker.FactorTracker.Builder: Builds a FactorTracker block.
build() - Method in class ai.djl.training.tracker.LinearTracker.Builder: Builds a LinearTracker block.
build() - Method in class ai.djl.training.tracker.MultiFactorTracker.Builder: Builds a MultiFactorTracker block.
build() - Method in class ai.djl.training.tracker.PolynomialDecayTracker.Builder: Builds a PolynomialDecayTracker.
build() - Method in class ai.djl.training.tracker.WarmUpTracker.Builder: Builds a WarmUpTracker block.
build() - Method in class ai.djl.translate.PaddingStackBatchifier.Builder: Builds the PaddingStackBatchifier.
builder() - Static method in class ai.djl.modality.cv.MultiBoxDetection: Creates a builder to build a MultiBoxDetection.
builder() - Static method in class ai.djl.modality.cv.MultiBoxPrior: Creates a builder to build a MultiBoxPrior.
builder() - Static method in class ai.djl.modality.cv.MultiBoxTarget: Creates a builder to build a MultiBoxTarget.
builder() - Static method in class ai.djl.modality.cv.translator.ImageClassificationTranslator: Creates a builder to build a ImageClassificationTranslator.
builder() - Static method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslator: Creates a builder to build a InstanceSegmentationTranslator.
builder() - Static method in class ai.djl.modality.cv.translator.SimplePoseTranslator: Creates a builder to build a SimplePoseTranslator.
builder() - Static method in class ai.djl.modality.cv.translator.SingleShotDetectionTranslator: Creates a builder to build a SingleShotDetectionTranslator.
builder() - Static method in class ai.djl.modality.cv.translator.YoloTranslator: Creates a builder to build a YoloTranslator.
builder() - Static method in class ai.djl.modality.cv.translator.YoloV5Translator: Creates a builder to build a YoloV5Translator.
builder() - Static method in class ai.djl.modality.nlp.DefaultVocabulary: Creates a new builder to build a DefaultVocabulary.
builder() - Static method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Creates a builder to build an Embedding.
builder() - Static method in class ai.djl.nn.convolutional.Conv1d: Creates a builder to build a Conv1d.
builder() - Static method in class ai.djl.nn.convolutional.Conv1dTranspose: Creates a builder to build a Conv1dTranspose.
builder() - Static method in class ai.djl.nn.convolutional.Conv2d: Creates a builder to build a Conv2d.
builder() - Static method in class ai.djl.nn.convolutional.Conv2dTranspose: Creates a builder to build a Conv2dTranspose.
builder() - Static method in class ai.djl.nn.convolutional.Conv3d: Creates a builder to build a Conv3d.
builder() - Static method in class ai.djl.nn.core.Linear: Creates a builder to build a Linear.
builder() - Static method in class ai.djl.nn.norm.BatchNorm: Creates a builder to build a BatchNorm.
builder() - Static method in class ai.djl.nn.norm.Dropout: Creates a builder to build a Dropout.
builder() - Static method in class ai.djl.nn.norm.LayerNorm: Creates a builder to build a LayerNorm.
builder() - Static method in class ai.djl.nn.Parameter: Creates a builder to build a Parameter.
builder() - Static method in class ai.djl.nn.recurrent.GRU: Creates a builder to build a GRU.
builder() - Static method in class ai.djl.nn.recurrent.LSTM: Creates a builder to build a LSTM.
builder() - Static method in class ai.djl.nn.recurrent.RNN: Creates a builder to build a RNN.
builder() - Static method in class ai.djl.nn.transformer.BertBlock: Returns a new BertBlock builder.
builder() - Static method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock: Creates a new Builder to build an Attention Block with.
builder() - Static method in class ai.djl.repository.zoo.Criteria: Creates a builder to build a Criteria.
builder() - Static method in class ai.djl.training.optimizer.Adagrad: Creates a builder to build a Adam.
builder() - Static method in class ai.djl.training.optimizer.Adam: Creates a builder to build a Adam.
builder() - Static method in class ai.djl.training.optimizer.RmsProp: Creates a builder to build a RMSProp.
builder() - Static method in class ai.djl.training.tracker.CosineTracker: Creates a new builder.
builder() - Static method in class ai.djl.training.tracker.FactorTracker: Creates a new builder.
builder() - Static method in class ai.djl.training.tracker.LinearTracker: Creates a new builder.
builder() - Static method in class ai.djl.training.tracker.MultiFactorTracker: Creates a new builder.
builder() - Static method in class ai.djl.training.tracker.PolynomialDecayTracker: Creates a new builder.
builder() - Static method in class ai.djl.training.tracker.WarmUpTracker: Creates a new builder.
builder() - Static method in class ai.djl.translate.PaddingStackBatchifier: Returns a PaddingStackBatchifier.Builder.
builder(Map<String, ?>) - Static method in class ai.djl.modality.cv.translator.ImageClassificationTranslator: Creates a builder to build a ImageClassificationTranslator with specified arguments.
builder(Map<String, ?>) - Static method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslator: Creates a builder to build a InstanceSegmentationTranslator with specified arguments.
builder(Map<String, ?>) - Static method in class ai.djl.modality.cv.translator.SimplePoseTranslator: Creates a builder to build a SimplePoseTranslator with specified arguments.
builder(Map<String, ?>) - Static method in class ai.djl.modality.cv.translator.SingleShotDetectionTranslator: Creates a builder to build a SingleShotDetectionTranslator with specified arguments.
builder(Map<String, ?>) - Static method in class ai.djl.modality.cv.translator.YoloTranslator: Creates a builder to build a YoloTranslator with specified arguments.
builder(Map<String, ?>) - Static method in class ai.djl.modality.cv.translator.YoloV5Translator: Creates a builder to build a YoloV5Translator with specified arguments.
Builder() - Constructor for class ai.djl.modality.cv.translator.SingleShotDetectionTranslator.Builder
Builder() - Constructor for class ai.djl.modality.cv.translator.YoloTranslator.Builder
Builder() - Constructor for class ai.djl.modality.cv.translator.YoloV5Translator.Builder
Builder() - Constructor for class ai.djl.nn.Parameter.Builder
Builder() - Constructor for class ai.djl.nn.recurrent.GRU.Builder
Builder() - Constructor for class ai.djl.nn.recurrent.LSTM.Builder
Builder() - Constructor for class ai.djl.nn.recurrent.RNN.Builder
Builder() - Constructor for class ai.djl.nn.transformer.IdEmbedding.Builder
Builder() - Constructor for class ai.djl.training.dataset.ArrayDataset.Builder
buildModel(HpSet) - Method in class ai.djl.training.hyperparameter.EasyHpo: Builds the Model and Block to train.
buildSentence(List<String>) - Method in class ai.djl.modality.nlp.preprocess.SimpleTokenizer: Combines a list of tokens to form a sentence.
buildSentence(List<String>) - Method in interface ai.djl.modality.nlp.preprocess.Tokenizer: Combines a list of tokens to form a sentence.
BYTES - ai.djl.metric.Unit
BYTES_PER_SECOND - ai.djl.metric.Unit
BytesSupplier - Interface in ai.djl.ndarray: Represents a supplier of byte[].

C

cast(DataType) - Method in interface ai.djl.Model: Casts the model to support a different precision level.
cast(DataType) - Method in class ai.djl.nn.AbstractBaseBlock: Guaranteed to throw an exception.
cast(DataType) - Method in interface ai.djl.nn.Block: Guaranteed to throw an exception.
cast(DataType) - Method in class ai.djl.repository.zoo.ZooModel: Casts the model to support a different precision level.
cbrt() - Method in interface ai.djl.ndarray.NDArray: Returns the cube-root of this NDArray element-wise.
cbrt() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the cube-root of this NDArray element-wise.
ceil() - Method in interface ai.djl.ndarray.NDArray: Returns the ceiling of this NDArray element-wise.
ceil() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the ceiling of this NDArray element-wise.
centerCrop(NDArray) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Crops an image to a square of size min(width, height).
centerCrop(NDArray, int, int) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Crops an image to a given width and height from the center of the image.
CenterCrop - Class in ai.djl.modality.cv.transform: A Transform that crops the center of an image.
CenterCrop() - Constructor for class ai.djl.modality.cv.transform.CenterCrop: Creates a CenterCrop Transform that crops to size min(width, height).
CenterCrop(int, int) - Constructor for class ai.djl.modality.cv.transform.CenterCrop: Creates a CenterCrop Transform that crops the given width and height.
CHANNEL - ai.djl.ndarray.types.LayoutType
checkConcatInput(NDList) - Static method in class ai.djl.ndarray.NDUtils: Check two criteria of concat input: 1.
checkLabelShapes(NDArray, NDArray) - Method in class ai.djl.training.evaluator.Evaluator: Checks the length of NDArrays.
checkLabelShapes(NDArray, NDArray, boolean) - Method in class ai.djl.training.evaluator.Evaluator: Checks if the two input NDArray have the same length or shape.
children - Variable in class ai.djl.nn.AbstractBlock: All direct children of this Block.
chooseAction(RlEnv, boolean) - Method in class ai.djl.modality.rl.agent.EpsilonGreedy: Chooses the next action to take within the RlEnv.
chooseAction(RlEnv, boolean) - Method in class ai.djl.modality.rl.agent.QAgent: Chooses the next action to take within the RlEnv.
chooseAction(RlEnv, boolean) - Method in interface ai.djl.modality.rl.agent.RlAgent: Chooses the next action to take within the RlEnv.
classes - Variable in class ai.djl.modality.cv.translator.ObjectDetectionTranslator
Classification(String, double) - Constructor for class ai.djl.modality.Classifications.Classification: Constructs a single class result for a classification.
ClassificationBuilder() - Constructor for class ai.djl.modality.cv.translator.BaseImageTranslator.ClassificationBuilder
Classifications - Class in ai.djl.modality: Classifications is the container that stores the classification results for classification on a single input.
Classifications(List<String>, NDArray) - Constructor for class ai.djl.modality.Classifications: Constructs a Classifications using list of classNames parallel to an NDArray of probabilities.
Classifications(List<String>, NDArray, int) - Constructor for class ai.djl.modality.Classifications: Constructs a Classifications using list of classNames parallel to an NDArray of probabilities.
Classifications(List<String>, List<Double>) - Constructor for class ai.djl.modality.Classifications: Constructs a Classifications using a parallel list of classNames and probabilities.
Classifications.Classification - Class in ai.djl.modality: A Classification stores the classification result for a single class on a single input.
Classifications.ClassificationsSerializer - Class in ai.djl.modality: A customized Gson serializer to serialize the Classifications object.
ClassificationsSerializer() - Constructor for class ai.djl.modality.Classifications.ClassificationsSerializer
classNames - Variable in class ai.djl.modality.Classifications
clear() - Method in class ai.djl.nn.AbstractBaseBlock: Closes all the parameters of the block.
clear() - Method in interface ai.djl.nn.Block: Closes all the parameters of the block.
clip(Number, Number) - Method in interface ai.djl.ndarray.NDArray: Clips (limit) the values in this NDArray.
clip(Number, Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Clips (limit) the values in this NDArray.
clipGrad - Variable in class ai.djl.training.optimizer.Optimizer
close() - Method in class ai.djl.BaseModel
close() - Method in class ai.djl.inference.Predictor
close() - Method in class ai.djl.modality.nlp.embedding.ModelZooTextEmbedding
close() - Method in interface ai.djl.modality.rl.env.RlEnv
close() - Method in interface ai.djl.modality.rl.env.RlEnv.Step
close() - Method in interface ai.djl.Model
close() - Method in class ai.djl.ndarray.BaseNDManager
close() - Method in interface ai.djl.ndarray.NDArray
close() - Method in class ai.djl.ndarray.NDArrayAdapter
close() - Method in class ai.djl.ndarray.NDList
close() - Method in interface ai.djl.ndarray.NDManager
close() - Method in interface ai.djl.ndarray.NDResource
close() - Method in class ai.djl.nn.Parameter
close() - Method in class ai.djl.repository.zoo.ZooModel
close() - Method in class ai.djl.training.dataset.Batch
close() - Method in interface ai.djl.training.GradientCollector
close() - Method in class ai.djl.training.LocalParameterServer
close() - Method in interface ai.djl.training.ParameterServer
close() - Method in class ai.djl.training.Trainer
close() - Method in class ai.djl.training.util.MinMaxScaler
close() - Method in interface ai.djl.translate.TranslatorContext
closed - Variable in class ai.djl.ndarray.BaseNDManager
collectMemoryInfo(Metrics) - Static method in class ai.djl.training.listener.MemoryTrainingListener: Collects memory information.
COLOR - ai.djl.modality.cv.Image.Flag
compare(Artifact, Artifact) - Method in class ai.djl.repository.Artifact.VersionComparator
compareTo(Version) - Method in class ai.djl.repository.Version
components - Variable in class ai.djl.training.loss.AbstractCompositeLoss
concat(NDArray) - Method in interface ai.djl.ndarray.NDArray: Joins a NDArray along the first axis.
concat(NDArray, int) - Method in interface ai.djl.ndarray.NDArray: Joins a NDArray along an existing axis.
concat(NDList) - Static method in class ai.djl.ndarray.NDArrays: Joins a NDList along the first axis.
concat(NDList, int) - Static method in class ai.djl.ndarray.NDArrays: Joins a NDList along an existing axis.
configPostProcess(Map<String, ?>) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder
configPostProcess(Map<String, ?>) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.ClassificationBuilder
configPostProcess(Map<String, ?>) - Method in class ai.djl.modality.cv.translator.ImageClassificationTranslator.Builder
configPostProcess(Map<String, ?>) - Method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslator.Builder
configPostProcess(Map<String, ?>) - Method in class ai.djl.modality.cv.translator.ObjectDetectionTranslator.ObjectDetectionBuilder
configPostProcess(Map<String, ?>) - Method in class ai.djl.modality.cv.translator.SimplePoseTranslator.Builder
configPostProcess(Map<String, ?>) - Method in class ai.djl.modality.cv.translator.YoloV5Translator.Builder
configPreProcess(Map<String, ?>) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder
configure(Map<String, ?>) - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder: Configures the builder with the model arguments.
CONSTANT - ai.djl.training.tracker.WarmUpTracker.Mode
ConstantEmbedding - Class in ai.djl.nn.core: An AbstractIndexedEmbedding that always returns a constant value.
ConstantEmbedding(NDArray) - Constructor for class ai.djl.nn.core.ConstantEmbedding: Constructs a constant embedding with the given constant.
ConstantInitializer - Class in ai.djl.training.initializer: Initializer that generates tensors with constant values.
ConstantInitializer(float) - Constructor for class ai.djl.training.initializer.ConstantInitializer: Creates a Constant Initializer.
contains(Artifact) - Method in class ai.djl.repository.VersionRange: Returns true if the artifact's version falls within this range.
contains(Version) - Method in class ai.djl.repository.VersionRange: Returns true if a version falls within this range.
contains(String) - Method in class ai.djl.modality.nlp.DefaultVocabulary: Check if the vocabulary contains a token.
contains(String) - Method in interface ai.djl.modality.nlp.Vocabulary: Check if the vocabulary contains a token.
contains(String) - Method in class ai.djl.ndarray.NDList: Returns true if this NDList contains an NDArray with the specified name.
contentEquals(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns true if all elements in this NDArray are equal to the other NDArray.
contentEquals(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns true if all elements in this NDArray are equal to the other NDArray.
contentEquals(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns true if all elements in NDArray a are equal to NDArray b.
contentEquals(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Returns true if all elements in NDArray a are equal to NDArray b.
contentEquals(Number) - Method in interface ai.djl.ndarray.NDArray: Returns true if all elements in this NDArray are equal to the Number.
contentEquals(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns true if all elements in this NDArray are equal to the Number.
conv1d(NDArray, NDArray) - Static method in class ai.djl.nn.convolutional.Conv1d: Applies 1D convolution over an input signal composed of several input planes.
conv1d(NDArray, NDArray, NDArray) - Static method in class ai.djl.nn.convolutional.Conv1d: Applies 1D convolution over an input signal composed of several input planes.
conv1d(NDArray, NDArray, NDArray, Shape) - Static method in class ai.djl.nn.convolutional.Conv1d: Applies 1D convolution over an input signal composed of several input planes.
conv1d(NDArray, NDArray, NDArray, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv1d: Applies 1D convolution over an input signal composed of several input planes.
conv1d(NDArray, NDArray, NDArray, Shape, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv1d: Applies 1D convolution over an input signal composed of several input planes.
conv1d(NDArray, NDArray, NDArray, Shape, Shape, Shape, int) - Static method in class ai.djl.nn.convolutional.Conv1d: Applies 1D convolution over an input signal composed of several input planes.
Conv1d - Class in ai.djl.nn.convolutional: A Conv1d layer works similar to Convolution layer with the exception of the number of dimension it operates on being only one, which is LayoutType.WIDTH.
Conv1d.Builder - Class in ai.djl.nn.convolutional: The Builder to construct a Conv1d type of Block.
conv1dTranspose(NDArray, NDArray) - Static method in class ai.djl.nn.convolutional.Conv1dTranspose: Applies 1D deconvolution over an input signal composed of several input planes.
conv1dTranspose(NDArray, NDArray, NDArray) - Static method in class ai.djl.nn.convolutional.Conv1dTranspose: Applies 1D deconvolution over an input signal composed of several input planes.
conv1dTranspose(NDArray, NDArray, NDArray, Shape) - Static method in class ai.djl.nn.convolutional.Conv1dTranspose: Applies 1D deconvolution over an input signal composed of several input planes.
conv1dTranspose(NDArray, NDArray, NDArray, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv1dTranspose: Applies 1D deconvolution over an input signal composed of several input planes.
conv1dTranspose(NDArray, NDArray, NDArray, Shape, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv1dTranspose: Applies 1D deconvolution over an input signal composed of several input planes.
conv1dTranspose(NDArray, NDArray, NDArray, Shape, Shape, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv1dTranspose: Applies 1D deconvolution over an input signal composed of several input planes.
conv1dTranspose(NDArray, NDArray, NDArray, Shape, Shape, Shape, Shape, int) - Static method in class ai.djl.nn.convolutional.Conv1dTranspose: Applies 1D convolution over an input signal composed of several input planes.
Conv1dTranspose - Class in ai.djl.nn.convolutional: A Conv1dTranspose layer works similar to Deconvolution layer with the exception of the number of dimension it operates on being only one, which is LayoutType.WIDTH.
Conv1dTranspose.Builder - Class in ai.djl.nn.convolutional: The Builder to construct a Conv1dTranspose type of Block.
conv2d(NDArray, NDArray) - Static method in class ai.djl.nn.convolutional.Conv2d: Applies 2D convolution over an input signal composed of several input planes.
conv2d(NDArray, NDArray, NDArray) - Static method in class ai.djl.nn.convolutional.Conv2d: Applies 2D convolution over an input signal composed of several input planes.
conv2d(NDArray, NDArray, NDArray, Shape) - Static method in class ai.djl.nn.convolutional.Conv2d: Applies 2D convolution over an input signal composed of several input planes.
conv2d(NDArray, NDArray, NDArray, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv2d: Applies 2D convolution over an input signal composed of several input planes.
conv2d(NDArray, NDArray, NDArray, Shape, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv2d: Applies 2D convolution over an input signal composed of several input planes.
conv2d(NDArray, NDArray, NDArray, Shape, Shape, Shape, int) - Static method in class ai.djl.nn.convolutional.Conv2d: Applies 2D convolution over an input signal composed of several input planes.
Conv2d - Class in ai.djl.nn.convolutional: Being the pioneer of convolution layers, Conv2d layer works on two dimensions of input, LayoutType.WIDTH and LayoutType.HEIGHT as usually a Conv2d layer is used to process data with two spatial dimensions, namely image.
Conv2d.Builder - Class in ai.djl.nn.convolutional: The Builder to construct a Conv2d type of Block.
conv2dTranspose(NDArray, NDArray) - Static method in class ai.djl.nn.convolutional.Conv2dTranspose: Applies 2D deconvolution over an input signal composed of several input planes.
conv2dTranspose(NDArray, NDArray, NDArray) - Static method in class ai.djl.nn.convolutional.Conv2dTranspose: Applies 2D deconvolution over an input signal composed of several input planes.
conv2dTranspose(NDArray, NDArray, NDArray, Shape) - Static method in class ai.djl.nn.convolutional.Conv2dTranspose: Applies 2D deconvolution over an input signal composed of several input planes.
conv2dTranspose(NDArray, NDArray, NDArray, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv2dTranspose: Applies 2D deconvolution over an input signal composed of several input planes.
conv2dTranspose(NDArray, NDArray, NDArray, Shape, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv2dTranspose: Applies 2D deconvolution over an input signal composed of several input planes.
conv2dTranspose(NDArray, NDArray, NDArray, Shape, Shape, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv2dTranspose: Applies 2D deconvolution over an input signal composed of several input planes.
conv2dTranspose(NDArray, NDArray, NDArray, Shape, Shape, Shape, Shape, int) - Static method in class ai.djl.nn.convolutional.Conv2dTranspose: Applies 2D deconvolution over an input signal composed of several input planes.
Conv2dTranspose - Class in ai.djl.nn.convolutional: The input to a Conv2dTranspose is an NDList with a single 4-D NDArray.
Conv2dTranspose.Builder - Class in ai.djl.nn.convolutional: The Builder to construct a Conv2dTranspose type of Block.
conv3d(NDArray, NDArray) - Static method in class ai.djl.nn.convolutional.Conv3d: Applies 3D convolution over an input signal composed of several input planes.
conv3d(NDArray, NDArray, NDArray) - Static method in class ai.djl.nn.convolutional.Conv3d: Applies 3D convolution over an input signal composed of several input planes.
conv3d(NDArray, NDArray, NDArray, Shape) - Static method in class ai.djl.nn.convolutional.Conv3d: Applies 3D convolution over an input signal composed of several input planes.
conv3d(NDArray, NDArray, NDArray, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv3d: Applies 3D convolution over an input signal composed of several input planes.
conv3d(NDArray, NDArray, NDArray, Shape, Shape, Shape) - Static method in class ai.djl.nn.convolutional.Conv3d: Applies 3D convolution over an input signal composed of several input planes.
conv3d(NDArray, NDArray, NDArray, Shape, Shape, Shape, int) - Static method in class ai.djl.nn.convolutional.Conv3d: Applies 3D convolution over an input signal composed of several input planes.
Conv3d - Class in ai.djl.nn.convolutional: Conv3d layer behaves just as Convolution does, with the distinction being it operates of 3-dimensional data such as medical images or video data.
Conv3d.Builder - Class in ai.djl.nn.convolutional: The Builder to construct a Conv3d type of Block.
Convolution - Class in ai.djl.nn.convolutional: A convolution layer does a dot product calculation on each channel of \(k\)-channel input data by specified number of filters, each containing \(k\) kernels for calculating each channel in the input data and then summed per filter, hence the number of filters denote the number of output channels of a convolution layer.
Convolution(Convolution.ConvolutionBuilder<?>) - Constructor for class ai.djl.nn.convolutional.Convolution: Creates a Convolution object.
Convolution.ConvolutionBuilder<T extends Convolution.ConvolutionBuilder> - Class in ai.djl.nn.convolutional: A builder that can build any Convolution block.
ConvolutionBuilder() - Constructor for class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder
COO - ai.djl.ndarray.types.SparseFormat
copyBuffer(Buffer, ByteBuffer) - Static method in class ai.djl.ndarray.BaseNDManager: Copies data from the source Buffer to the target ByteBuffer.
copyTo(NDArray) - Method in interface ai.djl.ndarray.NDArray: Deep-copies the current NDArray to the one passed in.
copyTo(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Deep-copies the current NDArray to the one passed in.
correctInstances - Variable in class ai.djl.training.evaluator.AbstractAccuracy
cos() - Method in interface ai.djl.ndarray.NDArray: Returns the trigonometric cosine of this NDArray element-wise.
cos() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the trigonometric cosine of this NDArray element-wise.
cosh() - Method in interface ai.djl.ndarray.NDArray: Returns the hyperbolic cosine of this NDArray element-wise.
cosh() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the hyperbolic cosine of this NDArray element-wise.
cosine() - Static method in interface ai.djl.training.tracker.Tracker: Returns a new instance of CosineTracker.Builder that can build an CosineTracker.
CosineTracker - Class in ai.djl.training.tracker: CosineTracker is an implementation of Tracker which is updated by taking sections of a cosine curve to smoothly reduce learning rate until a specified step and base learning rate.
CosineTracker(CosineTracker.Builder) - Constructor for class ai.djl.training.tracker.CosineTracker: Creates a new instance of CosineTracker.
CosineTracker.Builder - Class in ai.djl.training.tracker: The Builder to construct an CosineTracker object.
COUNT - ai.djl.metric.Unit
COUNT_PER_SECOND - ai.djl.metric.Unit
countNonzero() - Method in interface ai.djl.ndarray.NDArray: Counts the number of non-zero values in this NDArray.
countNonzero(int) - Method in interface ai.djl.ndarray.NDArray: Counts the number of non-zero values in this NDArray along a given axis.
cpu() - Static method in class ai.djl.Device: Returns the default CPU Device.
CPU - Static variable in interface ai.djl.Device.Type
create(boolean) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a scalar NDArray.
create(boolean[]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 1D NDArray.
create(boolean[][]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 2-D NDArray.
create(boolean[], Shape) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes an instance of NDArray with specified Shape and boolean array.
create(byte) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a scalar NDArray.
create(byte[]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 1D NDArray.
create(byte[][]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 2-D NDArray.
create(byte[], Shape) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes an instance of NDArray with specified Shape and byte array.
create(double) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a scalar NDArray.
create(double[]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 1D NDArray.
create(double[][]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 2D NDArray.
create(double[], Shape) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes an instance of NDArray with specified Shape and double array.
create(float) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a scalar NDArray.
create(float[]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 1D NDArray.
create(float[][]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 2D NDArray.
create(float[], Shape) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes an instance of NDArray with specified Shape and float array.
create(int) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a scalar NDArray.
create(int[]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 1D NDArray.
create(int[][]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 2D NDArray.
create(int[], Shape) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes an instance of NDArray with specified Shape and int array.
create(long) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a scalar NDArray.
create(long[]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 1D NDArray.
create(long[][]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a 2-D NDArray.
create(long[], Shape) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes an instance of NDArray with specified Shape and long array.
create(Shape) - Method in interface ai.djl.ndarray.NDManager: Creates an uninitialized instance of DataType.FLOAT32 NDArray with specified Shape.
create(Shape, DataType) - Method in class ai.djl.ndarray.BaseNDManager: Creates an uninitialized instance of NDArray with specified Shape, and DataType.
create(Shape, DataType) - Method in interface ai.djl.ndarray.NDManager: Creates an uninitialized instance of NDArray with specified Shape, and DataType.
create(Shape, DataType, Device) - Method in interface ai.djl.ndarray.NDManager: Creates an uninitialized instance of NDArray with specified Shape, DataType and Device.
create(Number) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a scalar NDArray.
create(String) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a scalar NDArray.
create(String[]) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes 1D NDArray.
create(String[], Shape) - Method in interface ai.djl.ndarray.NDManager: Creates a String NDArray based on the provided shape.
create(String[], Charset) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes 1D NDArray.
create(String[], Charset, Shape) - Method in class ai.djl.ndarray.BaseNDManager: Creates a String NDArray based on the provided shape.
create(String[], Charset, Shape) - Method in interface ai.djl.ndarray.NDManager: Creates a String NDArray based on the provided shape.
create(Buffer, Shape) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes a NDArray with specified Shape.
create(Buffer, Shape, DataType) - Method in interface ai.djl.ndarray.NDManager: Creates and initializes an instance of NDArray with specified Shape and DataType.
createAttentionMaskFromInputMask(NDArray, NDArray) - Static method in class ai.djl.nn.transformer.BertBlock: Creates a 3D attention mask from a 2D tensor mask.
createCoo(Buffer, long[][], Shape) - Method in class ai.djl.ndarray.BaseNDManager: Creates a Coordinate Format (COO) Matrix.
createCoo(Buffer, long[][], Shape) - Method in interface ai.djl.ndarray.NDManager: Creates a Coordinate Format (COO) Matrix.
createCSR(float[], long[], long[], Shape, Device) - Method in interface ai.djl.ndarray.NDManager: Creates a Compressed Sparse Row Storage (CSR) Format Matrix.
createCSR(Buffer, long[], long[], Shape) - Method in class ai.djl.ndarray.BaseNDManager: Creates a Compressed Sparse Row Storage (CSR) Format Matrix.
createCSR(Buffer, long[], long[], Shape) - Method in interface ai.djl.ndarray.NDManager: Creates a Compressed Sparse Row Storage (CSR) Format Matrix.
createCSR(Buffer, long[], long[], Shape, Device) - Method in interface ai.djl.ndarray.NDManager: Creates a Compressed Sparse Row Storage (CSR) Format Matrix.
createModel(Path, String, Device, Block, Map<String, Object>, String) - Method in class ai.djl.repository.zoo.BaseModelLoader
createRowSparse(Buffer, Shape, long[], Shape) - Method in class ai.djl.ndarray.BaseNDManager: Stores the matrix in row sparse format.
createRowSparse(Buffer, Shape, long[], Shape) - Method in interface ai.djl.ndarray.NDManager: Stores the matrix in row sparse format.
createRowSparse(Buffer, Shape, long[], Shape, Device) - Method in interface ai.djl.ndarray.NDManager: Stores the matrix in row sparse format.
Criteria<I,O> - Class in ai.djl.repository.zoo: The Criteria class contains search criteria to look up a ZooModel.
Criteria.Builder<I,O> - Class in ai.djl.repository.zoo: A Builder to construct a Criteria.
crop(NDArray, int, int, int, int) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Crops an image with a given location and size.
Crop - Class in ai.djl.modality.cv.transform: A Transform that crops the image to a given location and size.
Crop(int, int, int, int) - Constructor for class ai.djl.modality.cv.transform.Crop: Creates a CenterCrop Transform.
CSR - ai.djl.ndarray.types.SparseFormat
CUDA - Static variable in class ai.djl.engine.StandardCapabilities
CUDNN - Static variable in class ai.djl.engine.StandardCapabilities
cumSum() - Method in interface ai.djl.ndarray.NDArray: Returns the cumulative sum of the elements in the flattened NDArray.
cumSum() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the cumulative sum of the elements in the flattened NDArray.
cumSum(int) - Method in interface ai.djl.ndarray.NDArray: Return the cumulative sum of the elements along a given axis.
cumSum(int) - Method in class ai.djl.ndarray.NDArrayAdapter: Return the cumulative sum of the elements along a given axis.

D

data - Variable in class ai.djl.training.dataset.ArrayDataset
dataBatchifier - Variable in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder
dataBatchifier - Variable in class ai.djl.training.dataset.RandomAccessDataset
DataDesc - Class in ai.djl.ndarray.types: A data descriptor class that encapsulates information of a NDArray.
DataDesc(Shape) - Constructor for class ai.djl.ndarray.types.DataDesc: Constructs and initializes a DataDesc with specified Shape.
DataDesc(Shape, DataType) - Constructor for class ai.djl.ndarray.types.DataDesc: Constructs and initializes a DataDesc with specified Shape and DataType.
DataDesc(Shape, DataType, String) - Constructor for class ai.djl.ndarray.types.DataDesc: Constructs and initializes a DataDesc with specified Shape, DataType, name, Device and SparseFormat.
DataDesc(Shape, String) - Constructor for class ai.djl.ndarray.types.DataDesc: Constructs and initializes a DataDesc with specified Shape and name.
DataIterable - Class in ai.djl.training.dataset: DataIterable is a data loader that combines Dataset, Batchifier, Pipeline, and Sampler to provide an iterable over the given RandomAccessDataset.
DataIterable(RandomAccessDataset, NDManager, Sampler, Batchifier, Batchifier, Pipeline, Pipeline, ExecutorService, int, Device) - Constructor for class ai.djl.training.dataset.DataIterable: Creates a new instance of DataIterable with the given parameters.
dataset(Application, String, String) - Method in interface ai.djl.repository.Repository: Creates a dataset MRL with specified application.
dataset(Application, String, String, String) - Method in interface ai.djl.repository.Repository: Creates a dataset MRL with specified application.
dataset(Repository, Application, String, String, String) - Static method in class ai.djl.repository.MRL: Creates a dataset MRL with specified application.
Dataset - Interface in ai.djl.training.dataset: An interface to represent a set of sample data/label pairs to train a model.
Dataset.Usage - Enum in ai.djl.training.dataset: An enum that indicates the mode - training, test or validation.
dataType - Variable in class ai.djl.BaseModel
dataType - Variable in class ai.djl.ndarray.NDArrayAdapter
DataType - Enum in ai.djl.ndarray.types: An enum representing the underlying NDArray's data type.
DataType.Format - Enum in ai.djl.ndarray.types: The general data type format categories.
debugDump(int) - Method in class ai.djl.ndarray.BaseNDManager: Prints information about this NDManager and all sub-managers to the console.
debugEnvironment() - Static method in class ai.djl.engine.Engine: Prints debug information about the environment for debugging environment issues.
decode(byte[]) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Decodes the given byte array into an object of input parameter type.
decode(byte[]) - Method in interface ai.djl.ndarray.NDManager: Decodes NDArray through byte array.
decode(byte[]) - Method in interface ai.djl.nn.core.AbstractIndexedEmbedding: Decodes the given byte array into an object of input parameter type.
decode(byte[]) - Method in class ai.djl.nn.core.ConstantEmbedding: Decodes the given byte array into an object of input parameter type.
decode(byte[]) - Method in class ai.djl.nn.core.Embedding.DefaultEmbedding: Decodes the given byte array into an object of input parameter type.
decode(byte[]) - Method in class ai.djl.nn.core.Embedding.DefaultItem: Decodes the given byte array into an object of input parameter type.
decode(NDManager, byte[]) - Static method in interface ai.djl.ndarray.NDArray: Decodes NDArray from bytes.
decode(NDManager, byte[]) - Static method in class ai.djl.ndarray.NDList: Decodes NDList from byte array.
decode(NDManager, InputStream) - Static method in class ai.djl.ndarray.NDList: Decodes NDList from InputStream.
decode(DataInputStream) - Static method in class ai.djl.ndarray.types.Shape: Decodes the data in the given DataInputStream and converts it into the corresponding Shape object.
decode(InputStream) - Method in interface ai.djl.ndarray.NDManager: Decodes NDArray through DataInputStream.
decoder - Variable in class ai.djl.modality.nlp.EncoderDecoder
Decoder - Class in ai.djl.modality.nlp: Decoder is an abstract block that be can used as decoder in encoder-decoder architecture.
Decoder(byte, Block) - Constructor for class ai.djl.modality.nlp.Decoder: Constructs a new instance of Decoder with the given block.
Deconvolution - Class in ai.djl.nn.convolutional: Transposed convolution, also named fractionally-strided convolution Dumoulin & Visin or deconvolution Long et al., 2015, serves this purpose.
Deconvolution(Deconvolution.DeconvolutionBuilder<?>) - Constructor for class ai.djl.nn.convolutional.Deconvolution: Creates a Deconvolution object.
Deconvolution.DeconvolutionBuilder<T extends Deconvolution.DeconvolutionBuilder> - Class in ai.djl.nn.convolutional: A builder that can build any Deconvolution block.
DeconvolutionBuilder() - Constructor for class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder
DEFAULT_FORM - Static variable in class ai.djl.modality.nlp.preprocess.UnicodeNormalizer
defaultDevice() - Method in class ai.djl.engine.Engine: Returns the engine's default Device.
defaultDevice() - Method in class ai.djl.ndarray.BaseNDManager: Returns the default context used in Engine.
defaultDevice() - Method in interface ai.djl.ndarray.NDManager: Returns the default context used in Engine.
DefaultEmbedding() - Constructor for class ai.djl.nn.core.Embedding.DefaultEmbedding
defaultFactory - Variable in class ai.djl.repository.zoo.BaseModelLoader
defaultItem - Variable in class ai.djl.nn.core.Embedding.BaseBuilder
DefaultItem(T) - Constructor for class ai.djl.nn.core.Embedding.DefaultItem
DefaultModelZoo - Class in ai.djl.repository.zoo: A ModelZoo that contains models in specified locations.
DefaultModelZoo() - Constructor for class ai.djl.repository.zoo.DefaultModelZoo: Constructs a new LocalModelZoo instance.
DefaultModelZoo(String) - Constructor for class ai.djl.repository.zoo.DefaultModelZoo: Constructs a new LocalModelZoo instance from the given search locations.
DefaultTrainingConfig - Class in ai.djl.training: DefaultTrainingConfig is an implementation of the TrainingConfig interface.
DefaultTrainingConfig(Loss) - Constructor for class ai.djl.training.DefaultTrainingConfig: Creates an instance of DefaultTrainingConfig with the given Loss.
DefaultTranslatorFactory - Class in ai.djl.translate: A default implementation of TranslatorFactory.
DefaultTranslatorFactory() - Constructor for class ai.djl.translate.DefaultTranslatorFactory
DefaultVocabulary - Class in ai.djl.modality.nlp: The default implementation of Vocabulary.
DefaultVocabulary(DefaultVocabulary.Builder) - Constructor for class ai.djl.modality.nlp.DefaultVocabulary: Creates a DefaultVocabulary object with a DefaultVocabulary.Builder.
DefaultVocabulary(List<String>) - Constructor for class ai.djl.modality.nlp.DefaultVocabulary: Creates a DefaultVocabulary object with the given list of tokens.
DefaultVocabulary.Builder - Class in ai.djl.modality.nlp: Builder class that is used to build the DefaultVocabulary.
DefaultZooProvider - Class in ai.djl.repository.zoo: An ZooProvider implementation can load models from specified locations.
DefaultZooProvider() - Constructor for class ai.djl.repository.zoo.DefaultZooProvider
DENSE - ai.djl.ndarray.types.SparseFormat
DEPTH - ai.djl.ndarray.types.LayoutType
describeInput() - Method in class ai.djl.BaseModel: Returns the input descriptor of the model.
describeInput() - Method in class ai.djl.modality.nlp.EncoderDecoder: Returns a PairList of input names, and shapes.
describeInput() - Method in interface ai.djl.Model: Returns the input descriptor of the model.
describeInput() - Method in class ai.djl.nn.AbstractBaseBlock: Returns a PairList of input names, and shapes.
describeInput() - Method in interface ai.djl.nn.Block: Returns a PairList of input names, and shapes.
describeInput() - Method in class ai.djl.nn.core.Linear: Returns a PairList of input names, and shapes.
describeInput() - Method in class ai.djl.repository.zoo.ZooModel: Returns the input descriptor of the model.
describeOutput() - Method in class ai.djl.BaseModel: Returns the output descriptor of the model.
describeOutput() - Method in interface ai.djl.Model: Returns the output descriptor of the model.
describeOutput() - Method in interface ai.djl.nn.SymbolBlock: Returns a PairList of output names and shapes stored in model file.
describeOutput() - Method in class ai.djl.repository.zoo.ZooModel: Returns the output descriptor of the model.
detach() - Method in class ai.djl.ndarray.NDList: Detaches the NDResource from current NDManager's lifecycle.
detach() - Method in interface ai.djl.ndarray.NDResource: Detaches the NDResource from current NDManager's lifecycle.
detach() - Method in class ai.djl.training.util.MinMaxScaler: Detaches this MinMaxScaler fitted value from current NDManager's lifecycle.
detachInternal(String) - Method in class ai.djl.ndarray.BaseNDManager: Detaches a NDArray from this NDManager's lifecycle.
detachInternal(String) - Method in interface ai.djl.ndarray.NDManager: Detaches a NDArray from this NDManager's lifecycle.
DETECT - ai.djl.modality.cv.translator.YoloV5Translator.YoloOutputType
DetectedObject(String, double, BoundingBox) - Constructor for class ai.djl.modality.cv.output.DetectedObjects.DetectedObject: Constructs a bounding box with the given data.
DetectedObjects - Class in ai.djl.modality.cv.output: A class representing the detected objects results for a single image in an Application.CV.OBJECT_DETECTION case.
DetectedObjects(List<String>, List<Double>, List<BoundingBox>) - Constructor for class ai.djl.modality.cv.output.DetectedObjects: Constructs a DetectedObjects, usually during post-processing.
DetectedObjects.DetectedObject - Class in ai.djl.modality.cv.output: A DetectedObject represents a single potential detected Object for an image.
detection(NDList) - Method in class ai.djl.modality.cv.MultiBoxDetection: Converts multi-box detection predictions.
device - Variable in class ai.djl.ndarray.BaseNDManager
device - Variable in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder
device - Variable in class ai.djl.training.dataset.RandomAccessDataset
Device - Class in ai.djl: The Device class provides the specified assignment for CPU/GPU processing on the NDArray.
Device.Type - Interface in ai.djl: Contains device type string constants.
DeviceType - Interface in ai.djl: DeviceType is a class used to map the Device name to their corresponding type number.
dilation - Variable in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder
dilation - Variable in class ai.djl.nn.convolutional.Convolution
dilation - Variable in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder
dilation - Variable in class ai.djl.nn.convolutional.Deconvolution
dimension() - Method in class ai.djl.ndarray.types.Shape: Returns the number of dimensions of this Shape.
Dimension - Class in ai.djl.metric: A class represents a metric dimension.
Dimension() - Constructor for class ai.djl.metric.Dimension: Constructs a new Dimension instance.
Dimension(String, String) - Constructor for class ai.djl.metric.Dimension: Constructs a new Dimension instance.
div(NDArray) - Method in interface ai.djl.ndarray.NDArray: Divides this NDArray by the other NDArray element-wise.
div(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Divides this NDArray by the other NDArray element-wise.
div(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Divides a NDArray by a NDArray element-wise.
div(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Divides the NDArray by a number element-wise.
div(Number) - Method in interface ai.djl.ndarray.NDArray: Divides this NDArray by a number element-wise.
div(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Divides this NDArray by a number element-wise.
div(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Divides a number by a NDArray element-wise.
DivergenceCheckTrainingListener - Class in ai.djl.training.listener: TrainingListener that gives early warning if your training has failed by divergence.
DivergenceCheckTrainingListener() - Constructor for class ai.djl.training.listener.DivergenceCheckTrainingListener
divi(NDArray) - Method in interface ai.djl.ndarray.NDArray: Divides this NDArray by the other NDArray element-wise in place.
divi(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Divides this NDArray by the other NDArray element-wise in place.
divi(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Divides a NDArray by a NDArray element-wise.
divi(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Divides a number by a NDArray element-wise in place.
divi(Number) - Method in interface ai.djl.ndarray.NDArray: Divides this NDArray by a number element-wise in place.
divi(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Divides this NDArray by a number element-wise in place.
divi(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Divides a number by a NDArray element-wise.
dot(NDArray) - Method in interface ai.djl.ndarray.NDArray: Dot product of this NDArray and the other NDArray.
dot(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Dot product of this NDArray and the other NDArray.
dot(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Dot product of NDArray a and NDArray b.
download(String, String) - Static method in class ai.djl.training.util.DownloadUtils: Downloads a file from specified url.
download(String, String, Progress) - Static method in class ai.djl.training.util.DownloadUtils: Downloads a file from specified url.
download(URL, Path, Progress) - Static method in class ai.djl.training.util.DownloadUtils: Downloads a file from specified url.
download(Path, URI, Artifact.Item, Progress) - Method in class ai.djl.repository.AbstractRepository
download(Path, URI, Artifact.Item, Progress) - Method in class ai.djl.repository.JarRepository
download(Path, URI, Artifact.Item, Progress) - Method in class ai.djl.repository.SimpleRepository
download(Path, URI, Artifact.Item, Progress) - Method in class ai.djl.repository.SimpleUrlRepository
DownloadUtils - Class in ai.djl.training.util: A utility class downloads the file from specified url.
drawBoundingBoxes(DetectedObjects) - Method in interface ai.djl.modality.cv.Image: Draws the bounding boxes on the image.
drawJoints(Joints) - Method in interface ai.djl.modality.cv.Image: Draws all joints of a body on an image.
dropout(NDArray) - Static method in class ai.djl.nn.norm.Dropout: Applies Dropout to the input.
dropout(NDArray, float) - Static method in class ai.djl.nn.norm.Dropout: Applies Dropout to the input.
dropout(NDArray, float, boolean) - Static method in class ai.djl.nn.norm.Dropout: Applies Dropout to the input.
Dropout - Class in ai.djl.nn.norm: A dropout layer benefits a network by allowing some units (neurons), and hence their respective connections, of a network to be randomly and temporarily removed by setting its value to 0 only during training by specified probability \(p\), usually set to 0.5.
Dropout.Builder - Class in ai.djl.nn.norm: The Builder to construct a Dropout type of Block.
dropRate - Variable in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder
dropRate - Variable in class ai.djl.nn.recurrent.RecurrentBlock
dumpMemoryInfo(Metrics, String) - Static method in class ai.djl.training.listener.MemoryTrainingListener: Dump memory metrics into log directory.
duplicate() - Method in interface ai.djl.modality.cv.Image: Gets a deep copy of the original image.
duplicate() - Method in interface ai.djl.ndarray.NDArray: Returns a copy of this NDArray.

E

EasyHpo - Class in ai.djl.training.hyperparameter: Helper for easy training with hyperparameters.
EasyHpo() - Constructor for class ai.djl.training.hyperparameter.EasyHpo
EasyTrain - Class in ai.djl.training: Helper for easy training of a whole model, a trainining batch, or a validation batch.
ElasticNetWeightDecay - Class in ai.djl.training.loss: ElasticWeightDecay calculates L1+L2 penalty of a set of parameters.
ElasticNetWeightDecay(NDList) - Constructor for class ai.djl.training.loss.ElasticNetWeightDecay: Calculates Elastic Net weight decay for regularization.
ElasticNetWeightDecay(String, NDList) - Constructor for class ai.djl.training.loss.ElasticNetWeightDecay: Calculates Elastic Net weight decay for regularization.
ElasticNetWeightDecay(String, NDList, float) - Constructor for class ai.djl.training.loss.ElasticNetWeightDecay: Calculates Elastic Net weight decay for regularization.
ElasticNetWeightDecay(String, NDList, float, float) - Constructor for class ai.djl.training.loss.ElasticNetWeightDecay: Calculates Elastic Net weight decay for regularization.
elasticNetWeightedDecay(NDList) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of ElasticNetWeightDecay with default weight and name.
elasticNetWeightedDecay(String, float, float, NDList) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of ElasticNetWeightDecay.
elasticNetWeightedDecay(String, float, NDList) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of ElasticNetWeightDecay.
elasticNetWeightedDecay(String, NDList) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of ElasticNetWeightDecay with default weight.
elu(NDArray, float) - Static method in class ai.djl.nn.Activation: Applies ELU activation on the input NDArray.
elu(NDList, float) - Static method in class ai.djl.nn.Activation: Applies ELU(Exponential Linear Unit) activation on the input singleton NDList.
eluBlock(float) - Static method in class ai.djl.nn.Activation: Creates a LambdaBlock that applies the ELU activation function in its forward function.
embed(NDManager, Object[]) - Method in class ai.djl.nn.core.ConstantEmbedding: Embeds an array of items.
embed(NDManager, T[]) - Method in interface ai.djl.nn.core.AbstractEmbedding: Embeds an array of items.
embed(NDManager, T[]) - Method in class ai.djl.nn.core.Embedding.DefaultEmbedding: Embeds an array of items.
embed(NDManager, T[]) - Method in class ai.djl.nn.core.Embedding.DefaultItem: Embeds an array of items.
embed(NDManager, T[]) - Method in class ai.djl.nn.core.Embedding: Embeds an array of items.
embed(Object) - Method in class ai.djl.nn.core.ConstantEmbedding: Embeds an item.
embed(String) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Embeds an item.
embed(T) - Method in interface ai.djl.nn.core.AbstractIndexedEmbedding: Embeds an item.
embed(T) - Method in class ai.djl.nn.core.Embedding.DefaultEmbedding: Embeds an item.
embed(T) - Method in class ai.djl.nn.core.Embedding.DefaultItem: Embeds an item.
embedding - Variable in class ai.djl.nn.core.ConstantEmbedding
embedding - Variable in class ai.djl.nn.core.Embedding
embedding(NDArray, NDArray, SparseFormat) - Static method in class ai.djl.nn.core.Embedding: A simple lookup table that looks up embeddings in a fixed dictionary and size.
Embedding<T> - Class in ai.djl.nn.core: An Embedding block map a collection of items to 1-Dimensional representative NDArrays.
Embedding(NDArray) - Constructor for class ai.djl.nn.core.Embedding: Constructs a pretrained embedding.
Embedding(NDArray, SparseFormat) - Constructor for class ai.djl.nn.core.Embedding: Constructs a pretrained embedding.
Embedding(Embedding.BaseBuilder<T, ?>) - Constructor for class ai.djl.nn.core.Embedding
Embedding.BaseBuilder<T,B extends Embedding.BaseBuilder<T,B>> - Class in ai.djl.nn.core: The Builder to construct a Embedding type of Block.
Embedding.DefaultEmbedding - Class in ai.djl.nn.core
Embedding.DefaultItem - Class in ai.djl.nn.core
EmbeddingException - Exception in ai.djl.modality.nlp.embedding: Thrown to indicate that there was some error while loading embeddings.
EmbeddingException(String) - Constructor for exception ai.djl.modality.nlp.embedding.EmbeddingException: Constructs a new exception with the specified detail message.
EmbeddingException(String, Throwable) - Constructor for exception ai.djl.modality.nlp.embedding.EmbeddingException: Constructs a new exception with the specified detail message and cause.
EmbeddingException(Throwable) - Constructor for exception ai.djl.modality.nlp.embedding.EmbeddingException: Constructs a new exception with the specified cause and a detail message of (cause==null ? null : cause.toString()) which typically contains the class and detail message of cause.
embeddingSize - Variable in class ai.djl.nn.core.Embedding.BaseBuilder
embeddingSize - Variable in class ai.djl.nn.core.Embedding
embeddingType - Variable in class ai.djl.nn.core.Embedding.BaseBuilder
embedText(NDArray) - Method in class ai.djl.modality.nlp.embedding.ModelZooTextEmbedding: Embeds the text after preprocessed using TextEmbedding.preprocessTextToEmbed(List).
embedText(NDArray) - Method in class ai.djl.modality.nlp.embedding.SimpleTextEmbedding: Embeds the text after preprocessed using TextEmbedding.preprocessTextToEmbed(List).
embedText(NDArray) - Method in interface ai.djl.modality.nlp.embedding.TextEmbedding: Embeds the text after preprocessed using TextEmbedding.preprocessTextToEmbed(List).
embedText(NDArray) - Method in class ai.djl.modality.nlp.embedding.TrainableTextEmbedding: Embeds the text after preprocessed using TextEmbedding.preprocessTextToEmbed(List).
embedText(NDManager, long[]) - Method in interface ai.djl.modality.nlp.embedding.TextEmbedding: Embeds the text after preprocessed using TextEmbedding.preprocessTextToEmbed(List).
embedText(NDManager, List<String>) - Method in interface ai.djl.modality.nlp.embedding.TextEmbedding: Embeds a text.
embedWord(NDArray) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Embeds the word after preprocessed using WordEmbedding.preprocessWordToEmbed(String).
embedWord(NDArray) - Method in interface ai.djl.modality.nlp.embedding.WordEmbedding: Embeds the word after preprocessed using WordEmbedding.preprocessWordToEmbed(String).
embedWord(NDManager, long) - Method in interface ai.djl.modality.nlp.embedding.WordEmbedding: Embeds the word after preprocessed using WordEmbedding.preprocessWordToEmbed(String).
embedWord(NDManager, String) - Method in interface ai.djl.modality.nlp.embedding.WordEmbedding: Embeds a word.
encode() - Method in interface ai.djl.ndarray.NDArray: Encodes NDArray to byte array.
encode() - Method in class ai.djl.ndarray.NDList: Encodes the NDList to byte array.
encode(OutputStream) - Method in class ai.djl.ndarray.NDList: Writes the encoded NDList to OutputStream.
encode(OutputStream, boolean) - Method in class ai.djl.ndarray.NDList: Writes the encoded NDList to OutputStream.
encode(Object) - Method in class ai.djl.nn.core.ConstantEmbedding: Encodes an object of input type into a byte array.
encode(String) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Encodes an object of input type into a byte array.
encode(String, String) - Method in class ai.djl.modality.nlp.bert.BertTokenizer: Encodes questions and paragraph sentences.
encode(String, String, int) - Method in class ai.djl.modality.nlp.bert.BertTokenizer: Encodes questions and paragraph sentences with max length.
encode(T) - Method in interface ai.djl.nn.core.AbstractIndexedEmbedding: Encodes an object of input type into a byte array.
encode(T) - Method in class ai.djl.nn.core.Embedding.DefaultEmbedding: Encodes an object of input type into a byte array.
encode(T) - Method in class ai.djl.nn.core.Embedding.DefaultItem: Encodes an object of input type into a byte array.
encoder - Variable in class ai.djl.modality.nlp.EncoderDecoder
Encoder - Class in ai.djl.modality.nlp: Encoder is an abstract block that be can used as encoder in encoder-decoder architecture.
Encoder(byte, Block) - Constructor for class ai.djl.modality.nlp.Encoder: Constructs a new instance of Encoder with the given block.
EncoderDecoder - Class in ai.djl.modality.nlp: EncoderDecoder is a general implementation of the very popular encoder-decoder architecture.
EncoderDecoder(Encoder, Decoder) - Constructor for class ai.djl.modality.nlp.EncoderDecoder: Constructs a new instance of EncoderDecoder class with the given Encoder and Decoder.
end() - Method in class ai.djl.training.util.ProgressBar
Engine - Class in ai.djl.engine: The Engine interface is the base of the provided implementation for DJL.
Engine() - Constructor for class ai.djl.engine.Engine
EngineException - Exception in ai.djl.engine: Thrown to indicate that a native error is raised from the underlying Engine.
EngineException(String) - Constructor for exception ai.djl.engine.EngineException: Constructs a new exception with the specified detail message.
EngineException(String, Throwable) - Constructor for exception ai.djl.engine.EngineException: Constructs a new exception with the specified detail message and cause.
EngineException(Throwable) - Constructor for exception ai.djl.engine.EngineException: Constructs a new exception with the specified cause and a detail message of (cause==null ? null : cause.toString()) (which typically contains the class and detail message of cause).
EngineProvider - Interface in ai.djl.engine: The EngineProvider instance manufactures an Engine instance, which is available in the system.
EpochTrainingListener - Class in ai.djl.training.listener: EpochTrainingListener that tracks epochs.
EpochTrainingListener() - Constructor for class ai.djl.training.listener.EpochTrainingListener
EpsilonGreedy - Class in ai.djl.modality.rl.agent: The EpsilonGreedy is a simple exploration/excitation agent.
EpsilonGreedy(RlAgent, Tracker) - Constructor for class ai.djl.modality.rl.agent.EpsilonGreedy: Constructs an EpsilonGreedy.
eq(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Equals" comparison.
eq(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Equals" comparison.
eq(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Equals" comparison.
eq(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Equals" comparison.
eq(Number) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Equals" comparison.
eq(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Equals" comparison.
eq(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Equals" comparison.
equals(Object) - Method in class ai.djl.Application
equals(Object) - Method in class ai.djl.Device
equals(Object) - Method in class ai.djl.ndarray.types.Shape
equals(Object) - Method in class ai.djl.repository.Version
erfinv() - Method in interface ai.djl.ndarray.NDArray: Returns element-wise inverse gauss error function of the NDArray.
erfinv() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns element-wise inverse gauss error function of the NDArray.
erfinv(NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns element-wise inverse gauss error function of the input NDArray.
evaluate(NDList) - Method in class ai.djl.training.Trainer: Evaluates function of the model once on the given input NDList.
evaluate(NDList, NDList) - Method in class ai.djl.nn.transformer.BertMaskedLanguageModelLoss: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.nn.transformer.BertNextSentenceLoss: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.evaluator.AbstractAccuracy: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.evaluator.BoundingBoxError: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.evaluator.Evaluator: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.evaluator.IndexEvaluator: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.loss.AbstractCompositeLoss: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.loss.ElasticNetWeightDecay: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.loss.HingeLoss: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.loss.IndexLoss: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.loss.L1Loss: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.loss.L1WeightDecay: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.loss.L2Loss: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.loss.L2WeightDecay: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.loss.MaskedSoftmaxCrossEntropyLoss: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.loss.SigmoidBinaryCrossEntropyLoss: Calculates the evaluation between the labels and the predictions.
evaluate(NDList, NDList) - Method in class ai.djl.training.loss.SoftmaxCrossEntropyLoss: Calculates the evaluation between the labels and the predictions.
evaluateDataset(Trainer, Dataset) - Static method in class ai.djl.training.EasyTrain: Evaluates the test dataset.
Evaluator - Class in ai.djl.training.evaluator: Base class for all Evaluators that can be used to evaluate the performance of a model.
Evaluator(String) - Constructor for class ai.djl.training.evaluator.Evaluator: Creates an evaluator with abstract update methods.
EvaluatorTrainingListener - Class in ai.djl.training.listener: TrainingListener that records evaluator results.
EvaluatorTrainingListener() - Constructor for class ai.djl.training.listener.EvaluatorTrainingListener: Constructs an EvaluatorTrainingListener that updates the training progress the default frequency.
EvaluatorTrainingListener(int) - Constructor for class ai.djl.training.listener.EvaluatorTrainingListener: Constructs an EvaluatorTrainingListener that updates the training progress the given frequency.
exp() - Method in interface ai.djl.ndarray.NDArray: Returns the exponential value of this NDArray element-wise.
exp() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the exponential value of this NDArray element-wise.
expandDims(int) - Method in interface ai.djl.ndarray.NDArray: Expands the Shape of a NDArray.
expandDims(int) - Method in class ai.djl.ndarray.NDArrayAdapter: Expands the Shape of a NDArray.
eye(int) - Method in interface ai.djl.ndarray.NDManager: Returns a 2-D array with ones on the diagonal and zeros elsewhere.
eye(int, int) - Method in interface ai.djl.ndarray.NDManager: Returns a 2-D array with ones on the diagonal and zeros elsewhere.
eye(int, int, int) - Method in interface ai.djl.ndarray.NDManager: Returns a 2-D array with ones on the diagonal and zeros elsewhere.
eye(int, int, int, DataType) - Method in class ai.djl.ndarray.BaseNDManager: Returns a 2-D array with ones on the diagonal and zeros elsewhere.
eye(int, int, int, DataType) - Method in interface ai.djl.ndarray.NDManager: Returns a 2-D array with ones on the diagonal and zeros elsewhere.
eye(int, int, int, DataType, Device) - Method in interface ai.djl.ndarray.NDManager: Returns a 2-D array with ones on the diagonal and zeros elsewhere.

F

factor() - Static method in interface ai.djl.training.tracker.Tracker: Returns a new instance of FactorTracker.Builder that can build an FactorTracker.
FactorTracker - Class in ai.djl.training.tracker: FactorTracker is an implementation of Tracker which is updated by a multiplicative factor.
FactorTracker(FactorTracker.Builder) - Constructor for class ai.djl.training.tracker.FactorTracker: Creates a new instance of FactorTracker.
FactorTracker.Builder - Class in ai.djl.training.tracker: The Builder to construct an FactorTracker object.
fallthrough - Variable in class ai.djl.nn.core.Embedding.BaseBuilder
fallthroughEmbedding - Variable in class ai.djl.nn.core.Embedding
FilenameUtils - Class in ai.djl.repository: A class containing utility methods.
FileTranslator<T> - Class in ai.djl.modality.cv.translator.wrapper: Built-in Translator that provides image pre-processing from file path.
FileTranslator(Translator<Image, T>) - Constructor for class ai.djl.modality.cv.translator.wrapper.FileTranslator: Creates a FileTranslator instance.
filterByLayoutType(Predicate<LayoutType>) - Method in class ai.djl.ndarray.types.Shape: Returns only the axes of the Shape whose layout types match the predicate.
filters - Variable in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder
filters - Variable in class ai.djl.nn.convolutional.Convolution
filters - Variable in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder
filters - Variable in class ai.djl.nn.convolutional.Deconvolution
finalize() - Method in class ai.djl.BaseModel
finalize() - Method in class ai.djl.inference.Predictor
finalize() - Method in class ai.djl.training.Trainer
fit() - Method in class ai.djl.training.hyperparameter.EasyHpo: Fits the model given the implemented abstract methods.
fit(NDArray) - Method in class ai.djl.training.util.MinMaxScaler: Computes the minimum and maximum to be used for later scaling.
fit(NDArray, int[]) - Method in class ai.djl.training.util.MinMaxScaler: Computes the minimum and maximum to be used for later scaling.
fit(Trainer, int, Dataset, Dataset) - Static method in class ai.djl.training.EasyTrain: Runs a basic epoch training experience with a given trainer.
fixed(float) - Static method in interface ai.djl.training.tracker.Tracker: Returns a new instance of Tracker with a fixed value.
flag - Variable in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder
flatten() - Method in interface ai.djl.ndarray.NDArray: Flattens this NDArray into a 1-D NDArray in row-major order.
flatten() - Method in class ai.djl.ndarray.NDArrayAdapter: Flattens this NDArray into a 1-D NDArray in row-major order.
flip(int...) - Method in interface ai.djl.ndarray.NDArray: Returns the reverse order of elements in an array along the given axis.
flip(int...) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the reverse order of elements in an array along the given axis.
FLOAT16 - ai.djl.ndarray.types.DataType
FLOAT32 - ai.djl.ndarray.types.DataType
FLOAT64 - ai.djl.ndarray.types.DataType
FLOATING - ai.djl.ndarray.types.DataType.Format
floatValue(Map<String, ?>, String) - Static method in class ai.djl.translate.ArgumentsUtil: Returns the float value from the arguments.
floatValue(Map<String, ?>, String, float) - Static method in class ai.djl.translate.ArgumentsUtil: Returns the float value from the arguments.
floor() - Method in interface ai.djl.ndarray.NDArray: Returns the floor of this NDArray element-wise.
floor() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the floor of this NDArray element-wise.
forward(NDList) - Method in class ai.djl.training.Trainer: Applies the forward function of the model once on the given input NDList.
forward(NDList, NDList) - Method in class ai.djl.training.Trainer: Applies the forward function of the model once with both data and labels.
forward(ParameterStore, NDList, boolean) - Method in interface ai.djl.nn.Block: Applies the operating function of the block once.
forward(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.AbstractBaseBlock: Applies the operating function of the block once.
forward(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in interface ai.djl.nn.Block: Applies the operating function of the block once.
forward(ParameterStore, NDList, NDList, PairList<String, Object>) - Method in class ai.djl.modality.nlp.EncoderDecoder: A forward call using both training data and labels.
forward(ParameterStore, NDList, NDList, PairList<String, Object>) - Method in class ai.djl.nn.AbstractBaseBlock: A forward call using both training data and labels.
forward(ParameterStore, NDList, NDList, PairList<String, Object>) - Method in interface ai.djl.nn.Block: A forward call using both training data and labels.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.modality.nlp.Decoder: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.modality.nlp.embedding.TrainableTextEmbedding: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.modality.nlp.Encoder: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.modality.nlp.EncoderDecoder: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.AbstractBaseBlock: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.convolutional.Convolution: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.convolutional.Deconvolution: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.core.ConstantEmbedding: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.core.Embedding: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.core.Linear: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.core.Prelu: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.LambdaBlock: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.norm.BatchNorm: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.norm.Dropout: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.norm.LayerNorm: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.ParallelBlock: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.recurrent.GRU: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.recurrent.LSTM: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.recurrent.RNN: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.SequentialBlock: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.transformer.BertBlock: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.transformer.BertMaskedLanguageModelBlock: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.transformer.BertNextSentenceBlock: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.transformer.BertPretrainingBlock: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.transformer.IdEmbedding: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, boolean, PairList<String, Object>) - Method in class ai.djl.nn.transformer.TransformerEncoderBlock: A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
forwardInternal(ParameterStore, NDList, NDList, PairList<String, Object>) - Method in class ai.djl.modality.nlp.Encoder
forwardInternal(ParameterStore, NDList, NDList, PairList<String, Object>) - Method in class ai.djl.nn.AbstractBaseBlock: A helper for Block.forward(ParameterStore, NDList, NDList, PairList) after initialization.
forwardInternal(ParameterStore, NDList, NDList, PairList<String, Object>) - Method in class ai.djl.nn.ParallelBlock: A helper for Block.forward(ParameterStore, NDList, NDList, PairList) after initialization.
forwardInternal(ParameterStore, NDList, NDList, PairList<String, Object>) - Method in class ai.djl.nn.SequentialBlock: A helper for Block.forward(ParameterStore, NDList, NDList, PairList) after initialization.
freeze(boolean) - Method in class ai.djl.nn.Parameter: Freezes or unfreezes the parameter for training.
freezeParameters(boolean) - Method in interface ai.djl.nn.Block: Freezes or unfreezes all parameters inside the block for training.
from(NDArray) - Method in interface ai.djl.ndarray.NDManager: Creates a new NDArray if the input NDArray is from external engine.
fromBuffer(Buffer) - Static method in enum ai.djl.ndarray.types.DataType: Returns the data type to use for a data buffer.
fromDeviceType(int) - Static method in interface ai.djl.DeviceType: Map device to its type number.
fromFile(Path) - Method in class ai.djl.modality.cv.BufferedImageFactory: Gets Image from file.
fromFile(Path) - Method in class ai.djl.modality.cv.ImageFactory: Gets Image from file.
fromImage(Object) - Method in class ai.djl.modality.cv.BufferedImageFactory: Gets Image from varies Java image types.
fromImage(Object) - Method in class ai.djl.modality.cv.ImageFactory: Gets Image from varies Java image types.
fromIndex(NDIndex, Shape) - Static method in class ai.djl.ndarray.index.full.NDIndexFullPick: Returns (if possible) the NDIndexFullPick representation of an NDIndex.
fromIndex(NDIndex, Shape) - Static method in class ai.djl.ndarray.index.full.NDIndexFullSlice: Returns (if possible) the NDIndexFullSlice representation of an NDIndex.
fromInputStream(InputStream) - Method in class ai.djl.modality.cv.BufferedImageFactory: Gets Image from InputStream.
fromInputStream(InputStream) - Method in class ai.djl.modality.cv.ImageFactory: Gets Image from InputStream.
fromName(String) - Static method in class ai.djl.Device: Parses a deviceName string into a device for the default engine.
fromName(String, Engine) - Static method in class ai.djl.Device: Parses a deviceName string into a device.
fromNDArray(NDArray) - Method in class ai.djl.modality.cv.BufferedImageFactory: Gets Image from NDArray.
fromNDArray(NDArray) - Method in class ai.djl.modality.cv.ImageFactory: Gets Image from NDArray.
fromNumpy(String) - Static method in enum ai.djl.ndarray.types.DataType: Returns the data type from numpy value.
fromString(String) - Static method in interface ai.djl.translate.Batchifier: Returns a batchifier from a batchifier name.
fromUrl(String) - Method in class ai.djl.modality.cv.ImageFactory: Gets Image from URL.
fromUrl(URL) - Method in class ai.djl.modality.cv.ImageFactory: Gets Image from URL.
fromValue(char) - Static method in enum ai.djl.ndarray.types.LayoutType: Converts the character to the matching layout type.
fromValue(int) - Static method in enum ai.djl.ndarray.types.SparseFormat: Gets the SparseFormat from it's integer value.
fromValue(String) - Static method in enum ai.djl.metric.Unit: Returns Unit instance from an string value.
fromValue(String) - Static method in enum ai.djl.ndarray.types.LayoutType: Converts each character to the matching layout type.
full(Shape, float) - Method in interface ai.djl.ndarray.NDManager: Return a new NDArray of given shape, filled with value.
full(Shape, float, DataType) - Method in class ai.djl.ndarray.BaseNDManager: Return a new NDArray of given shape, filled with value.
full(Shape, float, DataType) - Method in interface ai.djl.ndarray.NDManager: Return a new NDArray of given shape, filled with value.
full(Shape, float, DataType, Device) - Method in interface ai.djl.ndarray.NDManager: Return a new NDArray of given shape, device, filled with value.
full(Shape, int) - Method in interface ai.djl.ndarray.NDManager: Return a new NDArray of given shape, filled with value.

G

GAMMA - ai.djl.nn.Parameter.Type
gates - Variable in class ai.djl.nn.recurrent.RecurrentBlock
gather(NDArray, int) - Method in interface ai.djl.ndarray.NDArray: Returns a partial NDArray pointed by the indexed array.
gather(NDArray, int) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns a partial NDArray pointed by the indexed array.
gatherFromIndices(NDArray, NDArray) - Static method in class ai.djl.nn.transformer.BertMaskedLanguageModelBlock: Given a 3D array of shape (B, S, E) and a 2D array of shape (B, I) returns the flattened lookup result of shape (B * I * E).
gatherNd(NDArray, NDArray) - Static method in class ai.djl.nn.transformer.MissingOps: Applies the mxnet gather_nd operator.
GAUSSIAN - ai.djl.training.initializer.XavierInitializer.RandomType
gelu(NDArray) - Static method in class ai.djl.nn.Activation: Applies GELU(Gaussian Error Linear Unit) activation on the input NDArray.
gelu(NDList) - Static method in class ai.djl.nn.Activation: Applies GELU(Gaussian Error Linear Unit) activation on the input singleton NDList.
geluBlock() - Static method in class ai.djl.nn.Activation: Creates a LambdaBlock that applies the GELU activation function in its forward function.
generateAnchorBoxes(NDArray) - Method in class ai.djl.modality.cv.MultiBoxPrior: Generates the anchorBoxes array in the input's manager and device.
get(int) - Method in class ai.djl.modality.Input: Returns the element at the specified position in the Input.
get(int) - Method in class ai.djl.ndarray.index.NDIndex: Returns the index affecting the given dimension.
get(int) - Method in class ai.djl.ndarray.types.Shape: Returns the shape in the given dimension.
get(long...) - Method in interface ai.djl.ndarray.NDArray: Returns a partial NDArray.
get(NDIndex) - Method in interface ai.djl.ndarray.NDArray: Returns a partial NDArray.
get(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns a partial NDArray.
get(NDArray, NDIndexFullPick) - Method in class ai.djl.ndarray.index.NDArrayIndexer: Returns a subarray by picking the elements.
get(NDArray, NDIndexFullSlice) - Method in class ai.djl.ndarray.index.NDArrayIndexer: Returns a subarray at the slice.
get(NDArray, NDIndex) - Method in class ai.djl.ndarray.index.NDArrayIndexer: Returns a subarray at the given index.
get(NDManager) - Method in interface ai.djl.translate.NDArraySupplier: Gets an NDArray from the given NDManager.
get(NDManager, long) - Method in class ai.djl.training.dataset.ArrayDataset: Gets the Record for the given index from the dataset.
get(NDManager, long) - Method in class ai.djl.training.dataset.RandomAccessDataset: Gets the Record for the given index from the dataset.
get(String) - Method in class ai.djl.modality.Classifications: Returns the result for a particular class name.
get(String) - Method in class ai.djl.modality.Input: Returns the element for the first key found in the Input.
get(String) - Method in class ai.djl.ndarray.NDList: Returns the first occurrence of the specified element from this NDList if it is present.
get(String, Object...) - Method in interface ai.djl.ndarray.NDArray: Returns a partial NDArray.
getAccumulator(String) - Method in class ai.djl.training.evaluator.AbstractAccuracy: Returns the accumulated evaluator value.
getAccumulator(String) - Method in class ai.djl.training.evaluator.BoundingBoxError: Returns the accumulated evaluator value.
getAccumulator(String) - Method in class ai.djl.training.evaluator.Evaluator: Returns the accumulated evaluator value.
getAccumulator(String) - Method in class ai.djl.training.evaluator.IndexEvaluator: Returns the accumulated evaluator value.
getAccumulator(String) - Method in class ai.djl.training.loss.AbstractCompositeLoss: Returns the accumulated evaluator value.
getAccumulator(String) - Method in class ai.djl.training.loss.Loss: Returns the accumulated evaluator value.
getAction() - Method in interface ai.djl.modality.rl.env.RlEnv.Step: Returns the action taken.
getActionSpace() - Method in interface ai.djl.modality.rl.env.RlEnv: Returns the current actions that can be taken in the environment.
getAllEngines() - Static method in class ai.djl.engine.Engine: Returns a set of engine names that are loaded.
getAlternativeEngine() - Method in class ai.djl.engine.Engine: Returns the alternative engine if available.
getApplication() - Method in class ai.djl.repository.Metadata: Returns the Application.
getApplication() - Method in class ai.djl.repository.MRL: Returns the application.
getApplication() - Method in class ai.djl.repository.zoo.BaseModelLoader: Returns the application of the ModelLoader.
getApplication() - Method in class ai.djl.repository.zoo.Criteria: Returns the application of the model.
getApplication() - Method in interface ai.djl.repository.zoo.ModelLoader: Returns the application of the ModelLoader.
getArguments() - Method in class ai.djl.repository.Artifact: Returns the artifact arguments.
getArguments() - Method in class ai.djl.repository.zoo.Criteria: Returns the override configurations of the model loading arguments.
getArguments(Map<String, Object>) - Method in class ai.djl.repository.Artifact: Returns the artifact arguments.
getArray() - Method in class ai.djl.nn.Parameter: Gets the values of this Parameter as an NDArray.
getArtifact() - Method in class ai.djl.repository.Artifact.Item: Returns the artifact associated with this item.
getArtifact(String) - Method in class ai.djl.BaseModel: Finds an artifact resource with a given name in the model.
getArtifact(String) - Method in interface ai.djl.Model: Finds an artifact resource with a given name in the model.
getArtifact(String) - Method in class ai.djl.repository.zoo.ZooModel: Finds an artifact resource with a given name in the model.
getArtifact(String, Function<InputStream, T>) - Method in class ai.djl.BaseModel: Attempts to load the artifact using the given function and cache it if the specified artifact is not already cached.
getArtifact(String, Function<InputStream, T>) - Method in interface ai.djl.Model: Attempts to load the artifact using the given function and cache it if the specified artifact is not already cached.
getArtifact(String, Function<InputStream, T>) - Method in class ai.djl.repository.zoo.ZooModel: Attempts to load the artifact using the given function and cache it if the specified artifact is not already cached.
getArtifactAsStream(String) - Method in class ai.djl.BaseModel: Finds an artifact resource with a given name in the model.
getArtifactAsStream(String) - Method in interface ai.djl.Model: Finds an artifact resource with a given name in the model.
getArtifactAsStream(String) - Method in class ai.djl.repository.zoo.ZooModel: Finds an artifact resource with a given name in the model.
getArtifactId() - Method in class ai.djl.repository.Metadata: Returns the artifactId.
getArtifactId() - Method in class ai.djl.repository.MRL: Returns the artifactId.
getArtifactId() - Method in class ai.djl.repository.zoo.BaseModelLoader: Returns the artifact ID of the ModelLoader.
getArtifactId() - Method in class ai.djl.repository.zoo.Criteria: Returns the artifactId of the ModelLoader to be searched.
getArtifactId() - Method in interface ai.djl.repository.zoo.ModelLoader: Returns the artifact ID of the ModelLoader.
getArtifactNames() - Method in class ai.djl.BaseModel: Returns the artifact names associated with the model.
getArtifactNames() - Method in interface ai.djl.Model: Returns the artifact names associated with the model.
getArtifactNames() - Method in class ai.djl.repository.zoo.ZooModel: Returns the artifact names associated with the model.
getArtifacts() - Method in class ai.djl.repository.Metadata: Returns all the artifacts in the metadata.
getAsBytes() - Method in interface ai.djl.ndarray.BytesSupplier: Returns the byte[] presentation of the object.
getAsBytes() - Method in class ai.djl.ndarray.NDList: Returns the byte[] presentation of the object.
getAsBytes(int) - Method in class ai.djl.modality.Input: Returns the value as byte[] at the specified position in the Input.
getAsBytes(String) - Method in class ai.djl.modality.Input: Returns the value as byte[] for the first key found in the Input.
getAsNDArray(NDManager, int) - Method in class ai.djl.modality.Input: Returns the value as NDArray at the specified position in the Input.
getAsNDArray(NDManager, String) - Method in class ai.djl.modality.Input: Returns the value as NDArray for the first key found in the Input.
getAsNDList(NDManager, int) - Method in class ai.djl.modality.Input: Returns the value as NDList at the specified position in the Input.
getAsNDList(NDManager, String) - Method in class ai.djl.modality.Input: Returns the value as NDList for the first key found in the Input.
getAsObject() - Method in interface ai.djl.ndarray.BytesSupplier: Returns the object that backs this BytesSupplier.
getAsString() - Method in class ai.djl.modality.Classifications: Returns the String presentation of the object.
getAsString() - Method in interface ai.djl.ndarray.BytesSupplier: Returns the String presentation of the object.
getAsString(int) - Method in class ai.djl.modality.Input: Returns the value as byte[] at the specified position in the Input.
getAsString(String) - Method in class ai.djl.modality.Input: Returns the value as byte[] for the first key found in the Input.
getAttachment(String) - Method in interface ai.djl.translate.TranslatorContext: Returns value of attached key-value pair to context.
getAttentionMask() - Method in class ai.djl.modality.nlp.bert.BertToken: Gets the mask to avoid performing attention on padding token indices.
getAxis() - Method in class ai.djl.ndarray.index.full.NDIndexFullPick: Returns the axis to pick.
getBaseUri() - Method in class ai.djl.repository.AbstractRepository: Returns the URI to the base of the repository.
getBaseUri() - Method in interface ai.djl.repository.Repository: Returns the URI to the base of the repository.
getBaseUri() - Method in class ai.djl.repository.SimpleRepository: Returns the URI to the base of the repository.
getBatch() - Method in interface ai.djl.modality.rl.env.RlEnv: Returns a batch of steps from the environment ReplayBuffer.
getBatch() - Method in class ai.djl.modality.rl.LruReplayBuffer: Returns a batch of steps from this buffer.
getBatch() - Method in interface ai.djl.modality.rl.ReplayBuffer: Returns a batch of steps from this buffer.
getBatch() - Method in class ai.djl.training.listener.TrainingListener.BatchData: Returns the original batch.
getBatchifier() - Method in class ai.djl.modality.cv.translator.BaseImageTranslator: Gets the Batchifier.
getBatchifier() - Method in class ai.djl.modality.cv.translator.ImageServingTranslator: Gets the Batchifier.
getBatchifier() - Method in class ai.djl.modality.cv.translator.wrapper.FileTranslator: Gets the Batchifier.
getBatchifier() - Method in class ai.djl.modality.cv.translator.wrapper.InputStreamTranslator: Gets the Batchifier.
getBatchifier() - Method in class ai.djl.modality.cv.translator.wrapper.UrlTranslator: Gets the Batchifier.
getBatchifier() - Method in class ai.djl.modality.nlp.translator.QaServingTranslator: Gets the Batchifier.
getBatchifier() - Method in class ai.djl.modality.nlp.translator.QATranslator: Gets the Batchifier.
getBatchifier() - Method in class ai.djl.modality.nlp.translator.SimpleText2TextTranslator: Gets the Batchifier.
getBatchifier() - Method in class ai.djl.modality.nlp.translator.TextClassificationServingTranslator: Gets the Batchifier.
getBatchifier() - Method in interface ai.djl.translate.NoBatchifyTranslator: Gets the Batchifier.
getBatchifier() - Method in class ai.djl.translate.NoopTranslator: Gets the Batchifier.
getBatchifier() - Method in interface ai.djl.translate.Translator: Gets the Batchifier.
getBatchSize() - Method in class ai.djl.training.dataset.BatchSampler: Returns the batch size of the Sampler.
getBatchSize() - Method in interface ai.djl.training.dataset.Sampler: Returns the batch size of the Sampler.
getBertMaskedLanguageModelLoss() - Method in class ai.djl.nn.transformer.BertPretrainingLoss: gets BertMaskedLanguageModelLoss.
getBertNextSentenceLoss() - Method in class ai.djl.nn.transformer.BertPretrainingLoss: gets BertNextSentenceLoss.
getBest() - Method in class ai.djl.training.hyperparameter.optimizer.BaseHpOptimizer: Returns the best hyperparameters and loss.
getBest() - Method in interface ai.djl.training.hyperparameter.optimizer.HpOptimizer: Returns the best hyperparameters and loss.
getBlock() - Method in class ai.djl.BaseModel: Gets the block from the Model.
getBlock() - Method in interface ai.djl.Model: Gets the block from the Model.
getBlock() - Method in class ai.djl.repository.zoo.Criteria: Returns the optional Block to be used for ZooModel.
getBlock() - Method in class ai.djl.repository.zoo.ZooModel: Gets the block from the Model.
getBlock() - Method in interface ai.djl.translate.TranslatorContext: Returns the block from the TranslatorContext.
getBoolean(long...) - Method in interface ai.djl.ndarray.NDArray: Returns a boolean element from this NDArray.
getBoundingBox() - Method in class ai.djl.modality.cv.output.DetectedObjects.DetectedObject: Returns the BoundingBox of the detected object.
getBounds() - Method in interface ai.djl.modality.cv.output.BoundingBox: Returns the bounding Rectangle of this BoundingBox.
getBounds() - Method in class ai.djl.modality.cv.output.Rectangle: Returns the bounding Rectangle of this BoundingBox.
getByte(long...) - Method in interface ai.djl.ndarray.NDArray: Returns an byte element from this NDArray.
getCacheDirectory() - Method in class ai.djl.repository.AbstractRepository: Returns the cache directory for the repository.
getCacheDirectory() - Method in interface ai.djl.repository.Repository: Returns the cache directory for the repository.
getCacheDirectory() - Method in class ai.djl.repository.SimpleRepository: Returns the cache directory for the repository.
getCheckpoint() - Method in class ai.djl.training.listener.SaveModelTrainingListener: Returns the checkpoint frequency (or -1 for no checkpointing) in SaveModelTrainingListener.
getChildren() - Method in class ai.djl.nn.AbstractBlock: Returns a list of all the children of the block.
getChildren() - Method in class ai.djl.nn.AbstractSymbolBlock: Returns a list of all the children of the block.
getChildren() - Method in interface ai.djl.nn.Block: Returns a list of all the children of the block.
getClassName() - Method in class ai.djl.modality.Classifications.Classification: Returns the class name.
getCode() - Method in class ai.djl.modality.Output: Returns the status code of the output.
getComponents() - Method in class ai.djl.training.loss.AbstractCompositeLoss: Returns the component losses that make up the composite loss.
getConfidence() - Method in class ai.djl.modality.cv.output.Joints.Joint: Returns the confidence probability for the joint.
getContent() - Method in class ai.djl.modality.Input: Returns the content of the input.
getData() - Method in class ai.djl.modality.Input: Returns the default data item.
getData() - Method in class ai.djl.training.dataset.Batch: Gets the data of this Batch.
getData() - Method in class ai.djl.training.dataset.Record: Gets the data of this Record.
getData(NDManager) - Method in interface ai.djl.training.dataset.Dataset: Fetches an iterator that can iterate through the Dataset.
getData(NDManager) - Method in class ai.djl.training.dataset.RandomAccessDataset: Fetches an iterator that can iterate through the Dataset.
getData(NDManager, Sampler) - Method in class ai.djl.training.dataset.RandomAccessDataset: Fetches an iterator that can iterate through the Dataset with a custom sampler.
getData(NDManager, Sampler, ExecutorService) - Method in class ai.djl.training.dataset.RandomAccessDataset: Fetches an iterator that can iterate through the Dataset with a custom sampler multi-threaded.
getData(NDManager, ExecutorService) - Method in interface ai.djl.training.dataset.Dataset: Fetches an iterator that can iterate through the Dataset with multiple threads.
getData(NDManager, ExecutorService) - Method in class ai.djl.training.dataset.RandomAccessDataset: Fetches an iterator that can iterate through the Dataset with multiple threads.
getDataAsNDList(NDManager) - Method in class ai.djl.modality.Input: Returns the default data as NDList.
getDataset(Dataset.Usage) - Method in class ai.djl.training.hyperparameter.EasyHpo: Returns the dataset to train with.
getDataType() - Method in class ai.djl.BaseModel: Returns the standard data type used within the model.
getDataType() - Method in interface ai.djl.Model: Returns the standard data type used within the model.
getDataType() - Method in interface ai.djl.ndarray.NDArray: Returns the DataType of this NDArray.
getDataType() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the DataType of this NDArray.
getDataType() - Method in class ai.djl.ndarray.types.DataDesc: Returns the DataType of the NDArray.
getDataType() - Method in class ai.djl.repository.zoo.ZooModel: Returns the standard data type used within the model.
getDefaultArtifact() - Method in class ai.djl.repository.MRL: Returns the default artifact.
getDefaultEngineName() - Static method in class ai.djl.engine.Engine: Returns the default Engine name.
getDescription() - Method in class ai.djl.repository.Metadata: Returns the description.
getDevice() - Method in class ai.djl.ndarray.BaseNDManager: Returns the default Device of this NDManager.
getDevice() - Method in interface ai.djl.ndarray.NDArray: Returns the Device of this NDArray.
getDevice() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the Device of this NDArray.
getDevice() - Method in interface ai.djl.ndarray.NDManager: Returns the default Device of this NDManager.
getDevice() - Method in class ai.djl.repository.zoo.Criteria: Returns the Device of the model to be loaded on.
getDeviceId() - Method in class ai.djl.Device: Returns the deviceId of the Device.
getDevices() - Method in class ai.djl.engine.Engine: Returns an array of devices.
getDevices() - Method in class ai.djl.training.DefaultTrainingConfig: Gets the Device that are available for computation.
getDevices() - Method in class ai.djl.training.Trainer: Returns the devices used for training.
getDevices() - Method in interface ai.djl.training.TrainingConfig: Gets the Device that are available for computation.
getDevices(int) - Method in class ai.djl.engine.Engine: Returns an array of devices given the maximum number of GPUs to use.
getDeviceType() - Method in class ai.djl.Device: Returns the device type of the Device.
getDimensions() - Method in class ai.djl.metric.Metric: Returns the metric dimensions.
getDirectParameters() - Method in class ai.djl.nn.AbstractBlock: Returns a list of all the direct parameters of the block.
getDirectParameters() - Method in interface ai.djl.nn.Block: Returns a list of all the direct parameters of the block.
getDouble(long...) - Method in interface ai.djl.ndarray.NDArray: Returns a double element from this NDArray.
getEllipsisIndex() - Method in class ai.djl.ndarray.index.NDIndex: Returns the index of the ellipsis.
getEmbeddingSize() - Method in class ai.djl.nn.transformer.BertBlock: Returns the embedding size used for tokens.
getEmbeddingType() - Method in class ai.djl.nn.core.Embedding.BaseBuilder: Returns the embedded type.
getEncoded() - Method in class ai.djl.ndarray.types.Shape: Gets the byte array representation of this Shape for serialization.
getEngine() - Method in interface ai.djl.engine.EngineProvider: Returns the instance of the Engine class EngineProvider should bind to.
getEngine() - Method in interface ai.djl.ndarray.NDManager: Returns the Engine associated with this manager.
getEngine() - Method in class ai.djl.repository.zoo.Criteria: Returns the engine name.
getEngine(String) - Static method in class ai.djl.engine.Engine: Returns the Engine with the given name.
getEngineName() - Method in class ai.djl.engine.Engine: Returns the name of the Engine.
getEngineName() - Method in interface ai.djl.engine.EngineProvider: Returns the name of the Engine.
getEngineRank() - Method in interface ai.djl.engine.EngineProvider: Returns the rank of the Engine.
getEpoch() - Method in class ai.djl.training.TrainingResult: Returns the actual number of epoch.
getEvaluations() - Method in class ai.djl.training.TrainingResult: Returns the raw evaluation metrics.
getEvaluators() - Method in class ai.djl.training.DefaultTrainingConfig: Returns the list of Evaluators that should be computed during training.
getEvaluators() - Method in class ai.djl.training.Trainer: Gets all Evaluators.
getEvaluators() - Method in interface ai.djl.training.TrainingConfig: Returns the list of Evaluators that should be computed during training.
getExecutorService() - Method in class ai.djl.training.DefaultTrainingConfig: Gets the ExecutorService for parallelization.
getExecutorService() - Method in class ai.djl.training.Trainer: Returns the ExecutorService.
getExecutorService() - Method in interface ai.djl.training.TrainingConfig: Gets the ExecutorService for parallelization.
getExpectedLayout() - Method in class ai.djl.nn.convolutional.Conv1d: Returns the expected layout of the input.
getExpectedLayout() - Method in class ai.djl.nn.convolutional.Conv1dTranspose: Returns the expected layout of the input.
getExpectedLayout() - Method in class ai.djl.nn.convolutional.Conv2d: Returns the expected layout of the input.
getExpectedLayout() - Method in class ai.djl.nn.convolutional.Conv2dTranspose: Returns the expected layout of the input.
getExpectedLayout() - Method in class ai.djl.nn.convolutional.Conv3d: Returns the expected layout of the input.
getExpectedLayout() - Method in class ai.djl.nn.convolutional.Convolution: Returns the expected layout of the input.
getExpectedLayout() - Method in class ai.djl.nn.convolutional.Deconvolution: Returns the expected layout of the input.
getExtension() - Method in class ai.djl.repository.Artifact.Item: Returns the type of file extension.
getFile(Artifact.Item, String) - Method in class ai.djl.repository.AbstractRepository: Returns the path to a file for the item.
getFile(Artifact.Item, String) - Method in interface ai.djl.repository.Repository: Returns the path to a file for the item.
getFileExtension(String) - Static method in class ai.djl.repository.FilenameUtils: Returns the file name extension of the file.
getFiles() - Method in class ai.djl.repository.Artifact: Returns all the file items in the artifact.
getFileType(String) - Static method in class ai.djl.repository.FilenameUtils: Returns the type of the file.
getFilters() - Method in class ai.djl.repository.zoo.Criteria: Returns the search filters that must match the properties of the model.
getFloat(long...) - Method in interface ai.djl.ndarray.NDArray: Returns a float element from this NDArray.
getFormat() - Method in enum ai.djl.ndarray.types.DataType: Returns the format of the data type.
getGpuCount() - Method in class ai.djl.engine.Engine: Returns the number of GPUs available in the system.
getGradient() - Method in interface ai.djl.ndarray.NDArray: Returns the gradient NDArray attached to this NDArray.
getGradient() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the gradient NDArray attached to this NDArray.
getGroupId() - Method in class ai.djl.repository.Metadata: Returns the groupId.
getGroupId() - Method in class ai.djl.repository.MRL: Returns the groupId.
getGroupId() - Method in class ai.djl.repository.zoo.Criteria: Returns the groupId of the ModelZoo to be searched.
getGroupId() - Method in class ai.djl.repository.zoo.DefaultModelZoo: Returns the global unique identifier of the ModelZoo.
getGroupId() - Method in class ai.djl.repository.zoo.ModelZoo: Returns the global unique identifier of the ModelZoo.
getHeight() - Method in interface ai.djl.modality.cv.Image: Gets the height of the image.
getHeight() - Method in class ai.djl.modality.cv.output.Rectangle: Returns the height of the Rectangle.
getHParam(String) - Method in class ai.djl.training.hyperparameter.param.HpSet: Returns the hyperparameter in the set with the given name.
getId() - Method in class ai.djl.nn.Parameter: Gets the ID of this Parameter.
getId() - Method in class ai.djl.repository.License: Returns the identifier of the license.
getImageHeight() - Method in class ai.djl.modality.cv.translator.ObjectDetectionTranslator.ObjectDetectionBuilder: Get resized image height.
getImageWidth() - Method in class ai.djl.modality.cv.translator.ObjectDetectionTranslator.ObjectDetectionBuilder: Get resized image width.
getIncrementalVersion() - Method in class ai.djl.repository.Version: Returns the incremental version (assuming major.minor.incremental...) of the version.
getIndex() - Method in class ai.djl.ndarray.index.dim.NDIndexBooleans: Returns the mask binary NDArray.
getIndex() - Method in class ai.djl.ndarray.index.dim.NDIndexFixed: Returns the dimension of the index.
getIndex(String) - Method in class ai.djl.modality.nlp.DefaultVocabulary: Returns the index of the given token.
getIndex(String) - Method in interface ai.djl.modality.nlp.Vocabulary: Returns the index of the given token.
getIndices() - Method in class ai.djl.ndarray.index.dim.NDIndexPick: Returns the indices to pick.
getIndices() - Method in class ai.djl.ndarray.index.full.NDIndexFullPick: Returns the indices to pick.
getIndices() - Method in class ai.djl.ndarray.index.NDIndex: Returns the indices.
getInitializer() - Method in enum ai.djl.nn.Parameter.Type: Gets the Initializer of this ParameterType.
getInitializers() - Method in class ai.djl.training.DefaultTrainingConfig: Gets a list of Initializer and Predicate to initialize the parameters of the model.
getInitializers() - Method in interface ai.djl.training.TrainingConfig: Gets a list of Initializer and Predicate to initialize the parameters of the model.
getInputClass() - Method in class ai.djl.repository.zoo.Criteria: Returns the input data type.
getInstance() - Static method in class ai.djl.engine.Engine: Returns the default Engine.
getInstance() - Static method in class ai.djl.modality.cv.ImageFactory: Gets new instance of Image factory from the provided factory implementation.
getInt(long...) - Method in interface ai.djl.ndarray.NDArray: Returns an int element from this NDArray.
getIoU(BoundingBox) - Method in interface ai.djl.modality.cv.output.BoundingBox: Gets the Intersection over Union (IoU) value between bounding boxes.
getIoU(BoundingBox) - Method in class ai.djl.modality.cv.output.Rectangle: Gets the Intersection over Union (IoU) value between bounding boxes.
getJoints() - Method in class ai.djl.modality.cv.output.Joints: Gets the joints for the image.
getKeyProjection() - Method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock: Pointwise Linear projection of the keys.
getLabels() - Method in class ai.djl.training.dataset.Batch: Gets the labels corresponding to the data of this Batch.
getLabels() - Method in class ai.djl.training.dataset.Record: Gets the labels that correspond to the data of this Record.
getLabels() - Method in class ai.djl.training.listener.TrainingListener.BatchData: Returns the labels for each device.
getLastUpdated() - Method in class ai.djl.repository.Metadata: Returns the last update date for the metadata.
getLatestEvaluations() - Method in class ai.djl.training.listener.EvaluatorTrainingListener: Returns the latest evaluations.
getLayout() - Method in class ai.djl.ndarray.types.Shape: Returns the layout type for each axis in this shape.
getLayoutType(int) - Method in class ai.djl.ndarray.types.Shape: Returns the layout type in the given dimension.
getLeadingOnes() - Method in class ai.djl.ndarray.types.Shape: Returns the number of leading ones in the array shape.
getLicenses() - Method in class ai.djl.repository.Metadata: Returns the License.
getLong(long...) - Method in interface ai.djl.ndarray.NDArray: Returns a long element from this NDArray.
getLoss() - Method in class ai.djl.training.Trainer: Gets the training Loss function of the trainer.
getLoss(HpSet) - Method in class ai.djl.training.hyperparameter.optimizer.BaseHpOptimizer: Returns the recorded loss.
getLoss(HpSet) - Method in interface ai.djl.training.hyperparameter.optimizer.HpOptimizer: Returns the recorded loss.
getLossFunction() - Method in class ai.djl.training.DefaultTrainingConfig: Gets the Loss function to compute the loss against.
getLossFunction() - Method in interface ai.djl.training.TrainingConfig: Gets the Loss function to compute the loss against.
getMajorVersion() - Method in class ai.djl.repository.Version: Returns the major version (assuming major.minor.incremental...) of the version.
getManager() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the NDManager that manages this.
getManager() - Method in class ai.djl.ndarray.NDList: Returns the NDManager that manages this.
getManager() - Method in interface ai.djl.ndarray.NDResource: Returns the NDManager that manages this.
getManager() - Method in class ai.djl.training.dataset.Batch: Gets the NDManager that is attached to this Batch.
getManager() - Method in class ai.djl.training.ParameterStore: Get the NDManager associated with ParameterStore.
getManager() - Method in class ai.djl.training.Trainer: Gets the NDManager from the model.
getMax() - Method in class ai.djl.ndarray.index.dim.NDIndexSlice: Returns the end of the range.
getMax() - Method in class ai.djl.ndarray.index.full.NDIndexFullSlice: Returns the slice max for each axis.
getMax() - Method in class ai.djl.training.util.MinMaxScaler: Returns the value of fittedMax.
getMessage() - Method in class ai.djl.modality.Output: Returns the status code of the output.
getMetadata() - Method in class ai.djl.repository.Artifact: Returns the metadata containing this artifact.
getMetadataVersion() - Method in class ai.djl.repository.Artifact: Returns the metadata format version.
getMetadataVersion() - Method in class ai.djl.repository.Metadata: Returns the metadata format version.
getMetric(String) - Method in class ai.djl.metric.Metrics: Returns all Metrics with the specified metric name.
getMetricName() - Method in class ai.djl.metric.Metric: Returns the name of the Metric.
getMetricNames() - Method in class ai.djl.metric.Metrics: Returns a set of String metric names.
getMetrics() - Method in class ai.djl.training.Trainer: Returns the Metrics param used for benchmarking.
getMetrics() - Method in interface ai.djl.translate.TranslatorContext: Returns the Metric tool to do benchmark.
getMin() - Method in class ai.djl.ndarray.index.dim.NDIndexSlice: Returns the start of the range.
getMin() - Method in class ai.djl.ndarray.index.full.NDIndexFullSlice: Returns the slice min for each axis.
getMin() - Method in class ai.djl.training.util.MinMaxScaler: Returns the value of fittedMin.
getMinorVersion() - Method in class ai.djl.repository.Version: Returns the minor version (assuming major.minor.incremental...) of the version.
getModel() - Method in class ai.djl.training.Trainer: Returns the model used to create this trainer.
getModel() - Method in interface ai.djl.translate.TranslatorContext: Returns the Model object to understand the input/output.
getModelLoader(String) - Method in class ai.djl.repository.zoo.ModelZoo: Returns the ModelLoader based on the model name.
getModelLoaders() - Method in class ai.djl.repository.zoo.DefaultModelZoo: Lists the available model families in the ModelZoo.
getModelLoaders() - Method in class ai.djl.repository.zoo.ModelZoo: Lists the available model families in the ModelZoo.
getModelName() - Method in class ai.djl.repository.zoo.Criteria: Returns the optional model name to be used for ZooModel.
getModelPath() - Method in class ai.djl.BaseModel: Returns the directory from where the model is loaded.
getModelPath() - Method in interface ai.djl.Model: Returns the directory from where the model is loaded.
getModelPath() - Method in class ai.djl.repository.zoo.ZooModel: Returns the directory from where the model is loaded.
getModelZoo() - Method in class ai.djl.repository.zoo.Criteria: Returns the ModelZoo to be searched.
getModelZoo() - Method in class ai.djl.repository.zoo.DefaultZooProvider: Returns the instance of the ModelZoo.
getModelZoo() - Method in interface ai.djl.repository.zoo.ZooProvider: Returns the instance of the ModelZoo.
getModelZoo(String) - Static method in class ai.djl.repository.zoo.ModelZoo: Returns the ModelZoo with the groupId.
getName() - Method in class ai.djl.BaseModel: Gets the model name.
getName() - Method in class ai.djl.metric.Dimension: Returns the dimension name.
getName() - Method in interface ai.djl.Model: Gets the model name.
getName() - Method in class ai.djl.ndarray.BaseNDManager: Gets the name of the NDManager.
getName() - Method in interface ai.djl.ndarray.NDArray: Returns the name of this NDArray.
getName() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the name of this NDArray.
getName() - Method in interface ai.djl.ndarray.NDManager: Gets the name of the NDManager.
getName() - Method in class ai.djl.ndarray.types.DataDesc: Returns the name of the NDArray.
getName() - Method in class ai.djl.nn.Parameter: Gets the name of this Parameter.
getName() - Method in class ai.djl.repository.AbstractRepository: Returns the repository name.
getName() - Method in class ai.djl.repository.Artifact: Returns the artifact name.
getName() - Method in class ai.djl.repository.Artifact.Item: Returns the item name.
getName() - Method in class ai.djl.repository.License: Returns the name of the license.
getName() - Method in class ai.djl.repository.Metadata: Returns the metadata-level name.
getName() - Method in interface ai.djl.repository.Repository: Returns the repository name.
getName() - Method in class ai.djl.repository.zoo.ZooModel: Gets the model name.
getName() - Method in interface ai.djl.repository.zoo.ZooProvider: Gets the name of the ModelZoo.
getName() - Method in class ai.djl.training.evaluator.Evaluator: Returns the name of this Evaluator.
getName() - Method in class ai.djl.training.hyperparameter.param.Hyperparameter: Returns the name of the hyperparameter.
getNamePart(String) - Static method in class ai.djl.repository.FilenameUtils: Returns the name of the file without file extension.
getNDArrayInternal() - Method in interface ai.djl.ndarray.NDArray: Returns an internal representative of Native NDArray.
getNDArrayInternal() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns an internal representative of Native NDArray.
getNDManager() - Method in class ai.djl.BaseModel: Gets the NDManager from the model.
getNDManager() - Method in interface ai.djl.Model: Gets the NDManager from the model.
getNDManager() - Method in class ai.djl.repository.zoo.ZooModel: Gets the NDManager from the model.
getNDManager() - Method in interface ai.djl.translate.TranslatorContext: Returns the NDManager to create NDArray.
getNewValue(int) - Method in class ai.djl.training.tracker.CosineTracker: Fetches the value after the given number of steps/updates.
getNewValue(int) - Method in class ai.djl.training.tracker.FactorTracker: Fetches the value after the given number of steps/updates.
getNewValue(int) - Method in class ai.djl.training.tracker.LinearTracker: Fetches the value after the given number of steps/updates.
getNewValue(int) - Method in class ai.djl.training.tracker.MultiFactorTracker: Fetches the value after the given number of steps/updates.
getNewValue(int) - Method in class ai.djl.training.tracker.PolynomialDecayTracker: Fetches the value after the given number of steps/updates.
getNewValue(int) - Method in interface ai.djl.training.tracker.Tracker: Fetches the value after the given number of steps/updates.
getNewValue(int) - Method in class ai.djl.training.tracker.WarmUpTracker: Fetches the value after the given number of steps/updates.
getNumberOfObjects() - Method in class ai.djl.modality.cv.output.DetectedObjects: Returns the number of objects found in an image.
getNumDirections() - Method in class ai.djl.nn.recurrent.RecurrentBlock
getNumEpochs() - Method in class ai.djl.training.listener.EpochTrainingListener: Returns the number of epochs.
getNumOfBytes() - Method in enum ai.djl.ndarray.types.DataType: Returns the number of bytes for each element.
getObservation() - Method in interface ai.djl.modality.rl.env.RlEnv: Returns the observation detailing the current state of the environment.
getOptimizer() - Method in class ai.djl.training.DefaultTrainingConfig: Gets the Optimizer to use during training.
getOptimizer() - Method in interface ai.djl.training.TrainingConfig: Gets the Optimizer to use during training.
getOptions() - Method in class ai.djl.repository.zoo.Criteria: Returns the model loading options.
getOptions(Map<String, String>) - Method in class ai.djl.repository.Artifact: Returns the artifact options.
getOutputClass() - Method in class ai.djl.repository.zoo.Criteria: Returns the output data type.
getOutputShapes(Shape[]) - Method in class ai.djl.modality.nlp.Decoder: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.modality.nlp.embedding.TrainableTextEmbedding: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.modality.nlp.Encoder: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.modality.nlp.EncoderDecoder: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.AbstractSymbolBlock: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in interface ai.djl.nn.Block: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.convolutional.Convolution: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.convolutional.Deconvolution: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.core.ConstantEmbedding: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.core.Embedding: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.core.Linear: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.core.Prelu: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.LambdaBlock: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.norm.BatchNorm: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.norm.Dropout: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.norm.LayerNorm: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.ParallelBlock: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.recurrent.RecurrentBlock: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.SequentialBlock: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.transformer.BertBlock: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.transformer.BertMaskedLanguageModelBlock: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.transformer.BertNextSentenceBlock: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.transformer.BertPretrainingBlock: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.transformer.IdEmbedding: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock: Returns the expected output shapes of the block for the specified input shapes.
getOutputShapes(Shape[]) - Method in class ai.djl.nn.transformer.TransformerEncoderBlock: Returns the expected output shapes of the block for the specified input shapes.
getOverrideModelName() - Method in class ai.djl.training.listener.SaveModelTrainingListener: Returns the override model name to save checkpoints with.
getParagraph() - Method in class ai.djl.modality.nlp.qa.QAInput: Gets the resource document that contains the answer.
getParameters() - Method in class ai.djl.nn.AbstractBaseBlock: Returns a list of all the parameters of the block, including the parameters of its children fetched recursively.
getParameters() - Method in interface ai.djl.nn.Block: Returns a list of all the parameters of the block, including the parameters of its children fetched recursively.
getParentManager() - Method in class ai.djl.ndarray.BaseNDManager: Returns the parent NDManager.
getParentManager() - Method in interface ai.djl.ndarray.NDManager: Returns the parent NDManager.
getParsedVersion() - Method in class ai.djl.repository.Artifact: Returns the artifact version as a Version.
getPath() - Method in class ai.djl.Application: Returns the repository path of the application.
getPath() - Method in interface ai.djl.modality.cv.output.BoundingBox: Returns an iterator object that iterates along the BoundingBox boundary and provides access to the geometry of the BoundingBox outline.
getPath() - Method in class ai.djl.modality.cv.output.Landmark: Returns an iterator object that iterates along the BoundingBox boundary and provides access to the geometry of the BoundingBox outline.
getPath() - Method in class ai.djl.modality.cv.output.Rectangle: Returns an iterator object that iterates along the BoundingBox boundary and provides access to the geometry of the BoundingBox outline.
getPoint() - Method in interface ai.djl.modality.cv.output.BoundingBox: Returns the top left point of the bounding box.
getPoint() - Method in class ai.djl.modality.cv.output.Rectangle: Returns the top left point of the bounding box.
getPostActionSpace() - Method in interface ai.djl.modality.rl.env.RlEnv.Step: Returns the available actions after the step.
getPostObservation() - Method in interface ai.djl.modality.rl.env.RlEnv.Step: Returns the observation detailing the state after the action.
getPredictions() - Method in class ai.djl.training.listener.TrainingListener.BatchData: Returns the predictions for each device.
getPredictorManager() - Method in interface ai.djl.translate.TranslatorContext: Returns the Predictor's NDManager.
getPreObservation() - Method in interface ai.djl.modality.rl.env.RlEnv.Step: Returns the observation detailing the state before the action.
getPreprocessors(boolean) - Static method in class ai.djl.modality.nlp.bert.BertFullTokenizer: Get a list of TextProcessors to process input text for Bert models.
getProbability() - Method in class ai.djl.modality.Classifications.Classification: Returns the probability.
getProbDist() - Method in class ai.djl.modality.cv.output.Mask: Returns the probability for each pixel.
getProgress() - Method in class ai.djl.repository.zoo.Criteria: Returns the optional Progress for the model loading.
getProgress() - Method in class ai.djl.training.dataset.Batch: Returns the progress of the batch if it is part of some kind of iteration like a dataset iteration.
getProgressTotal() - Method in class ai.djl.training.dataset.Batch: Returns the total or end value for the progress of the batch if it is part of some kind of iteration like a dataset iteration.
getProperties() - Method in class ai.djl.modality.Input: Returns the properties of the input.
getProperties() - Method in class ai.djl.repository.Artifact: Returns the artifact properties.
getProperty(String) - Method in class ai.djl.BaseModel: Gets the property of the model based on property name.
getProperty(String) - Method in interface ai.djl.Model: Gets the property of the model based on property name.
getProperty(String) - Method in class ai.djl.repository.zoo.ZooModel: Gets the property of the model based on property name.
getProperty(String, String) - Method in class ai.djl.modality.Input: Returns the value to which the specified key is mapped.
getQueryProjection() - Method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock: Pointwise Linear projection of the queries.
getQuestion() - Method in class ai.djl.modality.nlp.qa.QAInput: Gets the question for the model.
getRank() - Method in class ai.djl.engine.Engine: Return the rank of the Engine.
getRank() - Method in class ai.djl.ndarray.index.dim.NDIndexAll: Returns the number of dimensions occupied by this index element.
getRank() - Method in class ai.djl.ndarray.index.dim.NDIndexBooleans: Returns the number of dimensions occupied by this index element.
getRank() - Method in interface ai.djl.ndarray.index.dim.NDIndexElement: Returns the number of dimensions occupied by this index element.
getRank() - Method in class ai.djl.ndarray.index.dim.NDIndexFixed: Returns the number of dimensions occupied by this index element.
getRank() - Method in class ai.djl.ndarray.index.dim.NDIndexPick: Returns the number of dimensions occupied by this index element.
getRank() - Method in class ai.djl.ndarray.index.dim.NDIndexSlice: Returns the number of dimensions occupied by this index element.
getRank() - Method in class ai.djl.ndarray.index.NDIndex: Returns the number of dimensions specified in the Index.
getRecommendedVersion() - Method in class ai.djl.repository.VersionRange: Returns the recommended version in the range.
getRepository() - Method in class ai.djl.repository.MRL: Returns the repository.
getRepositoryUri() - Method in class ai.djl.repository.Metadata: Returns the URI to the repository storing the metadata.
getResourceDirectory(Artifact) - Method in interface ai.djl.repository.Repository: Returns the resource directory for the an artifact.
getResourceDirectory(Artifact) - Method in class ai.djl.repository.SimpleRepository: Returns the resource directory for the an artifact.
getResources() - Method in class ai.djl.repository.JarRepository: Returns a list of MRLs in the repository.
getResources() - Method in class ai.djl.repository.LocalRepository: Returns a list of MRLs in the repository.
getResources() - Method in class ai.djl.repository.RemoteRepository: Returns a list of MRLs in the repository.
getResources() - Method in interface ai.djl.repository.Repository: Returns a list of MRLs in the repository.
getResources() - Method in class ai.djl.repository.SimpleRepository: Returns a list of MRLs in the repository.
getResources() - Method in class ai.djl.repository.SimpleUrlRepository: Returns a list of MRLs in the repository.
getResourceType() - Method in class ai.djl.repository.Metadata: Returns the resource type.
getResourceUri() - Method in class ai.djl.repository.Artifact: Returns the location of the resource directory.
getRestrictions() - Method in class ai.djl.repository.VersionRange: Returns the restrictions that compose the range.
getResultProjection() - Method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock: Pointwise Linear projection of the results.
getReward() - Method in interface ai.djl.modality.rl.env.RlEnv.Step: Returns the reward given for the action.
getSampler() - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Gets the Sampler for the dataset.
getScalar(long...) - Method in interface ai.djl.ndarray.NDArray: Returns a scalar NDArray corresponding to a single element.
getSeed() - Method in class ai.djl.engine.Engine: Returns the random seed in DJL Engine.
getSha1Hash() - Method in class ai.djl.repository.Artifact.Item: Returns the hash of the item.
getShape() - Method in class ai.djl.ndarray.index.full.NDIndexFullSlice: Returns the slice shape without squeezing.
getShape() - Method in interface ai.djl.ndarray.NDArray: Returns the Shape of this NDArray.
getShape() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the Shape of this NDArray.
getShape() - Method in class ai.djl.ndarray.types.DataDesc: Returns the Shape of the NDArray.
getShape() - Method in class ai.djl.ndarray.types.Shape: Returns the dimensions of the Shape.
getShapeFromEmptyNDArrayForReductionOp(Shape, int) - Static method in class ai.djl.ndarray.NDUtils: Get Shape of the empty NDArray after applying reduction operations.
getShapes() - Method in class ai.djl.ndarray.NDList: Gets all of shapes in the NDList.
getSize() - Method in class ai.djl.repository.Artifact.Item: Returns the file size.
getSize() - Method in class ai.djl.training.dataset.Batch: Returns the batchSize.
getSparseFormat() - Method in interface ai.djl.ndarray.NDArray: Returns the SparseFormat of this NDArray.
getSparseFormat() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the SparseFormat of this NDArray.
getSqueezedShape() - Method in class ai.djl.ndarray.index.full.NDIndexFullSlice: Returns the slice shape with squeezing.
getStates(NDList) - Method in class ai.djl.modality.nlp.Encoder: Gets the state of the encoder from the given encoder output.
getStep() - Method in class ai.djl.ndarray.index.dim.NDIndexSlice: Returns the step between each slice.
getStep() - Method in class ai.djl.ndarray.index.full.NDIndexFullSlice: Returns the slice step for each axis.
getStringLayout() - Method in class ai.djl.nn.convolutional.Conv1d: Returns the string representing the layout of the input.
getStringLayout() - Method in class ai.djl.nn.convolutional.Conv1dTranspose: Returns the string representing the layout of the input.
getStringLayout() - Method in class ai.djl.nn.convolutional.Conv2d: Returns the string representing the layout of the input.
getStringLayout() - Method in class ai.djl.nn.convolutional.Conv2dTranspose: Returns the string representing the layout of the input.
getStringLayout() - Method in class ai.djl.nn.convolutional.Conv3d: Returns the string representing the layout of the input.
getStringLayout() - Method in class ai.djl.nn.convolutional.Convolution: Returns the string representing the layout of the input.
getStringLayout() - Method in class ai.djl.nn.convolutional.Deconvolution: Returns the string representing the layout of the input.
getSubImage(int, int, int, int) - Method in interface ai.djl.modality.cv.Image: Gets the subimage defined by a specified rectangular region.
getSupportedEngines() - Method in class ai.djl.repository.zoo.DefaultModelZoo: Returns all supported engine names.
getSupportedEngines() - Method in class ai.djl.repository.zoo.ModelZoo: Returns all supported engine names.
getSupportedScheme() - Method in interface ai.djl.repository.RepositoryFactory: Returns a set of URI scheme that the RepositoryFactory supports.
getSupportedTypes() - Method in class ai.djl.modality.cv.translator.BigGANTranslatorFactory: Returns supported input/output classes.
getSupportedTypes() - Method in class ai.djl.modality.cv.translator.ImageClassificationTranslatorFactory: Returns supported input/output classes.
getSupportedTypes() - Method in class ai.djl.modality.cv.translator.ObjectDetectionTranslatorFactory: Returns supported input/output classes.
getSupportedTypes() - Method in class ai.djl.modality.cv.translator.SimplePoseTranslatorFactory: Returns supported input/output classes.
getSupportedTypes() - Method in class ai.djl.modality.cv.translator.StyleTransferTranslatorFactory: Returns supported input/output classes.
getSupportedTypes() - Method in class ai.djl.translate.DefaultTranslatorFactory: Returns supported input/output classes.
getSupportedTypes() - Method in class ai.djl.translate.ServingTranslatorFactory: Returns supported input/output classes.
getSupportedTypes() - Method in interface ai.djl.translate.TranslatorFactory: Returns supported input/output classes.
getTimestamp() - Method in class ai.djl.metric.Metric: Returns the timestamp of the Metric.
getToken(long) - Method in class ai.djl.modality.nlp.DefaultVocabulary: Returns the token corresponding to the given index.
getToken(long) - Method in interface ai.djl.modality.nlp.Vocabulary: Returns the token corresponding to the given index.
getTokenDictionarySize() - Method in class ai.djl.nn.transformer.BertBlock: Returns the size of the token dictionary.
getTokenEmbedding() - Method in class ai.djl.nn.transformer.BertBlock: Returns the token embedding used by this Bert model.
getTokens() - Method in class ai.djl.modality.nlp.bert.BertToken: Gets the indices of input sequence tokens in the vocabulary.
getTokenTypes() - Method in class ai.djl.modality.nlp.bert.BertToken: Gets segment token indices to indicate first and second portions of the inputs.
getToSqueeze() - Method in class ai.djl.ndarray.index.full.NDIndexFullSlice: Returns the squeeze array of axis.
getTrailingOnes() - Method in class ai.djl.ndarray.types.Shape: Returns the number of trailing ones in the array shape.
getTrainEvaluation(String) - Method in class ai.djl.training.TrainingResult: Returns the evaluation to which the specified key is mapped.
getTrainingListeners() - Method in class ai.djl.training.DefaultTrainingConfig: Returns the list of TrainingListeners that should be used during training.
getTrainingListeners() - Method in interface ai.djl.training.TrainingConfig: Returns the list of TrainingListeners that should be used during training.
getTrainingResult() - Method in class ai.djl.training.Trainer: Returns the TrainingResult.
getTrainLoss() - Method in class ai.djl.training.TrainingResult: Returns the train loss.
getTranslator() - Method in class ai.djl.repository.zoo.ZooModel: Returns the default translator.
getTranslatorFactory() - Method in class ai.djl.repository.zoo.Criteria: Returns the optional TranslatorFactory to be used for ZooModel.
getTranslatorFactory(Criteria<?, ?>, Map<String, Object>) - Method in class ai.djl.repository.zoo.BaseModelLoader
getType() - Method in enum ai.djl.ndarray.types.SparseFormat: Returns the SparseFormat name.
getType() - Method in class ai.djl.nn.Parameter: Gets the type of this Parameter.
getType() - Method in class ai.djl.repository.Artifact.Item: Sets the type of the item.
getTypeDictionarySize() - Method in class ai.djl.nn.transformer.BertBlock: Returns the size of the type dictionary.
getUid() - Method in interface ai.djl.ndarray.NDArray: Returns unique identifier of this NDArray.
getUid() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns unique identifier of this NDArray.
getUint8(long...) - Method in interface ai.djl.ndarray.NDArray: Returns an integer element from this NDArray that represent unsigned integer with 8 bits.
getUnit() - Method in class ai.djl.metric.Metric: Returns the unit of the Metric.
getUnknownValueCount() - Method in class ai.djl.ndarray.types.Shape: Return the count of unknown value in this Shape.
getUri() - Method in class ai.djl.repository.Artifact.Item: Returns the URI of the item.
getUrl() - Method in class ai.djl.repository.License: Returns the url of the license.
getValidateEvaluation(String) - Method in class ai.djl.training.TrainingResult: Returns the evaluation to which the specified key is mapped.
getValidateLoss() - Method in class ai.djl.training.TrainingResult: Returns the validate loss.
getValidLength() - Method in class ai.djl.modality.nlp.bert.BertToken: Gets the length of the original sentence which has question and paragraph.
getValue() - Method in class ai.djl.metric.Dimension: Returns the dimension value.
getValue() - Method in class ai.djl.metric.Metric: Returns the int value of the Metric.
getValue() - Method in enum ai.djl.metric.Unit: Returns the string value of the Unit.
getValue() - Method in enum ai.djl.ndarray.types.LayoutType: Returns the character representation of the layout type.
getValue() - Method in enum ai.djl.ndarray.types.SparseFormat: Returns the integer value of this SparseFormat.
getValue(Parameter, Device, boolean) - Method in class ai.djl.training.ParameterStore: Returns the value of a mirrored parameter on a device.
getValue(ParameterStore, Device, boolean) - Method in class ai.djl.nn.transformer.IdEmbedding: Quick hack for bert model to acces embedding table, replace by a proper function to calculate raw logits from embeddings.
getValueProjection() - Method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock: Pointwise Linear projection of the values.
getVersion() - Method in class ai.djl.engine.Engine: Returns the version of the deep learning engine.
getVersion() - Method in class ai.djl.repository.Artifact: Returns the artifact version.
getVersion() - Method in class ai.djl.repository.MRL: Returns the version.
getVocabulary() - Method in class ai.djl.modality.nlp.bert.BertFullTokenizer: Returns the Vocabulary used for tokenization.
getWebsite() - Method in class ai.djl.repository.Metadata: Returns the website.
getWeightDecay() - Method in class ai.djl.training.optimizer.Optimizer: Gets the value of weight decay.
getWidth() - Method in interface ai.djl.modality.cv.Image: Gets the width of the image.
getWidth() - Method in class ai.djl.modality.cv.output.Rectangle: Returns the width of the Rectangle.
getWrappedImage() - Method in interface ai.djl.modality.cv.Image: Gets the wrapped image.
getWrappedModel() - Method in class ai.djl.repository.zoo.ZooModel: Returns the wrapped model.
getX() - Method in class ai.djl.modality.cv.output.Point: Returns the X coordinate of this Point in double precision.
getX() - Method in class ai.djl.modality.cv.output.Rectangle: Returns the left x-coordinate of the Rectangle.
getY() - Method in class ai.djl.modality.cv.output.Point: Returns the Y coordinate of this Point in double precision.
getY() - Method in class ai.djl.modality.cv.output.Rectangle: Returns the top y-coordinate of the Rectangle.
GIGABITS - ai.djl.metric.Unit
GIGABITS_PER_SECOND - ai.djl.metric.Unit
GIGABYTES - ai.djl.metric.Unit
GIGABYTES_PER_SECOND - ai.djl.metric.Unit
globalAvgPool1d(NDArray) - Static method in class ai.djl.nn.pooling.Pool: Performs 1-D Global Avg Pooling on the input.
globalAvgPool1dBlock() - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the globalAvgPool1d pooling function.
globalAvgPool2d(NDArray) - Static method in class ai.djl.nn.pooling.Pool: Performs 2-D Global Avg Pooling on the input.
globalAvgPool2dBlock() - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the globalAvgPool2d pooling function.
globalAvgPool3d(NDArray) - Static method in class ai.djl.nn.pooling.Pool: Performs 3-D Global Avg Pooling on the input.
globalAvgPool3dBlock() - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the globalAvgPool3d pooling function.
globalLpPool1d(NDArray, float) - Static method in class ai.djl.nn.pooling.Pool: Performs 1-D Global LP Pooling on the input.
globalLpPool1dBlock(float) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the globalLpPool1d pooling function.
globalLpPool2d(NDArray, float) - Static method in class ai.djl.nn.pooling.Pool: Performs 2-D Global LP Pooling on the input.
globalLpPool2dBlock(float) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the globalLpPool2d pooling function.
globalLpPool3d(NDArray, float) - Static method in class ai.djl.nn.pooling.Pool: Performs 3-D Global LP Pooling on the input.
globalLpPool3dBlock(float) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the globalLpPool3d pooling function.
globalMaxPool1d(NDArray) - Static method in class ai.djl.nn.pooling.Pool: Performs 1-D Global Max Pooling on the input.
globalMaxPool1dBlock() - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the globalmaxPool1dBlock pooling function.
globalMaxPool2d(NDArray) - Static method in class ai.djl.nn.pooling.Pool: Performs 2-D Global Max Pooling on the input.
globalMaxPool2dBlock() - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the globalmaxPool2dBlock pooling function.
globalMaxPool3d(NDArray) - Static method in class ai.djl.nn.pooling.Pool: Performs 3-D Global Max Pooling on the input.
globalMaxPool3dBlock() - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the globalmaxPool3dBlock pooling function.
gpu() - Static method in class ai.djl.Device: Returns the default GPU Device.
gpu(int) - Static method in class ai.djl.Device: Returns a new instance of GPU Device with the specified deviceId.
GPU - Static variable in interface ai.djl.Device.Type
GradientCollector - Interface in ai.djl.training: An interface that provides a mechanism to collect gradients during training.
GRAYSCALE - ai.djl.modality.cv.Image.Flag
GROUP_ID - Static variable in class ai.djl.repository.zoo.DefaultModelZoo
groupId - Variable in class ai.djl.repository.Metadata
groups - Variable in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder
groups - Variable in class ai.djl.nn.convolutional.Convolution
groups - Variable in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder
groups - Variable in class ai.djl.nn.convolutional.Deconvolution
GRU - Class in ai.djl.nn.recurrent: GRU is an abstract implementation of recurrent neural networks which applies GRU (Gated Recurrent Unit) recurrent layer to input.
GRU.Builder - Class in ai.djl.nn.recurrent: The Builder to construct a GRU type of Block.
gt(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Greater Than" comparison.
gt(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Greater Than" comparison.
gt(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Greater Than" comparison.
gt(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Greater Than" comparison.
gt(Number) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Greater" comparison.
gt(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Greater" comparison.
gt(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Greater Than" comparison.
gte(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Greater or equals" comparison.
gte(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Greater or equals" comparison.
gte(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Greater or equals" comparison.
gte(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Greater or equals" comparison.
gte(Number) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Greater or equals" comparison.
gte(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Greater or equals" comparison.
gte(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Greater or equals" comparison.

H

hasBiases - Variable in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder
hasBiases - Variable in class ai.djl.nn.recurrent.RecurrentBlock
hasCapability(String) - Method in class ai.djl.engine.Engine: Returns whether the engine has the specified capability.
hasEngine(String) - Static method in class ai.djl.engine.Engine: Returns if the specified engine is available.
hasGradient() - Method in interface ai.djl.ndarray.NDArray: Returns true if the gradient calculation is required for this NDArray.
hasGradient() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns true if the gradient calculation is required for this NDArray.
hashCode() - Method in class ai.djl.Application
hashCode() - Method in class ai.djl.Device
hashCode() - Method in class ai.djl.ndarray.types.Shape
hashCode() - Method in class ai.djl.repository.Version
hasItem(Object) - Method in class ai.djl.nn.core.ConstantEmbedding: Returns whether an item is in the embedding.
hasItem(String) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Returns whether an item is in the embedding.
hasItem(T) - Method in interface ai.djl.nn.core.AbstractEmbedding: Returns whether an item is in the embedding.
hasItem(T) - Method in class ai.djl.nn.core.Embedding.DefaultEmbedding: Returns whether an item is in the embedding.
hasItem(T) - Method in class ai.djl.nn.core.Embedding.DefaultItem: Returns whether an item is in the embedding.
hasMetric(String) - Method in class ai.djl.metric.Metrics: Returns true if the metrics object has a metric with the given name.
hasModelZoo(String) - Static method in class ai.djl.repository.zoo.ModelZoo: Returns whether a model zoo with the group id is available.
hasNext() - Method in class ai.djl.training.dataset.DataIterable
hasProperties(Map<String, String>) - Method in class ai.djl.repository.Artifact: Returns true if every filter matches the corresponding property.
hasZeroDimension() - Method in class ai.djl.ndarray.types.Shape: Returns true if the NDArray contains zero dimensions.
head() - Method in class ai.djl.ndarray.NDList: Returns the head index of the NDList.
head() - Method in class ai.djl.ndarray.types.Shape: Returns the head index of the shape.
height - Variable in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder
HEIGHT - ai.djl.ndarray.types.LayoutType
hingeLoss() - Static method in class ai.djl.training.loss.Loss: Returns a new instance of HingeLoss with default arguments.
hingeLoss(String) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of HingeLoss with default arguments.
hingeLoss(String, int, float) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of HingeLoss with the given arguments.
HingeLoss - Class in ai.djl.training.loss: HingeLoss is a type of Loss.
HingeLoss() - Constructor for class ai.djl.training.loss.HingeLoss: Calculates Hinge loss.
HingeLoss(String) - Constructor for class ai.djl.training.loss.HingeLoss: Calculates Hinge loss.
HingeLoss(String, int, float) - Constructor for class ai.djl.training.loss.HingeLoss: Calculates Hinge loss.
HpBool - Class in ai.djl.training.hyperparameter.param: A Hyperparameter for a boolean option.
HpBool(String) - Constructor for class ai.djl.training.hyperparameter.param.HpBool: Constructs a HpBool.
HpCategorical<T> - Class in ai.djl.training.hyperparameter.param: A Hyperparameter which is one of a fixed number of options (similar to an enum).
HpCategorical(String, List<T>) - Constructor for class ai.djl.training.hyperparameter.param.HpCategorical: Constructs a HpCategorical.
HpFloat - Class in ai.djl.training.hyperparameter.param: A Hyperparameter for a float.
HpFloat(String, float, float, boolean) - Constructor for class ai.djl.training.hyperparameter.param.HpFloat: Constructs a HpFloat.
HpInt - Class in ai.djl.training.hyperparameter.param: A Hyperparameter for an integer.
HpInt(String, int, int) - Constructor for class ai.djl.training.hyperparameter.param.HpInt: Constructs a HpInt.
HpOptimizer - Interface in ai.djl.training.hyperparameter.optimizer: An optimizer for Hyperparameters.
HpORandom - Class in ai.djl.training.hyperparameter.optimizer: A simple HpOptimizer that tries random hyperparameter choices within the range.
HpORandom(HpSet) - Constructor for class ai.djl.training.hyperparameter.optimizer.HpORandom: Constructs a new HpORandom.
HpSet - Class in ai.djl.training.hyperparameter.param: A nestable set of Hyperparameters.
HpSet(String) - Constructor for class ai.djl.training.hyperparameter.param.HpSet: Cosntructs a new empty HpSet.
HpSet(String, List<Hyperparameter<?>>) - Constructor for class ai.djl.training.hyperparameter.param.HpSet: Cosntructs a new HpSet.
HpVal<T> - Class in ai.djl.training.hyperparameter.param: A Hyperparameter with a known value instead of a range of possible values.
HpVal(String, T) - Constructor for class ai.djl.training.hyperparameter.param.HpVal: Cosntructs a new HpVal.
Hyperparameter<T> - Class in ai.djl.training.hyperparameter.param: A class representing an input to the network that can't be differentiated.
Hyperparameter(String) - Constructor for class ai.djl.training.hyperparameter.param.Hyperparameter: Constructs a hyperparameter with the given name.
hyperParams - Variable in class ai.djl.training.hyperparameter.optimizer.BaseHpOptimizer
HyphenNormalizer - Class in ai.djl.modality.nlp.preprocess: Unicode normalization does not take care of "exotic" hyphens that we normally do not want in NLP input.
HyphenNormalizer() - Constructor for class ai.djl.modality.nlp.preprocess.HyphenNormalizer

I

IdEmbedding - Class in ai.djl.nn.transformer: An Embedding from integer ids to float vectors.
IdEmbedding.Builder - Class in ai.djl.nn.transformer: The Builder to construct an IdEmbedding type of Block.
identityBlock() - Static method in class ai.djl.nn.Blocks: Creates a LambdaBlock that performs the identity function.
Image - Interface in ai.djl.modality.cv: Image is a container of an image in DJL.
IMAGE_CLASSIFICATION - Static variable in interface ai.djl.Application.CV: An application where images are assigned a single class name.
IMAGE_ENHANCEMENT - Static variable in interface ai.djl.Application.CV: An application that accepts an image and returns enhanced images.
IMAGE_GENERATION - Static variable in interface ai.djl.Application.CV: An application that accepts a seed and returns generated images.
Image.Flag - Enum in ai.djl.modality.cv: Flag indicates the color channel options for images.
Image.Interpolation - Enum in ai.djl.modality.cv: Interpolation indicates the Interpolation options for resizinig an image.
ImageClassificationTranslator - Class in ai.djl.modality.cv.translator: A generic Translator for Image Classification tasks.
ImageClassificationTranslator(ImageClassificationTranslator.Builder) - Constructor for class ai.djl.modality.cv.translator.ImageClassificationTranslator: Constructs an Image Classification using ImageClassificationTranslator.Builder.
ImageClassificationTranslator.Builder - Class in ai.djl.modality.cv.translator: A Builder to construct a ImageClassificationTranslator.
ImageClassificationTranslatorFactory - Class in ai.djl.modality.cv.translator: A TranslatorFactory that creates an ImageClassificationTranslator.
ImageClassificationTranslatorFactory() - Constructor for class ai.djl.modality.cv.translator.ImageClassificationTranslatorFactory
ImageFactory - Class in ai.djl.modality.cv: ImageFactory contains image creation mechanism on top of different platforms like PC and Android.
ImageFactory() - Constructor for class ai.djl.modality.cv.ImageFactory
imageHeight - Variable in class ai.djl.modality.cv.translator.ObjectDetectionTranslator
imageHeight - Variable in class ai.djl.modality.cv.translator.ObjectDetectionTranslator.ObjectDetectionBuilder
ImageServingTranslator - Class in ai.djl.modality.cv.translator: A Translator that can handle generic CV Input and Output.
ImageServingTranslator(Translator<Image, ?>) - Constructor for class ai.djl.modality.cv.translator.ImageServingTranslator: Constructs a new ImageServingTranslator instance.
imageWidth - Variable in class ai.djl.modality.cv.translator.ObjectDetectionTranslator
imageWidth - Variable in class ai.djl.modality.cv.translator.ObjectDetectionTranslator.ObjectDetectionBuilder
IN - ai.djl.training.initializer.XavierInitializer.FactorType
includeBias - Variable in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder
includeBias - Variable in class ai.djl.nn.convolutional.Convolution
includeBias - Variable in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder
includeBias - Variable in class ai.djl.nn.convolutional.Deconvolution
includeTokenTypes - Variable in class ai.djl.modality.nlp.translator.QATranslator
increment(long) - Method in class ai.djl.training.util.ProgressBar
IndexEvaluator - Class in ai.djl.training.evaluator: A wrapper for an Evaluator that evaluates on only a particular NDArray in the predictions and/or labels NDLists.
IndexEvaluator(Evaluator, int) - Constructor for class ai.djl.training.evaluator.IndexEvaluator: Constructs an IndexEvaluator with the same index for both predictions and labels.
IndexEvaluator(Evaluator, Integer, Integer) - Constructor for class ai.djl.training.evaluator.IndexEvaluator: Constructs an IndexEvaluator.
IndexLoss - Class in ai.djl.training.loss: A wrapper for a Loss that evaluates on only a particular NDArray in the predictions and/or labels NDLists.
IndexLoss(Loss, int) - Constructor for class ai.djl.training.loss.IndexLoss: Constructs an IndexLoss with the same index for both predictions and labels.
IndexLoss(Loss, Integer, Integer) - Constructor for class ai.djl.training.loss.IndexLoss: Constructs an IndexLoss.
init(String, NDArray[]) - Method in class ai.djl.training.LocalParameterServer: Initializes the ParameterStore for the given parameter.
init(String, NDArray[]) - Method in interface ai.djl.training.ParameterServer: Initializes the ParameterStore for the given parameter.
init(Map<String, String>) - Method in class ai.djl.repository.Metadata: Restores artifacts state.
initialize(NDManager, DataType) - Method in class ai.djl.nn.Parameter: Initializes the parameter with the given NDManager, with given DataType for the given expected input shapes.
initialize(NDManager, DataType, Shape...) - Method in class ai.djl.modality.nlp.EncoderDecoder: Initializes the parameters of the block.
initialize(NDManager, DataType, Shape...) - Method in class ai.djl.nn.AbstractBaseBlock: Initializes the parameters of the block.
initialize(NDManager, DataType, Shape...) - Method in interface ai.djl.nn.Block: Initializes the parameters of the block.
initialize(NDManager, Shape, DataType) - Method in class ai.djl.training.initializer.ConstantInitializer: Initializes a single NDArray.
initialize(NDManager, Shape, DataType) - Method in interface ai.djl.training.initializer.Initializer: Initializes a single NDArray.
initialize(NDManager, Shape, DataType) - Method in class ai.djl.training.initializer.NormalInitializer: Initializes a single NDArray.
initialize(NDManager, Shape, DataType) - Method in class ai.djl.training.initializer.TruncatedNormalInitializer: Initializes a single NDArray.
initialize(NDManager, Shape, DataType) - Method in class ai.djl.training.initializer.UniformInitializer: Initializes a single NDArray.
initialize(NDManager, Shape, DataType) - Method in class ai.djl.training.initializer.XavierInitializer: Initializes a single NDArray.
initialize(Shape...) - Method in class ai.djl.training.Trainer: Initializes the Model that the Trainer is going to train.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.modality.nlp.Decoder: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.modality.nlp.embedding.TrainableTextEmbedding: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.modality.nlp.Encoder: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.nn.AbstractBaseBlock: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.nn.ParallelBlock: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.nn.SequentialBlock: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.nn.transformer.BertBlock: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.nn.transformer.BertMaskedLanguageModelBlock: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.nn.transformer.BertNextSentenceBlock: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.nn.transformer.BertPretrainingBlock: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.nn.transformer.IdEmbedding: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock: Initializes the Child blocks of this block.
initializeChildBlocks(NDManager, DataType, Shape...) - Method in class ai.djl.nn.transformer.TransformerEncoderBlock: Initializes the Child blocks of this block.
Initializer - Interface in ai.djl.training.initializer: An interface representing an initialization method.
Input - Class in ai.djl.modality: A class stores the generic input data for inference.
Input() - Constructor for class ai.djl.modality.Input: Constructs a new Input instance.
inputData - Variable in class ai.djl.BaseModel
inputForComponent(int, NDList, NDList) - Method in class ai.djl.nn.transformer.BertPretrainingLoss
inputForComponent(int, NDList, NDList) - Method in class ai.djl.training.loss.AbstractCompositeLoss: Returns the inputs to computing the loss for a component loss.
inputForComponent(int, NDList, NDList) - Method in class ai.djl.training.loss.SimpleCompositeLoss: Returns the inputs to computing the loss for a component loss.
inputForComponent(int, NDList, NDList) - Method in class ai.djl.training.loss.SingleShotDetectionLoss: Calculate loss between label and prediction.
inputNames - Variable in class ai.djl.nn.AbstractBaseBlock: List of names for the input, named inputs should be manually set in sub class.
inputShape(HpSet) - Method in class ai.djl.training.hyperparameter.EasyHpo: Returns the input shape for the model.
inputShapes - Variable in class ai.djl.nn.AbstractBaseBlock: The shape of the input for this block, set by the initialization process.
InputStreamTranslator<T> - Class in ai.djl.modality.cv.translator.wrapper: Built-in Translator that provides image pre-processing from InputStream.
InputStreamTranslator(Translator<Image, T>) - Constructor for class ai.djl.modality.cv.translator.wrapper.InputStreamTranslator: Creates a UrlTranslator instance.
insert(int, int, Transform) - Method in class ai.djl.translate.Pipeline: Inserts the given Transform to the list of transforms at the given position to be applied on the NDArray at the given index in the input NDList.
insert(int, Transform) - Method in class ai.djl.translate.Pipeline: Inserts the given Transform to the list of transforms at the given position.
insert(int, String, Transform) - Method in class ai.djl.translate.Pipeline: Inserts the given Transform to the list of transforms at the given position to be applied on the NDArray with the given name in the input NDList.
INSTANCE_SEGMENTATION - Static variable in interface ai.djl.Application.CV: An application that finds zero or more objects in an image, the object class (see image classification), and their location as a pixel map.
InstanceSegmentationTranslator - Class in ai.djl.modality.cv.translator: A BaseImageTranslator that post-process the NDArray into DetectedObjects with boundaries at the detailed pixel level.
InstanceSegmentationTranslator(InstanceSegmentationTranslator.Builder) - Constructor for class ai.djl.modality.cv.translator.InstanceSegmentationTranslator: Creates the Instance Segmentation translator from the given builder.
InstanceSegmentationTranslator.Builder - Class in ai.djl.modality.cv.translator: The builder for Instance Segmentation translator.
InstanceSegmentationTranslatorFactory - Class in ai.djl.modality.cv.translator: A TranslatorFactory that creates a InstanceSegmentationTranslator instance.
InstanceSegmentationTranslatorFactory() - Constructor for class ai.djl.modality.cv.translator.InstanceSegmentationTranslatorFactory
INT - ai.djl.ndarray.types.DataType.Format
INT32 - ai.djl.ndarray.types.DataType
INT64 - ai.djl.ndarray.types.DataType
INT8 - ai.djl.ndarray.types.DataType
intern(NDArray) - Method in interface ai.djl.ndarray.NDArray: Replace the handle of the NDArray with the other.
intValue(Map<String, ?>, String) - Static method in class ai.djl.translate.ArgumentsUtil: Returns the integer value from the arguments.
intValue(Map<String, ?>, String, int) - Static method in class ai.djl.translate.ArgumentsUtil: Returns the integer value from the arguments.
inverseTransform(NDArray) - Method in class ai.djl.training.util.MinMaxScaler: Undoes the transformation of X according to feature_range.
inverseTransformi(NDArray) - Method in class ai.djl.training.util.MinMaxScaler: Undoes the transformation of X according to feature_range as an in-place operation.
invoke(String, NDArray[], NDArray[], PairList<String, ?>) - Method in class ai.djl.ndarray.BaseNDManager: An engine specific generic invocation to native operation.
invoke(String, NDArray[], NDArray[], PairList<String, ?>) - Method in interface ai.djl.ndarray.NDManager: An engine specific generic invocation to native operation.
invoke(String, NDList, PairList<String, ?>) - Method in class ai.djl.ndarray.BaseNDManager: An engine specific generic invocation to native operation.
invoke(String, NDList, PairList<String, ?>) - Method in interface ai.djl.ndarray.NDManager: An engine specific generic invocation to native operation.
isArchiveFile(String) - Static method in class ai.djl.repository.FilenameUtils: Returns if the the file is an archive file.
isCHW(Shape) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Check if the shape of the image follows CHW/NCHW.
isClosed - Variable in class ai.djl.ndarray.NDArrayAdapter
isControl(char) - Static method in class ai.djl.modality.nlp.NlpUtils: Check whether a character is is considered as a control character.
isDone() - Method in interface ai.djl.modality.rl.env.RlEnv.Step: Returns whether the environment is finished or can accept further actions.
isEmpty() - Method in interface ai.djl.ndarray.NDArray: Returns true if this NDArray is special case: no-value NDArray.
isFloating() - Method in enum ai.djl.ndarray.types.DataType: Checks whether it is a floating data type.
isGpu() - Method in class ai.djl.Device: Returns if the Device is GPU.
isHyphenLike(Integer) - Static method in class ai.djl.modality.nlp.preprocess.HyphenNormalizer: Returns whether the given code point is a hyphen-like codepoint.
isInfinite() - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray with value true where this NDArray's entries are infinite, or false where they are not infinite.
isInfinite() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray with value true where this NDArray's entries are infinite, or false where they are not infinite.
isInitialized() - Method in class ai.djl.nn.AbstractBaseBlock: Returns a boolean whether the block is initialized.
isInitialized() - Method in interface ai.djl.nn.Block: Returns a boolean whether the block is initialized.
isInitialized() - Method in class ai.djl.nn.Parameter: Checks if this Parameter is initialized.
isInteger() - Method in enum ai.djl.ndarray.types.DataType: Checks whether it is an integer data type.
isLayoutKnown() - Method in class ai.djl.ndarray.types.Shape: Returns true if a layout is set.
isNaN() - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray with value true where this NDArray's entries are NaN, or false where they are not NaN.
isNaN() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray with value true where this NDArray's entries are NaN, or false where they are not NaN.
isOpen() - Method in class ai.djl.ndarray.BaseNDManager: Check if the manager is still valid.
isOpen() - Method in interface ai.djl.ndarray.NDManager: Check if the manager is still valid.
isPunctuation(char) - Static method in class ai.djl.modality.nlp.NlpUtils: Check whether a character is considered as a punctuation.
isRemote() - Method in class ai.djl.repository.JarRepository: Returns whether the repository is remote repository.
isRemote() - Method in class ai.djl.repository.LocalRepository: Returns whether the repository is remote repository.
isRemote() - Method in class ai.djl.repository.RemoteRepository: Returns whether the repository is remote repository.
isRemote() - Method in interface ai.djl.repository.Repository: Returns whether the repository is remote repository.
isRemote() - Method in class ai.djl.repository.SimpleRepository: Returns whether the repository is remote repository.
isRemote() - Method in class ai.djl.repository.SimpleUrlRepository: Returns whether the repository is remote repository.
isScalar() - Method in interface ai.djl.ndarray.NDArray: Returns true if this NDArray is a scalar NDArray with empty Shape.
isScalar() - Method in class ai.djl.ndarray.types.Shape: Returns true if the NDArray is a scalar.
isSnapshot() - Method in class ai.djl.repository.Artifact: Returns true if the artifact is a snapshot.
isSnapshot() - Method in class ai.djl.repository.Version: Returns true if this is a snapshot version.
isSparse() - Method in interface ai.djl.ndarray.NDArray: Returns true if this NDArray is a SparseNDArray.
isSupported(Class<?>, Class<?>) - Method in class ai.djl.translate.DefaultTranslatorFactory: Returns if the input/output is supported by the TranslatorFactory.
isSupported(Class<?>, Class<?>) - Method in interface ai.djl.translate.TranslatorFactory: Returns if the input/output is supported by the TranslatorFactory.
isWhiteSpace(char) - Static method in class ai.djl.modality.nlp.NlpUtils: Check whether a character is is considered as a whitespace.
item(int) - Method in class ai.djl.modality.Classifications: Returns the item at a given index based on the order used to construct the Classifications.
item(int) - Method in class ai.djl.modality.cv.output.DetectedObjects: Returns the item at a given index based on the order used to construct the Classifications.
Item() - Constructor for class ai.djl.repository.Artifact.Item
items() - Method in class ai.djl.modality.Classifications: Returns a classification item for each potential class for the input.
iterateDataset(Dataset) - Method in class ai.djl.training.Trainer: Fetches an iterator that can iterate through the given Dataset.
iterator() - Method in class ai.djl.training.dataset.DataIterable

J

JarRepository - Class in ai.djl.repository: A JarRepository is a Repository contains an archive file from classpath.
Joint(double, double, double) - Constructor for class ai.djl.modality.cv.output.Joints.Joint: Constructs a Joint with given data.
Joints - Class in ai.djl.modality.cv.output: A result of all joints found during Human Pose Estimation on a single image.
Joints(List<Joints.Joint>) - Constructor for class ai.djl.modality.cv.output.Joints: Constructs the Joints with the provided joints.
Joints.Joint - Class in ai.djl.modality.cv.output: A joint that was detected using Human Pose Estimation on an image.

K

kernelShape - Variable in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder
kernelShape - Variable in class ai.djl.nn.convolutional.Convolution
kernelShape - Variable in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder
kernelShape - Variable in class ai.djl.nn.convolutional.Deconvolution
KILOBITS - ai.djl.metric.Unit
KILOBITS_PER_SECOND - ai.djl.metric.Unit
KILOBYTES - ai.djl.metric.Unit
KILOBYTES_PER_SECOND - ai.djl.metric.Unit

L

l1Loss() - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L1Loss with default weight and batch axis.
l1Loss(String) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L1Loss with default weight and batch axis.
l1Loss(String, float) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L1Loss with given weight and batch axis.
L1Loss - Class in ai.djl.training.loss: L1Loss calculates L1 loss between label and prediction.
L1Loss() - Constructor for class ai.djl.training.loss.L1Loss: Calculates L1 Loss between the label and prediction, a.k.a.
L1Loss(String) - Constructor for class ai.djl.training.loss.L1Loss: Calculates L1 Loss between the label and prediction, a.k.a.
L1Loss(String, float) - Constructor for class ai.djl.training.loss.L1Loss: Calculates L1 Loss between the label and prediction, a.k.a.
L1WeightDecay - Class in ai.djl.training.loss: L1WeightDecay calculates L1 penalty of a set of parameters.
L1WeightDecay(NDList) - Constructor for class ai.djl.training.loss.L1WeightDecay: Calculates L1 weight decay for regularization.
L1WeightDecay(String, NDList) - Constructor for class ai.djl.training.loss.L1WeightDecay: Calculates L1 weight decay for regularization.
L1WeightDecay(String, NDList, float) - Constructor for class ai.djl.training.loss.L1WeightDecay: Calculates L1 weight decay for regularization.
l1WeightedDecay(NDList) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L1WeightDecay with default weight and name.
l1WeightedDecay(String, float, NDList) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L1WeightDecay.
l1WeightedDecay(String, NDList) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L1WeightDecay with default weight.
l2Loss() - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L2Loss with default weight and batch axis.
l2Loss(String) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L2Loss with default weight and batch axis.
l2Loss(String, float) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L2Loss with given weight and batch axis.
L2Loss - Class in ai.djl.training.loss: Calculates L2Loss between label and prediction, a.k.a.
L2Loss() - Constructor for class ai.djl.training.loss.L2Loss: Calculate L2Loss between the label and prediction, a.k.a.
L2Loss(String) - Constructor for class ai.djl.training.loss.L2Loss: Calculate L2Loss between the label and prediction, a.k.a.
L2Loss(String, float) - Constructor for class ai.djl.training.loss.L2Loss: Calculates L2Loss between the label and prediction, a.k.a.
L2WeightDecay - Class in ai.djl.training.loss: L2WeightDecay calculates L2 penalty of a set of parameters.
L2WeightDecay(NDList) - Constructor for class ai.djl.training.loss.L2WeightDecay: Calculates L2 weight decay for regularization.
L2WeightDecay(String, NDList) - Constructor for class ai.djl.training.loss.L2WeightDecay: Calculates L2 weight decay for regularization.
L2WeightDecay(String, NDList, float) - Constructor for class ai.djl.training.loss.L2WeightDecay: Calculates L2 weight decay for regularization.
l2WeightedDecay(NDList) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L2WeightDecay with default weight and name.
l2WeightedDecay(String, float, NDList) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L2WeightDecay.
l2WeightedDecay(String, NDList) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of L2WeightDecay with default weight.
labelBatchifier - Variable in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder
labelBatchifier - Variable in class ai.djl.training.dataset.RandomAccessDataset
labels - Variable in class ai.djl.training.dataset.ArrayDataset
LambdaBlock - Class in ai.djl.nn: LambdaBlock is a Block with no parameters or children.
LambdaBlock(Function<NDList, NDList>) - Constructor for class ai.djl.nn.LambdaBlock: Creates a LambdaBlock that can apply the specified function.
LambdaProcessor - Class in ai.djl.modality.nlp.preprocess: TextProcessor will apply user defined lambda function on input tokens.
LambdaProcessor(Function<String, String>) - Constructor for class ai.djl.modality.nlp.preprocess.LambdaProcessor: Creates a LambdaProcessor and specify the function to apply.
Landmark - Class in ai.djl.modality.cv.output: Landmark is the container that stores the key points for landmark on a single face.
Landmark(double, double, double, double, List<Point>) - Constructor for class ai.djl.modality.cv.output.Landmark: Constructs a Landmark using a list of points.
large() - Method in class ai.djl.nn.transformer.BertBlock.Builder: Sets this builder's params to the LARGE config of the original BERT paper.
latestMetric(String) - Method in class ai.djl.metric.Metrics: Returns the latest Metric with the specified metric name.
layerNorm(NDArray, Shape, NDArray, NDArray, float) - Static method in class ai.djl.nn.norm.LayerNorm: Applies Layer Normalization with average and variance for each input sample across the axis dimensions.
LayerNorm - Class in ai.djl.nn.norm: Layer normalization works by normalizing the values of input data for each input sample to have mean of 0 and variance of 1.
LayerNorm.Builder - Class in ai.djl.nn.norm: The Builder to construct a LayerNorm.
LayoutType - Enum in ai.djl.ndarray.types: An enum to represent the meaning of a particular axis in an NDArray.
LazyNDArray - Interface in ai.djl.ndarray: An NDArray that waits to compute values until they are needed.
leakyRelu(NDArray, float) - Static method in class ai.djl.nn.Activation: Applies Leaky ReLU activation on the input NDArray.
leakyRelu(NDList, float) - Static method in class ai.djl.nn.Activation: Applies Leaky ReLU activation on the input singleton NDList.
leakyReluBlock(float) - Static method in class ai.djl.nn.Activation: Creates a LambdaBlock that applies the LeakyReLU activation function in its forward function.
License - Class in ai.djl.repository: A License is a container to save the license information.
License() - Constructor for class ai.djl.repository.License
licenses - Variable in class ai.djl.repository.Metadata
like() - Method in interface ai.djl.ndarray.NDArray: Returns an uninitialized NDArray with the same Shape, DataType and SparseFormat as the input NDArray.
limit - Variable in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder
limit - Variable in class ai.djl.training.dataset.RandomAccessDataset
linear(NDArray, NDArray) - Static method in class ai.djl.nn.core.Linear: Applies a linear transformation to the incoming data.
linear(NDArray, NDArray, NDArray) - Static method in class ai.djl.nn.core.Linear: Applies a linear transformation to the incoming data.
Linear - Class in ai.djl.nn.core: A Linear block applies a linear transformation \(Y = XW^T + b\).
LINEAR - ai.djl.training.tracker.WarmUpTracker.Mode
LINEAR_REGRESSION - Static variable in interface ai.djl.Application.Tabular: An application that takes a feature vector (table row) and predicts a numerical feature based on it.
Linear.Builder - Class in ai.djl.nn.core: The Builder to construct a Linear type of Block.
LinearTracker - Class in ai.djl.training.tracker: FactorTracker is an implementation of Tracker which is updated by a constant factor.
LinearTracker(LinearTracker.Builder) - Constructor for class ai.djl.training.tracker.LinearTracker: Creates a new instance of FactorTracker.
LinearTracker.Builder - Class in ai.djl.training.tracker: The Builder to construct an LinearTracker object.
linspace(float, float, int) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced numbers over a specified interval.
linspace(float, float, int, boolean) - Method in class ai.djl.ndarray.BaseNDManager: Returns evenly spaced numbers over a specified interval.
linspace(float, float, int, boolean) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced numbers over a specified interval.
linspace(float, float, int, boolean, Device) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced numbers over a specified interval.
linspace(int, int, int) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced numbers over a specified interval.
linspace(int, int, int, boolean) - Method in interface ai.djl.ndarray.NDManager: Returns evenly spaced numbers over a specified interval.
listArtifacts() - Method in class ai.djl.repository.MRL: Returns a list of artifacts in this resource.
listDirectory(Artifact.Item, String) - Method in class ai.djl.repository.AbstractRepository: Returns the list of files directly within a specified directory in a zipped directory item.
listDirectory(Artifact.Item, String) - Method in interface ai.djl.repository.Repository: Returns the list of files directly within a specified directory in a zipped directory item.
listModels() - Method in class ai.djl.repository.zoo.BaseModelLoader: Returns a list of the available artifacts that can be loaded.
listModels() - Method in interface ai.djl.repository.zoo.ModelLoader: Returns a list of the available artifacts that can be loaded.
listModels() - Static method in class ai.djl.repository.zoo.ModelZoo: Returns the available Application and their model artifact metadata.
listModels(Criteria<?, ?>) - Static method in class ai.djl.repository.zoo.ModelZoo: Returns the available Application and their model artifact metadata.
listModelZoo() - Static method in class ai.djl.repository.zoo.ModelZoo: Returns available model zoos.
load(Model) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.SynsetLoader
load(NDManager, DataInputStream) - Method in class ai.djl.nn.Parameter: Loads parameter NDArrays from InputStream.
load(InputStream) - Method in interface ai.djl.Model: Loads the model from the InputStream.
load(InputStream, Map<String, ?>) - Method in class ai.djl.BaseModel: Loads the model from the InputStream with the options provided.
load(InputStream, Map<String, ?>) - Method in interface ai.djl.Model: Loads the model from the InputStream with the options provided.
load(InputStream, Map<String, ?>) - Method in class ai.djl.repository.zoo.ZooModel: Loads the model from the InputStream with the options provided.
load(Path) - Method in interface ai.djl.Model: Loads the model from the modelPath.
load(Path) - Method in class ai.djl.ndarray.BaseNDManager: Loads the NDArrays saved to a file.
load(Path) - Method in interface ai.djl.ndarray.NDManager: Loads the NDArrays saved to a file.
load(Path, Device) - Method in interface ai.djl.ndarray.NDManager: Loads the NDArrays saved to a file.
load(Path, String) - Method in interface ai.djl.Model: Loads the model from the modelPath and the given name.
load(Path, String, Map<String, ?>) - Method in interface ai.djl.Model: Loads the model from the modelPath with the name and options provided.
load(Path, String, Map<String, ?>) - Method in class ai.djl.repository.zoo.ZooModel: Loads the model from the modelPath with the name and options provided.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.nn.AbstractBaseBlock: Overwrite this to load additional metadata with the parameter values.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.nn.convolutional.Convolution: Overwrite this to load additional metadata with the parameter values.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.nn.convolutional.Deconvolution: Overwrite this to load additional metadata with the parameter values.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.nn.core.Linear: Overwrite this to load additional metadata with the parameter values.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.nn.core.Prelu: Overwrite this to load additional metadata with the parameter values.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.nn.norm.BatchNorm: Overwrite this to load additional metadata with the parameter values.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.nn.norm.Dropout: Overwrite this to load additional metadata with the parameter values.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.nn.norm.LayerNorm: Overwrite this to load additional metadata with the parameter values.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.nn.ParallelBlock: Overwrite this to load additional metadata with the parameter values.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.nn.recurrent.RecurrentBlock: Overwrite this to load additional metadata with the parameter values.
loadMetadata(byte, DataInputStream) - Method in class ai.djl.nn.SequentialBlock: Overwrite this to load additional metadata with the parameter values.
loadModel() - Method in class ai.djl.repository.zoo.Criteria: Load the ZooModel that matches this criteria.
loadModel(Criteria<I, O>) - Method in class ai.djl.repository.zoo.BaseModelLoader: Loads the model with the given criteria.
loadModel(Criteria<I, O>) - Method in interface ai.djl.repository.zoo.ModelLoader: Loads the model with the given criteria.
loadModel(Criteria<I, O>) - Static method in class ai.djl.repository.zoo.ModelZoo: Load the ZooModel that matches this criteria.
loadParameters(NDManager, DataInputStream) - Method in class ai.djl.modality.nlp.Decoder: Loads the parameters from the given input stream.
loadParameters(NDManager, DataInputStream) - Method in class ai.djl.modality.nlp.Encoder: Loads the parameters from the given input stream.
loadParameters(NDManager, DataInputStream) - Method in class ai.djl.modality.nlp.EncoderDecoder: Loads the parameters from the given input stream.
loadParameters(NDManager, DataInputStream) - Method in class ai.djl.nn.AbstractBaseBlock: Loads the parameters from the given input stream.
loadParameters(NDManager, DataInputStream) - Method in interface ai.djl.nn.Block: Loads the parameters from the given input stream.
loadParameters(NDManager, DataInputStream) - Method in class ai.djl.nn.core.ConstantEmbedding: Loads the parameters from the given input stream.
loadParameters(NDManager, DataInputStream) - Method in class ai.djl.nn.core.Embedding: Loads the parameters from the given input stream.
loadParameters(NDManager, DataInputStream) - Method in class ai.djl.nn.LambdaBlock: Loads the parameters from the given input stream.
locale - Variable in class ai.djl.modality.nlp.translator.QATranslator
LocalParameterServer - Class in ai.djl.training: LocalParameterServer is an implementation of the ParameterServer interface.
LocalParameterServer(Optimizer) - Constructor for class ai.djl.training.LocalParameterServer: Create a new instance of LocalParameterServer for the given optimizer.
LocalRepository - Class in ai.djl.repository: A LocalRepository is a Repository located in a filesystem directory.
LocalRepository(String, URI, Path) - Constructor for class ai.djl.repository.LocalRepository: (Internal) Constructs a LocalRepository from the path with inferred name.
locate(MRL) - Method in class ai.djl.repository.JarRepository: Returns the metadata at a mrl.
locate(MRL) - Method in class ai.djl.repository.LocalRepository: Returns the metadata at a mrl.
locate(MRL) - Method in class ai.djl.repository.RemoteRepository: Returns the metadata at a mrl.
locate(MRL) - Method in interface ai.djl.repository.Repository: Returns the metadata at a mrl.
locate(MRL) - Method in class ai.djl.repository.SimpleRepository: Returns the metadata at a mrl.
locate(MRL) - Method in class ai.djl.repository.SimpleUrlRepository: Returns the metadata at a mrl.
log() - Method in interface ai.djl.ndarray.NDArray: Returns the natural logarithmic value of this NDArray element-wise.
log() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the natural logarithmic value of this NDArray element-wise.
log10() - Method in interface ai.djl.ndarray.NDArray: Returns the base 10 logarithm of this NDArray element-wise.
log10() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the base 10 logarithm of this NDArray element-wise.
log2() - Method in interface ai.djl.ndarray.NDArray: Returns the base 2 logarithm of this NDArray element-wise.
log2() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the base 2 logarithm of this NDArray element-wise.
logging() - Static method in interface ai.djl.training.listener.TrainingListener.Defaults: A default TrainingListener set including batch output logging.
logging(int) - Static method in interface ai.djl.training.listener.TrainingListener.Defaults: A default TrainingListener set including batch output logging.
logging(String) - Static method in interface ai.djl.training.listener.TrainingListener.Defaults: A default TrainingListener set including batch output logging and output directory.
LoggingTrainingListener - Class in ai.djl.training.listener: TrainingListener that outputs the progress of training each batch and epoch into logs.
LoggingTrainingListener() - Constructor for class ai.djl.training.listener.LoggingTrainingListener: Constructs a LoggingTrainingListener instance.
LoggingTrainingListener(int) - Constructor for class ai.djl.training.listener.LoggingTrainingListener: Constructs a LoggingTrainingListener instance with specified steps.
logicalAnd(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns the truth value of this NDArray AND the other NDArray element-wise.
logicalAnd(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the truth value of this NDArray AND the other NDArray element-wise.
logicalAnd(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the truth value of NDArray a AND NDArray b element-wise.
logicalNot() - Method in interface ai.djl.ndarray.NDArray: Computes the truth value of NOT this NDArray element-wise.
logicalNot() - Method in class ai.djl.ndarray.NDArrayAdapter: Computes the truth value of NOT this NDArray element-wise.
logicalOr(NDArray) - Method in interface ai.djl.ndarray.NDArray: Computes the truth value of this NDArray OR the other NDArray element-wise.
logicalOr(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Computes the truth value of this NDArray OR the other NDArray element-wise.
logicalOr(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Computes the truth value of NDArray a AND NDArray b element-wise.
logicalXor(NDArray) - Method in interface ai.djl.ndarray.NDArray: Computes the truth value of this NDArray XOR the other NDArray element-wise.
logicalXor(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Computes the truth value of this NDArray XOR the other NDArray element-wise.
logicalXor(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Computes the truth value of NDArray a AND NDArray b element-wise.
logSoftmax(int) - Method in interface ai.djl.ndarray.NDArray: Applies the softmax function followed by a logarithm.
logSoftmax(int) - Method in class ai.djl.ndarray.NDArrayAdapter: Applies the softmax function followed by a logarithm.
longValue(Map<String, ?>, String) - Static method in class ai.djl.translate.ArgumentsUtil: Returns the long value from the arguments.
longValue(Map<String, ?>, String, long) - Static method in class ai.djl.translate.ArgumentsUtil: Returns the long value from the arguments.
Loss - Class in ai.djl.training.loss: Loss functions (or Cost functions) are used to evaluate the model predictions against true labels for optimization.
Loss(String) - Constructor for class ai.djl.training.loss.Loss: Base class for metric with abstract update methods.
LowerCaseConvertor - Class in ai.djl.modality.nlp.preprocess: LowerCaseConvertor converts every character of the input tokens to it's respective lower case character.
LowerCaseConvertor() - Constructor for class ai.djl.modality.nlp.preprocess.LowerCaseConvertor: Creates a TextProcessor that converts input text into lower case character with the default english Locale.
LowerCaseConvertor(Locale) - Constructor for class ai.djl.modality.nlp.preprocess.LowerCaseConvertor: Creates a TextProcessor that converts input text into lower case character given the Locale.
lpPool1d(NDArray, float, Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Performs 1-D LP Pooling on the input.
lpPool1dBlock(float, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the lpPool1dBlock pooling function in its forward function.
lpPool1dBlock(float, Shape, Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the lpPool1dBlock pooling function in its forward function.
lpPool1dBlock(float, Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the lpPool1dBlock pooling function in its forward function.
lpPool2d(NDArray, float, Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Performs 2-D LP Pooling on the input.
lpPool2dBlock(float, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the lpPool2dBlock pooling function in its forward function.
lpPool2dBlock(float, Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the lpPool2dBlock pooling function in its forward function.
lpPool2dBlock(float, Shape, Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the lpPool2dBlock pooling function in its forward function.
lpPool2dBlock(float, Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the lpPool2dBlock pooling function in its forward function.
lpPool3d(NDArray, float, Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Performs 3-D LP Pooling on the input.
lpPool3dBlock(float, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the lpPool3dBlock pooling function in its forward function.
lpPool3dBlock(float, Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the LpPoo3D pooling function in its forward function.
lpPool3dBlock(float, Shape, Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the lpPool3dBlock pooling function in its forward function.
lpPool3dBlock(float, Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the lpPool3dBlock pooling function in its forward function.
LruReplayBuffer - Class in ai.djl.modality.rl: A simple ReplayBuffer that randomly selects across the whole buffer, but always removes the oldest items in the buffer once it is full.
LruReplayBuffer(int, int) - Constructor for class ai.djl.modality.rl.LruReplayBuffer: Constructs a LruReplayBuffer.
LSTM - Class in ai.djl.nn.recurrent: LSTM is an implementation of recurrent neural networks which applies Long Short-Term Memory recurrent layer to input.
LSTM.Builder - Class in ai.djl.nn.recurrent: The Builder to construct a LSTM type of Block.
lt(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Less" comparison.
lt(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Less" comparison.
lt(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Less" comparison.
lt(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Less" comparison.
lt(Number) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Less" comparison.
lt(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Less" comparison.
lt(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Less" comparison.
lte(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Less or equals" comparison.
lte(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Less or equals" comparison.
lte(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Less or equals" comparison.
lte(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Less or equals" comparison.
lte(Number) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Less or equals" comparison.
lte(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Less or equals" comparison.
lte(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Less or equals" comparison.

M

MACHINE_TRANSLATION - Static variable in interface ai.djl.Application.NLP: An application that translates text from one language to another.
MalformedModelException - Exception in ai.djl: Thrown to indicate Model parameters are not in expected format or are malformed.
MalformedModelException(String) - Constructor for exception ai.djl.MalformedModelException: Constructs a new exception with the specified detail message.
MalformedModelException(String, Throwable) - Constructor for exception ai.djl.MalformedModelException: Constructs a new exception with the specified detail message and cause.
MalformedModelException(Throwable) - Constructor for exception ai.djl.MalformedModelException: Constructs a new exception with the specified cause and a detail message of (cause==null ? null : cause.toString()) which typically contains the class and detail message of cause.
manager - Variable in class ai.djl.BaseModel
manager - Variable in class ai.djl.inference.Predictor
manager - Variable in class ai.djl.ndarray.NDArrayAdapter
map(Function<Pair<Long, LayoutType>, Pair<Long, LayoutType>>) - Method in class ai.djl.ndarray.types.Shape: Returns a mapped shape.
Mask - Class in ai.djl.modality.cv.output: A mask with a probability for each pixel within a bounding rectangle.
Mask(double, double, double, double, float[][]) - Constructor for class ai.djl.modality.cv.output.Mask: Constructs a Mask with the given data.
maskedSoftmaxCrossEntropyLoss() - Static method in class ai.djl.training.loss.Loss: Returns a new instance of MaskedSoftmaxCrossEntropyLoss with default arguments.
maskedSoftmaxCrossEntropyLoss(String) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of MaskedSoftmaxCrossEntropyLoss with default arguments.
maskedSoftmaxCrossEntropyLoss(String, float, int, boolean, boolean) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of MaskedSoftmaxCrossEntropyLoss with the given arguments.
MaskedSoftmaxCrossEntropyLoss - Class in ai.djl.training.loss: MaskedSoftmaxCrossEntropyLoss is an implementation of Loss that only considers a specific number of values for the loss computations, and masks the rest according to the given sequence.
MaskedSoftmaxCrossEntropyLoss() - Constructor for class ai.djl.training.loss.MaskedSoftmaxCrossEntropyLoss: Creates a new instance of SoftmaxCrossEntropyLoss with default parameters.
MaskedSoftmaxCrossEntropyLoss(String) - Constructor for class ai.djl.training.loss.MaskedSoftmaxCrossEntropyLoss: Creates a new instance of SoftmaxCrossEntropyLoss with default parameters.
MaskedSoftmaxCrossEntropyLoss(String, float, int, boolean, boolean) - Constructor for class ai.djl.training.loss.MaskedSoftmaxCrossEntropyLoss: Creates a new instance of MaskedSoftmaxCrossEntropyLoss with the given parameters.
match(Map<String, String>) - Method in class ai.djl.repository.MRL: Returns the first artifact that matches a given criteria.
MatchAllMetadata() - Constructor for class ai.djl.repository.Metadata.MatchAllMetadata: Creates a MatchAllMetadata instance.
matches(Application) - Method in class ai.djl.Application: Returns whether this application matches the test application set.
matches(List<Artifact>) - Method in class ai.djl.repository.VersionRange: Filters the provided artifacts to those that match the version range.
matMul(NDArray) - Method in interface ai.djl.ndarray.NDArray: Product matrix of this NDArray and the other NDArray.
matMul(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Product matrix of this NDArray and the other NDArray.
matMul(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Product matrix of this NDArray and the other NDArray.
max() - Method in interface ai.djl.ndarray.NDArray: Returns the maximum of this NDArray.
max() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the maximum of this NDArray.
max(int[]) - Method in interface ai.djl.ndarray.NDArray: Returns the maximum of this NDArray along given axes.
max(int[], boolean) - Method in interface ai.djl.ndarray.NDArray: Returns the maximum of this NDArray along given axes.
max(int[], boolean) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the maximum of this NDArray along given axes.
maximum(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns the maximum of this NDArray and the other NDArray element-wise.
maximum(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the maximum of this NDArray and the other NDArray element-wise.
maximum(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the maximum of NDArray a and NDArray b element-wise.
maximum(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Returns the maximum of a NDArray and a number element-wise.
maximum(Number) - Method in interface ai.djl.ndarray.NDArray: Returns the maximum of this NDArray and a number element-wise.
maximum(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the maximum of this NDArray and a number element-wise.
maximum(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the maximum of a number and a NDArray element-wise.
maxLabels - Variable in class ai.djl.modality.nlp.translator.QATranslator
maxLength - Variable in class ai.djl.modality.nlp.translator.QATranslator
maxPool1d(NDArray, Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Performs 1-D Max Pooling on the input.
maxPool1dBlock(Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool1dBlock pooling function in its forward function.
maxPool1dBlock(Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool1dBlock pooling function in its forward function.
maxPool1dBlock(Shape, Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool1dBlock pooling function in its forward function.
maxPool1dBlock(Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool1d pooling function in its forward function.
maxPool2d(NDArray, Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Performs 2-D Max Pooling on the input.
maxPool2dBlock(Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool2dBlock pooling function in its forward function.
maxPool2dBlock(Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool2dBlock pooling function in its forward function.
maxPool2dBlock(Shape, Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool2dBlock pooling function in its forward function.
maxPool2dBlock(Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool2dBlock pooling function in its forward function.
maxPool3d(NDArray, Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Performs 3-D Max Pooling on the input.
maxPool3dBlock(Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool3dBlock pooling function in its forward function.
maxPool3dBlock(Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool3dBlock pooling function in its forward function.
maxPool3dBlock(Shape, Shape, Shape) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool3dBlock pooling function in its forward function.
maxPool3dBlock(Shape, Shape, Shape, boolean) - Static method in class ai.djl.nn.pooling.Pool: Creates a LambdaBlock that applies the maxPool3dBlock pooling function in its forward function.
md5hash(String) - Static method in class ai.djl.repository.AbstractRepository
mean() - Method in interface ai.djl.ndarray.NDArray: Returns the average of this NDArray.
mean() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the average of this NDArray.
mean(int[]) - Method in interface ai.djl.ndarray.NDArray: Returns the average of this NDArray along given axes.
mean(int[], boolean) - Method in interface ai.djl.ndarray.NDArray: Returns the average of this NDArray along given axes.
mean(int[], boolean) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the average of this NDArray along given axes.
mean(String) - Method in class ai.djl.metric.Metrics: Returns the average value of the specified metric.
median() - Method in interface ai.djl.ndarray.NDArray: Returns median value for this NDArray.
median() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns median value for this NDArray.
median(int[]) - Method in interface ai.djl.ndarray.NDArray: Returns median value along given axes.
median(int[]) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns median value along given axes.
MEGABITS - ai.djl.metric.Unit
MEGABITS_PER_SECOND - ai.djl.metric.Unit
MEGABYTES - ai.djl.metric.Unit
MEGABYTES_PER_SECOND - ai.djl.metric.Unit
MemoryTrainingListener - Class in ai.djl.training.listener: TrainingListener that collects the memory usage information.
MemoryTrainingListener() - Constructor for class ai.djl.training.listener.MemoryTrainingListener: Constructs a MemoryTrainingListener that does not output data to a file.
MemoryTrainingListener(String) - Constructor for class ai.djl.training.listener.MemoryTrainingListener: Constructs a MemoryTrainingListener that outputs data in the given directory.
Metadata - Class in ai.djl.repository: A Metadata is a collection of Artifacts with unified metadata (including MRL) that are stored in the same "metadata.json" file.
Metadata() - Constructor for class ai.djl.repository.Metadata
Metadata.MatchAllMetadata - Class in ai.djl.repository: A Metadata class that matches all any search criteria.
Metric - Class in ai.djl.metric: A class representing a single recorded Metric value.
Metric(String, Number) - Constructor for class ai.djl.metric.Metric: Constructs a Metric instance with the specified metricName and value.
Metric(String, Number, Unit) - Constructor for class ai.djl.metric.Metric: Constructs a Metric instance with the specified metricName, value, and unit.
Metric(String, Number, Unit, Dimension...) - Constructor for class ai.djl.metric.Metric: Constructs a Metric instance with the specified metricName, value, and unit.
metricName(Evaluator, String) - Static method in class ai.djl.training.listener.EvaluatorTrainingListener: Returns the metric created with the evaluator for the given stage.
metrics - Variable in class ai.djl.inference.Predictor
Metrics - Class in ai.djl.metric: A collection of Metric objects organized by metric name.
Metrics() - Constructor for class ai.djl.metric.Metrics: Constructs an empty Metrics instance.
micro() - Method in class ai.djl.nn.transformer.BertBlock.Builder: Sets this builder's params to a minimal configuration that nevertheless performs quite well.
MICROSECONDS - ai.djl.metric.Unit
MILLISECONDS - ai.djl.metric.Unit
min() - Method in interface ai.djl.ndarray.NDArray: Returns the minimum of this NDArray.
min() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the minimum of this NDArray.
min(int[]) - Method in interface ai.djl.ndarray.NDArray: Returns the minimum of this NDArray along given axes.
min(int[], boolean) - Method in interface ai.djl.ndarray.NDArray: Returns the minimum of this NDArray along given axes.
min(int[], boolean) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the minimum of this NDArray along given axes.
minimum(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns the minimum of this NDArray and the other NDArray element-wise.
minimum(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the minimum of this NDArray and the other NDArray element-wise.
minimum(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the minimum of NDArray a and NDArray b element-wise.
minimum(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Returns the minimum of a NDArray and a number element-wise.
minimum(Number) - Method in interface ai.djl.ndarray.NDArray: Returns the minimum of this NDArray and a number element-wise.
minimum(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the minimum of this NDArray and a number element-wise.
minimum(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the minimum of a number and a NDArray element-wise.
MinMaxScaler - Class in ai.djl.training.util: Transform arrays by scaling each value to a given range.
MinMaxScaler() - Constructor for class ai.djl.training.util.MinMaxScaler
mish(NDArray) - Static method in class ai.djl.nn.Activation: Applies Mish activation on the input NDArray.
mish(NDList) - Static method in class ai.djl.nn.Activation: Applies Mish activation on the input singleton NDList.
mishBlock() - Static method in class ai.djl.nn.Activation: Creates a LambdaBlock that applies the Mish activation function in its forward function.
MissingOps - Class in ai.djl.nn.transformer: Operators missing from NDArray that are necessary to implement Bert pretraining.
MKL - Static variable in class ai.djl.engine.StandardCapabilities
MKLDNN - Static variable in class ai.djl.engine.StandardCapabilities
mod(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns element-wise remainder of division.
mod(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns element-wise remainder of division.
mod(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns element-wise remainder of division.
mod(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Returns element-wise remainder of division.
mod(Number) - Method in interface ai.djl.ndarray.NDArray: Returns element-wise remainder of division.
mod(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns element-wise remainder of division.
mod(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns element-wise remainder of division.
model(Application, String, String) - Method in interface ai.djl.repository.Repository: Creates a model MRL with specified application.
model(Application, String, String, String) - Method in interface ai.djl.repository.Repository: Creates a model MRL with specified application.
model(Application, String, String, String, String) - Method in interface ai.djl.repository.Repository: Creates a model MRL with specified application.
model(Repository, Application, String, String, String, String) - Static method in class ai.djl.repository.MRL: Creates a model MRL with specified application.
Model - Interface in ai.djl: A model is a collection of artifacts that is created by the training process.
modelDir - Variable in class ai.djl.BaseModel
ModelException - Exception in ai.djl: Thrown to indicate Model parameter or load exceptions parent to Model Exceptions.
ModelException(String) - Constructor for exception ai.djl.ModelException: Constructs a new exception with the specified detail message.
ModelException(String, Throwable) - Constructor for exception ai.djl.ModelException: Constructs a new exception with the specified detail message and cause.
ModelException(Throwable) - Constructor for exception ai.djl.ModelException: Constructs a new exception with the specified cause and a detail message of (cause==null ? null : cause.toString()) which typically contains the class and detail message of cause.
ModelLoader - Interface in ai.djl.repository.zoo: A ModelLoader loads a particular ZooModel from a Repository for a model zoo.
modelName - Variable in class ai.djl.BaseModel
ModelNotFoundException - Exception in ai.djl.repository.zoo: Thrown when an application tries to load a model from repository search path.
ModelNotFoundException(String) - Constructor for exception ai.djl.repository.zoo.ModelNotFoundException: Constructs a new exception with the specified detail message.
ModelNotFoundException(String, Throwable) - Constructor for exception ai.djl.repository.zoo.ModelNotFoundException: Constructs a new exception with the specified detail message and cause.
ModelNotFoundException(Throwable) - Constructor for exception ai.djl.repository.zoo.ModelNotFoundException: Constructs a new exception with the specified cause and a detail message of (cause==null ? null : cause.toString()) (which typically contains the class and detail message of cause).
ModelZoo - Class in ai.djl.repository.zoo: An interface represents a collection of models.
ModelZoo() - Constructor for class ai.djl.repository.zoo.ModelZoo
ModelZooTextEmbedding - Class in ai.djl.modality.nlp.embedding: A WordEmbedding using a ZooModel.
ModelZooTextEmbedding(Model) - Constructor for class ai.djl.modality.nlp.embedding.ModelZooTextEmbedding: Constructs a ModelZooTextEmbedding.
modi(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns in place element-wise remainder of division in place.
modi(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns in place element-wise remainder of division in place.
modi(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns element-wise remainder of division.
modi(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Returns element-wise remainder of division in place.
modi(Number) - Method in interface ai.djl.ndarray.NDArray: Returns element-wise remainder of division in place.
modi(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns element-wise remainder of division in place.
modi(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns element-wise remainder of division in place.
mrl - Variable in class ai.djl.repository.zoo.BaseModelLoader
MRL - Class in ai.djl.repository: The MRL (Machine learning Resource Locator) is a pointer to a Metadata "resource" on a machine learning Repository.
mul(NDArray) - Method in interface ai.djl.ndarray.NDArray: Multiplies this NDArray by other NDArrays element-wise.
mul(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Multiplies this NDArray by other NDArrays element-wise.
mul(NDArray...) - Static method in class ai.djl.ndarray.NDArrays: Multiplies all of the NDArrays together element-wise.
mul(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Multiplies the NDArray by a number element-wise.
mul(Number) - Method in interface ai.djl.ndarray.NDArray: Multiplies this NDArray by a number element-wise.
mul(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Multiplies this NDArray by a number element-wise.
mul(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Multiplies a number by a NDArray element-wise.
muli(NDArray) - Method in interface ai.djl.ndarray.NDArray: Multiplies this NDArray by other NDArray element-wise in place.
muli(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Multiplies this NDArray by other NDArray element-wise in place.
muli(NDArray...) - Static method in class ai.djl.ndarray.NDArrays: Multiplies all of the NDArrays together element-wise in place.
muli(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Multiplies the NDArray by a number element-wise in place.
muli(Number) - Method in interface ai.djl.ndarray.NDArray: Multiplies this NDArray by a number element-wise in place.
muli(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Multiplies this NDArray by a number element-wise in place.
muli(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Multiplies a number by a NDArray element-wise.
MultiBoxDetection - Class in ai.djl.modality.cv: MultiBoxDetection is the class that takes the output of a multi-box detection model, and converts it into an NDList that contains the object detections.
MultiBoxDetection(MultiBoxDetection.Builder) - Constructor for class ai.djl.modality.cv.MultiBoxDetection: Creates a new instance of MultiBoxDetection with the arguments from the given MultiBoxDetection.Builder.
MultiBoxDetection.Builder - Class in ai.djl.modality.cv: The Builder to construct a MultiBoxDetection object.
MultiBoxPrior - Class in ai.djl.modality.cv: MultiBoxPrior is the class that generates anchor boxes that act as priors for object detection.
MultiBoxPrior(MultiBoxPrior.Builder) - Constructor for class ai.djl.modality.cv.MultiBoxPrior: Creates a new instance of MultiBoxPrior with the arguments from the given MultiBoxPrior.Builder.
MultiBoxPrior.Builder - Class in ai.djl.modality.cv: The Builder to construct a MultiBoxPrior object.
MultiBoxTarget - Class in ai.djl.modality.cv: MultiBoxTarget is the class that computes the training targets for training a Single Shot Detection (SSD) models.
MultiBoxTarget(MultiBoxTarget.Builder) - Constructor for class ai.djl.modality.cv.MultiBoxTarget: Creates a new instance of MultiBoxTarget with the arguments from the given MultiBoxTarget.Builder.
MultiBoxTarget.Builder - Class in ai.djl.modality.cv: The Builder to construct a MultiBoxTarget object.
multiFactor() - Static method in interface ai.djl.training.tracker.Tracker: Returns a new instance of MultiFactorTracker.Builder that can build an MultiFactorTracker.
MultiFactorTracker - Class in ai.djl.training.tracker: MultiFactorTracker is an implementation of Tracker which returns piecewise constant values for fixed numbers of steps.
MultiFactorTracker(MultiFactorTracker.Builder) - Constructor for class ai.djl.training.tracker.MultiFactorTracker: Creates a new instance of MultiFactorTracker.
MultiFactorTracker.Builder - Class in ai.djl.training.tracker: The Builder to construct an MultiFactorTracker object.
MULTIPLE_CHOICE - Static variable in interface ai.djl.Application.NLP: An application to represent a multiple choice question.

N

nag() - Static method in class ai.djl.training.optimizer.Optimizer: Returns a new instance of Nag.Builder that can build an Nag optimizer.
Nag - Class in ai.djl.training.optimizer: Nag is a Nesterov accelerated gradient optimizer.
Nag(Nag.Builder) - Constructor for class ai.djl.training.optimizer.Nag: Creates a new instance of Nag optimizer.
Nag.Builder - Class in ai.djl.training.optimizer: The Builder to construct an Nag object.
name - Variable in class ai.djl.ndarray.BaseNDManager
name - Variable in class ai.djl.ndarray.NDArrayAdapter
name - Variable in class ai.djl.repository.AbstractRepository
name - Variable in class ai.djl.training.hyperparameter.param.Hyperparameter
nano() - Method in class ai.djl.nn.transformer.BertBlock.Builder: Tiny config for testing on laptops.
NDArray - Interface in ai.djl.ndarray: An interface representing an n-dimensional array.
NDArrayAdapter - Class in ai.djl.ndarray: A base implementation of the NDArray that does nothing.
NDArrayAdapter(NDManager, NDManager, Shape, DataType, String) - Constructor for class ai.djl.ndarray.NDArrayAdapter
NDArrayIndexer - Class in ai.djl.ndarray.index: A helper class for NDArray implementations for operations with an NDIndex.
NDArrayIndexer() - Constructor for class ai.djl.ndarray.index.NDArrayIndexer
NDArrays - Class in ai.djl.ndarray: This class contains various methods for manipulating NDArrays.
NDArraySupplier - Interface in ai.djl.translate: Represents a supplier of NDArray.
NDImageUtils - Class in ai.djl.modality.cv.util: NDImageUtils is an image processing utility to load, reshape, and convert images using NDArray images.
NDIndex - Class in ai.djl.ndarray.index: The NDIndex allows you to specify a subset of an NDArray that can be used for fetching or updating.
NDIndex() - Constructor for class ai.djl.ndarray.index.NDIndex: Creates an empty NDIndex to append values to.
NDIndex(long...) - Constructor for class ai.djl.ndarray.index.NDIndex: Creates an NDIndex with the given indices as specified values on the NDArray.
NDIndex(String, Object...) - Constructor for class ai.djl.ndarray.index.NDIndex: Creates a NDIndex given the index values.
NDIndexAll - Class in ai.djl.ndarray.index.dim: An NDIndexElement to return all values in a particular dimension.
NDIndexAll() - Constructor for class ai.djl.ndarray.index.dim.NDIndexAll
NDIndexBooleans - Class in ai.djl.ndarray.index.dim: An NDIndexElement to return values based on a mask binary NDArray.
NDIndexBooleans(NDArray) - Constructor for class ai.djl.ndarray.index.dim.NDIndexBooleans: Constructs a NDIndexBooleans instance with specified mask binary NDArray.
NDIndexElement - Interface in ai.djl.ndarray.index.dim: An index for particular dimensions created by NDIndex.
NDIndexFixed - Class in ai.djl.ndarray.index.dim: An NDIndexElement that returns only a specific value in the corresponding dimension.
NDIndexFixed(long) - Constructor for class ai.djl.ndarray.index.dim.NDIndexFixed: Constructs a NDIndexFixed instance with specified dimension.
NDIndexFullPick - Class in ai.djl.ndarray.index.full: A simplified representation of a pick-based NDIndex.
NDIndexFullSlice - Class in ai.djl.ndarray.index.full: An index as a slice on all dimensions where some dimensions can be squeezed.
NDIndexPick - Class in ai.djl.ndarray.index.dim: An NDIndexElement that gets elements by index in the specified axis.
NDIndexPick(NDArray) - Constructor for class ai.djl.ndarray.index.dim.NDIndexPick: Constructs a pick.
NDIndexSlice - Class in ai.djl.ndarray.index.dim: An NDIndexElement that returns a range of values in the specified dimension.
NDIndexSlice(Long, Long, Long) - Constructor for class ai.djl.ndarray.index.dim.NDIndexSlice: Constructs a NDIndexSlice instance with specified range and step.
NDList - Class in ai.djl.ndarray: An NDList represents a sequence of NDArrays with names.
NDList() - Constructor for class ai.djl.ndarray.NDList: Constructs an empty NDList.
NDList(int) - Constructor for class ai.djl.ndarray.NDList: Constructs an empty NDList with the specified initial capacity.
NDList(NDArray...) - Constructor for class ai.djl.ndarray.NDList: Constructs and initiates an NDList with the specified NDArrays.
NDList(Collection<NDArray>) - Constructor for class ai.djl.ndarray.NDList: Constructs and initiates an NDList with the specified NDArrays.
NDManager - Interface in ai.djl.ndarray: NDArray managers are used to create NDArrays (n-dimensional array on native engine).
NDResource - Interface in ai.djl.ndarray: An object which is managed by an NDManager and tracks the manager it is attached to.
NDUtils - Class in ai.djl.ndarray: A class containing utility methods for NDArray operations.
NEAREST - ai.djl.modality.cv.Image.Interpolation
neg() - Method in interface ai.djl.ndarray.NDArray: Returns the numerical negative NDArray element-wise.
neg() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the numerical negative NDArray element-wise.
negi() - Method in interface ai.djl.ndarray.NDArray: Returns the numerical negative NDArray element-wise in place.
negi() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the numerical negative NDArray element-wise in place.
neq(NDArray) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Not equals" comparison.
neq(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Not equals" comparison.
neq(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Not equals" comparison.
neq(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Not equals" comparison.
neq(Number) - Method in interface ai.djl.ndarray.NDArray: Returns the boolean NDArray for element-wise "Not equals" comparison.
neq(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the boolean NDArray for element-wise "Not equals" comparison.
neq(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns the boolean NDArray for element-wise "Not equals" comparison.
newBaseManager() - Method in class ai.djl.engine.Engine: Creates a new top-level NDManager.
newBaseManager() - Static method in interface ai.djl.ndarray.NDManager: Creates a new top-level NDManager.
newBaseManager(Device) - Method in class ai.djl.engine.Engine: Creates a new top-level NDManager with specified Device.
newBaseManager(Device) - Static method in interface ai.djl.ndarray.NDManager: Creates a new top-level NDManager with specified Device.
newBaseManager(Device, String) - Static method in interface ai.djl.ndarray.NDManager: Creates a new top-level NDManager with specified Device and engine.
newBlock(Model, Path, Map<String, ?>) - Method in interface ai.djl.nn.BlockFactory: Constructs the uninitialized block.
newGradientCollector() - Method in class ai.djl.engine.Engine: Returns a new instance of GradientCollector.
newGradientCollector() - Method in class ai.djl.training.Trainer: Returns a new instance of GradientCollector.
newInstance(NDManager) - Static method in interface ai.djl.nn.SymbolBlock: Creates an empty SymbolBlock instance.
newInstance(Class<?>, Class<?>, Model, Map<String, ?>) - Method in class ai.djl.modality.cv.translator.BigGANTranslatorFactory: Returns a new instance of the Translator class.
newInstance(Class<?>, Class<?>, Model, Map<String, ?>) - Method in class ai.djl.modality.cv.translator.ImageClassificationTranslatorFactory: Returns a new instance of the Translator class.
newInstance(Class<?>, Class<?>, Model, Map<String, ?>) - Method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslatorFactory: Returns a new instance of the Translator class.
newInstance(Class<?>, Class<?>, Model, Map<String, ?>) - Method in class ai.djl.modality.cv.translator.SimplePoseTranslatorFactory: Returns a new instance of the Translator class.
newInstance(Class<?>, Class<?>, Model, Map<String, ?>) - Method in class ai.djl.modality.cv.translator.SingleShotDetectionTranslatorFactory: Returns a new instance of the Translator class.
newInstance(Class<?>, Class<?>, Model, Map<String, ?>) - Method in class ai.djl.modality.cv.translator.StyleTransferTranslatorFactory: Returns a new instance of the Translator class.
newInstance(Class<?>, Class<?>, Model, Map<String, ?>) - Method in class ai.djl.modality.cv.translator.YoloTranslatorFactory: Returns a new instance of the Translator class.
newInstance(Class<?>, Class<?>, Model, Map<String, ?>) - Method in class ai.djl.modality.cv.translator.YoloV5TranslatorFactory: Returns a new instance of the Translator class.
newInstance(Class<?>, Class<?>, Model, Map<String, ?>) - Method in class ai.djl.translate.DefaultTranslatorFactory: Returns a new instance of the Translator class.
newInstance(Class<?>, Class<?>, Model, Map<String, ?>) - Method in class ai.djl.translate.ServingTranslatorFactory: Returns a new instance of the Translator class.
newInstance(Class<?>, Class<?>, Model, Map<String, ?>) - Method in interface ai.djl.translate.TranslatorFactory: Returns a new instance of the Translator class.
newInstance(String) - Static method in interface ai.djl.Model: Creates an empty model instance.
newInstance(String, Device) - Static method in interface ai.djl.Model: Creates an empty model instance on the specified Device.
newInstance(String, Device, String) - Static method in interface ai.djl.Model: Creates an empty model instance on the specified Device and engine.
newInstance(String, String) - Static method in interface ai.djl.Model: Creates an empty model instance on the specified Device and engine.
newInstance(String, String) - Static method in interface ai.djl.repository.Repository: Creates a new instance of a repository with a name and url.
newInstance(String, URI) - Method in interface ai.djl.repository.RepositoryFactory: Creates a new instance of a repository with a name and url.
newInstance(String, Path) - Static method in interface ai.djl.repository.Repository: Creates a new instance of a repository with a name and url.
newModel(String, Device) - Method in class ai.djl.engine.Engine: Constructs a new model.
newParameterServer(Optimizer) - Method in class ai.djl.engine.Engine: Returns a new instance of ParameterServer.
newPredictor() - Method in class ai.djl.repository.zoo.ZooModel: Creates a new Predictor based on the model with the default translator.
newPredictor(Device) - Method in class ai.djl.repository.zoo.ZooModel: Creates a new Predictor based on the model with the default translator and a specified device.
newPredictor(Translator<I, O>) - Method in interface ai.djl.Model: Creates a new Predictor based on the model on the current device.
newPredictor(Translator<I, O>, Device) - Method in class ai.djl.BaseModel: Creates a new Predictor based on the model.
newPredictor(Translator<I, O>, Device) - Method in interface ai.djl.Model: Creates a new Predictor based on the model.
newPredictor(Translator<P, Q>, Device) - Method in class ai.djl.repository.zoo.ZooModel: Creates a new Predictor based on the model.
newSubManager() - Method in class ai.djl.ndarray.BaseNDManager: Creates a child NDManager.
newSubManager() - Method in interface ai.djl.ndarray.NDManager: Creates a child NDManager.
newSubManager(Device) - Method in interface ai.djl.ndarray.NDManager: Creates a child NDManager with specified default Device.
newSymbolBlock(NDManager) - Method in class ai.djl.engine.Engine: Construct an empty SymbolBlock for loading.
newTrainer(TrainingConfig) - Method in class ai.djl.BaseModel: Creates a new Trainer instance for a Model.
newTrainer(TrainingConfig) - Method in interface ai.djl.Model: Creates a new Trainer instance for a Model.
newTrainer(TrainingConfig) - Method in class ai.djl.repository.zoo.ZooModel: Creates a new Trainer instance for a Model.
next() - Method in class ai.djl.training.dataset.DataIterable
nextConfig() - Method in interface ai.djl.training.hyperparameter.optimizer.HpOptimizer: Returns the next hyperparameters to test.
nextConfig() - Method in class ai.djl.training.hyperparameter.optimizer.HpORandom: Returns the next hyperparameters to test.
NlpUtils - Class in ai.djl.modality.nlp: Utility functions for processing String and Characters in NLP problems.
nms(List<YoloV5Translator.IntermediateResult>) - Method in class ai.djl.modality.cv.translator.YoloV5Translator
NoBatchifyTranslator<I,O> - Interface in ai.djl.translate: A Translator that does not use a Batchifier.
none() - Method in interface ai.djl.ndarray.NDArray: Returns true if none of the elements within this NDArray are non-zero or true.
NONE - ai.djl.metric.Unit
nonzero() - Method in interface ai.djl.ndarray.NDArray: Returns the indices of elements that are non-zero.
nonzero() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the indices of elements that are non-zero.
NoopTranslator - Class in ai.djl.translate: A no operational Translator implementation.
NoopTranslator() - Constructor for class ai.djl.translate.NoopTranslator: Constructs a NoopTranslator.
NoopTranslator(Batchifier) - Constructor for class ai.djl.translate.NoopTranslator: Constructs a NoopTranslator with the given Batchifier.
norm() - Method in interface ai.djl.ndarray.NDArray: Returns the norm of this NDArray.
norm(boolean) - Method in interface ai.djl.ndarray.NDArray: Returns the norm of this NDArray.
norm(boolean) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the norm of this NDArray.
norm(int[]) - Method in interface ai.djl.ndarray.NDArray: Returns the norm of this NDArray.
norm(int[], boolean) - Method in interface ai.djl.ndarray.NDArray: Returns the norm of this NDArray.
norm(int, int[], boolean) - Method in interface ai.djl.ndarray.NDArray: Returns the norm of this NDArray.
norm(int, int[], boolean) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the norm of this NDArray.
NormalInitializer - Class in ai.djl.training.initializer: NormalInitializer initializes weights with random values sampled from a normal distribution with a mean of zero and standard deviation of sigma.
NormalInitializer() - Constructor for class ai.djl.training.initializer.NormalInitializer: Creates an instance of NormalInitializer with a default sigma of 0.01.
NormalInitializer(float) - Constructor for class ai.djl.training.initializer.NormalInitializer: Creates a Normal initializer.
normalize(NDArray, float[], float[]) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Normalizes an image NDArray of shape CHW or NCHW with mean and standard deviation.
normalize(NDArray, float, float) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Normalizes an image NDArray of shape CHW or NCHW with a single mean and standard deviation to apply to all channels.
Normalize - Class in ai.djl.modality.cv.transform: A Transform that normalizes an image NDArray of shape CHW or NCHW.
Normalize(float[], float[]) - Constructor for class ai.djl.modality.cv.transform.Normalize: Creates a Normalize Transform that normalizes.
normalizeDefault(String) - Static method in class ai.djl.modality.nlp.preprocess.UnicodeNormalizer: Normalizes a String using a sensible default normal form.
normalizeHyphens(String) - Static method in class ai.djl.modality.nlp.preprocess.HyphenNormalizer: Replaces hyphen like codepoints by ASCII "-", removes soft hyphens.
notifyListeners(Consumer<TrainingListener>) - Method in class ai.djl.training.Trainer: Executes a method on each of the TrainingListeners.
numChannels() - Method in enum ai.djl.modality.cv.Image.Flag: Returns the number of channels for this flag.
numDimensions() - Method in class ai.djl.nn.convolutional.Conv1d: Returns the number of dimensions of the input.
numDimensions() - Method in class ai.djl.nn.convolutional.Conv1dTranspose: Returns the number of dimensions of the input.
numDimensions() - Method in class ai.djl.nn.convolutional.Conv2d: Returns the number of dimensions of the input.
numDimensions() - Method in class ai.djl.nn.convolutional.Conv2dTranspose: Returns the number of dimensions of the input.
numDimensions() - Method in class ai.djl.nn.convolutional.Conv3d: Returns the number of dimensions of the input.
numDimensions() - Method in class ai.djl.nn.convolutional.Convolution: Returns the number of dimensions of the input.
numDimensions() - Method in class ai.djl.nn.convolutional.Deconvolution: Returns the number of dimensions of the input.
numEmbeddings - Variable in class ai.djl.nn.core.Embedding.BaseBuilder
numEmbeddings - Variable in class ai.djl.nn.core.Embedding
numEpochs(HpSet) - Method in class ai.djl.training.hyperparameter.EasyHpo: Returns the number of epochs to train for the current hyperparameter set.
numHyperParameterTests() - Method in class ai.djl.training.hyperparameter.EasyHpo: Returns the number of hyperparameter sets to train with.
numLayers - Variable in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder
numLayers - Variable in class ai.djl.nn.recurrent.RecurrentBlock

O

OBJECT_DETECTION - Static variable in interface ai.djl.Application.CV: An application that finds zero or more objects in an image, the object class (see image classification), and their locations as a BoundingBox.
ObjectDetectionBuilder() - Constructor for class ai.djl.modality.cv.translator.ObjectDetectionTranslator.ObjectDetectionBuilder
ObjectDetectionTranslator - Class in ai.djl.modality.cv.translator: A BaseImageTranslator that post-process the NDArray into DetectedObjects with boundaries.
ObjectDetectionTranslator(ObjectDetectionTranslator.ObjectDetectionBuilder<?>) - Constructor for class ai.djl.modality.cv.translator.ObjectDetectionTranslator: Creates the ObjectDetectionTranslator from the given builder.
ObjectDetectionTranslator.ObjectDetectionBuilder<T extends ObjectDetectionTranslator.ObjectDetectionBuilder> - Class in ai.djl.modality.cv.translator: The base builder for the object detection translator.
ObjectDetectionTranslatorFactory - Class in ai.djl.modality.cv.translator: An abstract TranslatorFactory that creates a ObjectDetectionTranslator instance.
ObjectDetectionTranslatorFactory() - Constructor for class ai.djl.modality.cv.translator.ObjectDetectionTranslatorFactory
of(String) - Static method in class ai.djl.Application: Converts a path string to a Application.
of(String, int) - Static method in class ai.djl.Device: Returns a Device with device type and device id.
oneHot(int) - Method in interface ai.djl.ndarray.NDArray: Returns a one-hot NDArray.
oneHot(int, float, float, DataType) - Method in interface ai.djl.ndarray.NDArray: Returns a one-hot NDArray.
oneHot(int, float, float, DataType) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns a one-hot NDArray.
oneHot(int, DataType) - Method in interface ai.djl.ndarray.NDArray: Returns a one-hot NDArray.
onEpoch(Trainer) - Method in class ai.djl.training.listener.EpochTrainingListener: Listens to the end of an epoch during training.
onEpoch(Trainer) - Method in class ai.djl.training.listener.EvaluatorTrainingListener: Listens to the end of an epoch during training.
onEpoch(Trainer) - Method in class ai.djl.training.listener.LoggingTrainingListener: Listens to the end of an epoch during training.
onEpoch(Trainer) - Method in class ai.djl.training.listener.SaveModelTrainingListener: Listens to the end of an epoch during training.
onEpoch(Trainer) - Method in class ai.djl.training.listener.TimeMeasureTrainingListener: Listens to the end of an epoch during training.
onEpoch(Trainer) - Method in interface ai.djl.training.listener.TrainingListener: Listens to the end of an epoch during training.
onEpoch(Trainer) - Method in class ai.djl.training.listener.TrainingListenerAdapter: Listens to the end of an epoch during training.
ones(Shape) - Method in interface ai.djl.ndarray.NDManager: Creates an instance of NDArray with specified Shape filled with ones.
ones(Shape, DataType) - Method in class ai.djl.ndarray.BaseNDManager: Creates an instance of NDArray with specified Shape filled with ones.
ones(Shape, DataType) - Method in interface ai.djl.ndarray.NDManager: Creates an instance of NDArray with specified Shape filled with ones.
ones(Shape, DataType, Device) - Method in interface ai.djl.ndarray.NDManager: Creates an instance of NDArray with specified Device, Shape, and DataType filled with ones.
ONES - Static variable in interface ai.djl.training.initializer.Initializer
onesLike() - Method in interface ai.djl.ndarray.NDArray: Returns an NDArray of ones with the same Shape, DataType and SparseFormat as the input NDArray.
onTrainingBatch(Trainer, TrainingListener.BatchData) - Method in class ai.djl.training.listener.DivergenceCheckTrainingListener: Listens to the end of training one batch of data during training.
onTrainingBatch(Trainer, TrainingListener.BatchData) - Method in class ai.djl.training.listener.EvaluatorTrainingListener: Listens to the end of training one batch of data during training.
onTrainingBatch(Trainer, TrainingListener.BatchData) - Method in class ai.djl.training.listener.LoggingTrainingListener: Listens to the end of training one batch of data during training.
onTrainingBatch(Trainer, TrainingListener.BatchData) - Method in class ai.djl.training.listener.MemoryTrainingListener: Listens to the end of training one batch of data during training.
onTrainingBatch(Trainer, TrainingListener.BatchData) - Method in class ai.djl.training.listener.TimeMeasureTrainingListener: Listens to the end of training one batch of data during training.
onTrainingBatch(Trainer, TrainingListener.BatchData) - Method in interface ai.djl.training.listener.TrainingListener: Listens to the end of training one batch of data during training.
onTrainingBatch(Trainer, TrainingListener.BatchData) - Method in class ai.djl.training.listener.TrainingListenerAdapter: Listens to the end of training one batch of data during training.
onTrainingBegin(Trainer) - Method in class ai.djl.training.listener.EpochTrainingListener: Listens to the beginning of training.
onTrainingBegin(Trainer) - Method in class ai.djl.training.listener.EvaluatorTrainingListener: Listens to the beginning of training.
onTrainingBegin(Trainer) - Method in class ai.djl.training.listener.LoggingTrainingListener: Listens to the beginning of training.
onTrainingBegin(Trainer) - Method in interface ai.djl.training.listener.TrainingListener: Listens to the beginning of training.
onTrainingBegin(Trainer) - Method in class ai.djl.training.listener.TrainingListenerAdapter: Listens to the beginning of training.
onTrainingEnd(Trainer) - Method in class ai.djl.training.listener.EpochTrainingListener: Listens to the end of training.
onTrainingEnd(Trainer) - Method in class ai.djl.training.listener.LoggingTrainingListener: Listens to the end of training.
onTrainingEnd(Trainer) - Method in class ai.djl.training.listener.MemoryTrainingListener: Listens to the end of training.
onTrainingEnd(Trainer) - Method in class ai.djl.training.listener.SaveModelTrainingListener: Listens to the end of training.
onTrainingEnd(Trainer) - Method in class ai.djl.training.listener.TimeMeasureTrainingListener: Listens to the end of training.
onTrainingEnd(Trainer) - Method in interface ai.djl.training.listener.TrainingListener: Listens to the end of training.
onTrainingEnd(Trainer) - Method in class ai.djl.training.listener.TrainingListenerAdapter: Listens to the end of training.
onValidationBatch(Trainer, TrainingListener.BatchData) - Method in class ai.djl.training.listener.EvaluatorTrainingListener: Listens to the end of validating one batch of data during validation.
onValidationBatch(Trainer, TrainingListener.BatchData) - Method in class ai.djl.training.listener.LoggingTrainingListener: Listens to the end of validating one batch of data during validation.
onValidationBatch(Trainer, TrainingListener.BatchData) - Method in class ai.djl.training.listener.MemoryTrainingListener: Listens to the end of validating one batch of data during validation.
onValidationBatch(Trainer, TrainingListener.BatchData) - Method in class ai.djl.training.listener.TimeMeasureTrainingListener: Listens to the end of validating one batch of data during validation.
onValidationBatch(Trainer, TrainingListener.BatchData) - Method in interface ai.djl.training.listener.TrainingListener: Listens to the end of validating one batch of data during validation.
onValidationBatch(Trainer, TrainingListener.BatchData) - Method in class ai.djl.training.listener.TrainingListenerAdapter: Listens to the end of validating one batch of data during validation.
OPENMP - Static variable in class ai.djl.engine.StandardCapabilities
openStream(Artifact.Item, String) - Method in class ai.djl.repository.AbstractRepository: Returns an InputStream for an item in a repository.
openStream(Artifact.Item, String) - Method in interface ai.djl.repository.Repository: Returns an InputStream for an item in a repository.
optApplication(Application) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets the model application for this criteria.
optApplySoftmax(boolean) - Method in class ai.djl.modality.cv.translator.ImageClassificationTranslator.Builder: Sets whether to apply softmax when processing output.
optArgument(String, Object) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets the optional model loading argument for this criteria.
optArguments(Map<String, Object>) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets an extra model loading argument for this criteria.
optArray(NDArray) - Method in class ai.djl.nn.Parameter.Builder: Sets the array of the Parameter.
optArtifactId(String) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets optional artifactId of the ModelLoader for this criteria.
optAttentionHeadCount(int) - Method in class ai.djl.nn.transformer.BertBlock.Builder: Sets the number of attention heads to use in each transformer block.
optAttentionProbsDropoutProb(float) - Method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock.Builder: Sets the probability of applying dropout to the attention probability distribution.
optAxis(int) - Method in class ai.djl.nn.norm.BatchNorm.Builder: Set the axis in which channel is specified.
optBackgroundId(int) - Method in class ai.djl.modality.cv.MultiBoxDetection.Builder: Sets the class ID for the background.
optBatchFirst(boolean) - Method in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder: Sets the optional batchFirst flag that indicates whether the input is batch major or not.
optBatchifier(Batchifier) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder: Sets the Batchifier for the Translator.
optBatchifier(Batchifier) - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder: Sets the Batchifier for the Translator.
optBeginNumUpdate(int) - Method in class ai.djl.training.optimizer.Optimizer.OptimizerBuilder: Sets the initial value of the number of updates.
optBeta1(float) - Method in class ai.djl.training.optimizer.Adam.Builder: Sets the decay rate for the first moment estimates.
optBeta2(float) - Method in class ai.djl.training.optimizer.Adam.Builder: Sets the decay rate for the second moment estimates.
optBias(boolean) - Method in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder: Sets the optional parameter of whether to include a bias vector.
optBias(boolean) - Method in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder: Sets the optional parameter of whether to include a bias vector.
optBias(boolean) - Method in class ai.djl.nn.core.Linear.Builder: Sets the optional parameter that indicates whether to include a bias vector with default value of true.
optBidirectional(boolean) - Method in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder: Sets the optional parameter that indicates whether to use bidirectional recurrent layers.
optBlock(Block) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets an optional model Block for this criteria.
optCenter(boolean) - Method in class ai.djl.nn.norm.BatchNorm.Builder: If True, add offset of `beta` to normalized tensor.
optCenter(boolean) - Method in class ai.djl.nn.norm.LayerNorm.Builder: If True, add offset of `beta` to normalized tensor.
optCentered(boolean) - Method in class ai.djl.training.optimizer.RmsProp.Builder: Sets which version of RMSProp to use.
optClip(boolean) - Method in class ai.djl.modality.cv.MultiBoxDetection.Builder: Sets the boolean parameter that indicates whether to clip out-of-boundary boxes.
optClip(boolean) - Method in class ai.djl.modality.cv.MultiBoxPrior.Builder: Sets the boolean parameter that indicates whether to clip out-of-boundary boxes.
optClipGrad(float) - Method in class ai.djl.training.optimizer.Optimizer.OptimizerBuilder: Sets the value of the \(clipGrad\).
optDataBatchifier(Batchifier) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Sets the Batchifier for the data.
optDefaultItem(T) - Method in class ai.djl.nn.core.Embedding.BaseBuilder: Sets whether to use a default item's embedding for undefined items.
optDevice(Device) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets the Device for this criteria.
optDevice(Device) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Sets the Device.
optDevices(Device[]) - Method in class ai.djl.training.DefaultTrainingConfig: Sets the array of Device available for training.
optDilation(Shape) - Method in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder: Sets the dilation along each dimension.
optDilation(Shape) - Method in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder: Sets the dilation along each dimension.
optDropRate(float) - Method in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder: Sets the drop rate of the dropout on the outputs of each RNN layer, except the last layer.
optEmbeddingSize(int) - Method in class ai.djl.nn.transformer.BertBlock.Builder: Sets the embedding size to use for input tokens.
optEngine(String) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets the engine name for this criteria.
optEpsilon(float) - Method in class ai.djl.nn.norm.BatchNorm.Builder: Sets the epsilon value to prevent division by 0.
optEpsilon(float) - Method in class ai.djl.nn.norm.LayerNorm.Builder: Sets the epsilon value to prevent division by 0.
optEpsilon(float) - Method in class ai.djl.training.optimizer.Adadelta.Builder: Sets \(epsilon\) - a small quantity for numerical stability.
optEpsilon(float) - Method in class ai.djl.training.optimizer.Adagrad.Builder: Sets \(epsilon\) - a small quantity for numerical stability.
optEpsilon(float) - Method in class ai.djl.training.optimizer.Adam.Builder: Sets \(epsilon\) - a small quantity for numerical stability.
optEpsilon(float) - Method in class ai.djl.training.optimizer.RmsProp.Builder: Sets \(epsilon\) - a small quantity for numerical stability.
optExecutorService() - Method in class ai.djl.training.DefaultTrainingConfig: Sets the ExecutorService with the global ForkJoinPool.commonPool().
optExecutorService(ExecutorService) - Method in class ai.djl.training.DefaultTrainingConfig: Sets the ExecutorService to train with multiple threads.
optFactor(float) - Method in class ai.djl.training.tracker.MultiFactorTracker.Builder: Set the value of the multiplicative factor.
optFallthrough(AbstractIndexedEmbedding<T>) - Method in class ai.djl.nn.core.Embedding.BaseBuilder: Sets a custom handler for items not found in the embedding.
optFilter(String, String) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets an extra search filter for this criteria.
optFilters(Map<String, String>) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets the extra search filters for this criteria.
optFinalValue(float) - Method in class ai.djl.training.tracker.CosineTracker.Builder: Sets the final value that the learning rate will remain constant as after the specified max number of updates.
optFlag(Image.Flag) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder: Sets the optional Image.Flag (default is Image.Flag.COLOR).
optForceSuppress(boolean) - Method in class ai.djl.modality.cv.MultiBoxDetection.Builder: Sets the boolean parameter that indicates whether to suppress all detections regardless of class_id.
optGroupId(String) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets optional groupId of the ModelZoo for this criteria.
optGroups(int) - Method in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder: Sets the number of group partitions.
optGroups(int) - Method in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder: Sets the number of group partitions.
optHasBiases(boolean) - Method in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder: Sets the optional biases flag that indicates whether to use biases or not.
optHiddenDropoutProbability(float) - Method in class ai.djl.nn.transformer.BertBlock.Builder: Sets the dropout probabilty in the hidden fully connected networks.
optHiddenSize(int) - Method in class ai.djl.nn.transformer.BertBlock.Builder: Sets the size of the hidden layers in the fully connected networks used.
optIgnoreLabel(float) - Method in class ai.djl.modality.cv.MultiBoxTarget.Builder: Sets the label for ignored anchors.
Optimizer - Class in ai.djl.training.optimizer: An Optimizer updates the weight parameters to minimize the loss function.
Optimizer(Optimizer.OptimizerBuilder<?>) - Constructor for class ai.djl.training.optimizer.Optimizer: Creates a new instance of Optimizer.
Optimizer.OptimizerBuilder<T extends Optimizer.OptimizerBuilder> - Class in ai.djl.training.optimizer: The Builder to construct an Optimizer.
OptimizerBuilder() - Constructor for class ai.djl.training.optimizer.Optimizer.OptimizerBuilder
optIncludeTokenTypes(boolean) - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder: Sets the if include token types for the Translator.
optIncludeValidLengths(boolean) - Method in class ai.djl.translate.PaddingStackBatchifier.Builder: Sets whether to include the valid lengths (length of non-padded data) for each array.
optInitializer(Initializer) - Method in class ai.djl.nn.Parameter.Builder: Sets the Initializer of the Parameter.
optInitializer(Initializer, Parameter.Type) - Method in class ai.djl.training.DefaultTrainingConfig: Sets the Initializer to use for the parameters (default from paper).
optInitializer(Initializer, String) - Method in class ai.djl.training.DefaultTrainingConfig: Sets the Initializer to use for the parameters (default from paper).
optInitializer(Initializer, Predicate<Parameter>) - Method in class ai.djl.training.DefaultTrainingConfig: Sets the Initializer to use for the parameters (default from paper).
optIouThreshold(float) - Method in class ai.djl.modality.cv.MultiBoxTarget.Builder: Sets the anchor-GroundTruth overlap threshold to be regarded as a positive match.
optLabelBatchifier(Batchifier) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Sets the Batchifier for the labels.
optLabels(NDArray...) - Method in class ai.djl.training.dataset.ArrayDataset.Builder: Sets the labels for the data in the ArrayDataset.
optLearningRateTracker(Tracker) - Method in class ai.djl.training.optimizer.Adagrad.Builder: Sets the Tracker for this optimizer.
optLearningRateTracker(Tracker) - Method in class ai.djl.training.optimizer.Adam.Builder: Sets the Tracker for this optimizer.
optLearningRateTracker(Tracker) - Method in class ai.djl.training.optimizer.RmsProp.Builder: Sets the Tracker for this optimizer.
optLimit(long) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Sets this dataset's limit.
optLocale(String) - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder: Sets the name of the locale for the Translator.
optMaxEdge(int) - Method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslator.Builder: Sets the maximum edge length of the rescaled image.
optMaxLabels(int) - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder: Sets the max number of labels for the Translator.
optMaxLength(int) - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder: Sets the max number of tokens for the Translator.
optMaxSequenceLength(int) - Method in class ai.djl.nn.transformer.BertBlock.Builder: Sets the maximum sequence length this model can process.
optMaxTokens(int) - Method in class ai.djl.modality.nlp.DefaultVocabulary.Builder: Sets the optional limit on the size of the vocabulary.
optMaxUpdates(int) - Method in class ai.djl.training.tracker.FactorTracker.Builder: Sets the maximum number of updates after which the value should remain constant.
optMaxUpdates(int) - Method in class ai.djl.training.tracker.LinearTracker.Builder: Sets the maximum number of updates after which the value should remain constant.
optMaxValue(float) - Method in class ai.djl.training.tracker.LinearTracker.Builder: Sets the maximum value for a positive slope.
optMinFrequency(int) - Method in class ai.djl.modality.nlp.DefaultVocabulary.Builder: Sets the optional parameter that specifies the minimum frequency to consider a token to be part of the DefaultVocabulary.
optMinNegativeSamples(int) - Method in class ai.djl.modality.cv.MultiBoxTarget.Builder: Sets the minimum number of negative samples.
optMinValue(float) - Method in class ai.djl.training.tracker.FactorTracker.Builder: Sets the minimum value.
optMinValue(float) - Method in class ai.djl.training.tracker.LinearTracker.Builder: Sets the minimum value for a negative slope.
optModelName(String) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets an optional model name for this criteria.
optModelPath(Path) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets the optional model path of the ModelLoader for this criteria.
optModelUrls(String) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets optional model urls of the ModelLoader for this criteria.
optModelZoo(ModelZoo) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets optional ModelZoo of the ModelLoader for this criteria.
optMomentum(float) - Method in class ai.djl.nn.norm.BatchNorm.Builder: Set the momentum for moving average.
optMomentum(float) - Method in class ai.djl.training.optimizer.RmsProp.Builder: Sets the momentum factor.
optMomentum(float) - Method in class ai.djl.training.optimizer.Sgd.Builder: Sets the momentum for Sgd.
optNegativeMinigRatio(float) - Method in class ai.djl.modality.cv.MultiBoxTarget.Builder: Sets the max negative to positive samples ratio.
optNegativeMiningThreshold(float) - Method in class ai.djl.modality.cv.MultiBoxTarget.Builder: Sets the threshold used for negative mining.
optNmsThreshold(float) - Method in class ai.djl.modality.cv.MultiBoxDetection.Builder: Sets the non-maximum suppression(NMS) threshold.
optNmsThreshold(float) - Method in class ai.djl.modality.cv.translator.YoloV5Translator.Builder: Sets the NMS threshold.
optNmsTopK(int) - Method in class ai.djl.modality.cv.MultiBoxDetection.Builder: Sets the boolean parameter that indicates whether to clip out-of-boundary boxes.
optNumEmbeddings(int) - Method in class ai.djl.nn.core.Embedding.BaseBuilder: Sets the size of the dictionary of embeddings.
optOffsets(List<Float>) - Method in class ai.djl.modality.cv.MultiBoxPrior.Builder: Sets the value of the center-box offsets across \(x\) and \(y\) dimensions.
optOptimizer(Optimizer) - Method in class ai.djl.training.DefaultTrainingConfig: Sets the Optimizer used during training (default Adam).
optOption(String, String) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets the optional model loading option for this criteria.
optOptions(Map<String, String>) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets the model loading options for this criteria.
optOutPadding(Shape) - Method in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder: Sets the out_padding along each dimension.
optOutputType(YoloV5Translator.YoloOutputType) - Method in class ai.djl.modality.cv.translator.YoloV5Translator.Builder: Sets the YoloOutputType.
optPadding(boolean) - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder: Sets the if pad the tokens for the Translator.
optPadding(Shape) - Method in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder: Sets the padding along each dimension.
optPadding(Shape) - Method in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder: Sets the padding along each dimension.
optPipeline(Pipeline) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Sets the Pipeline of Transform to be applied on the data.
optPower(float) - Method in class ai.djl.training.tracker.PolynomialDecayTracker.Builder: Sets the power of the polynomial to decay by.
optPrefetchNumber(int) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Sets the number of batches to prefetch at once.
optProgress(Progress) - Method in class ai.djl.repository.zoo.Criteria.Builder: Set the optional Progress.
optRange(float, float) - Method in class ai.djl.training.util.MinMaxScaler: Sets desired range of transformed data.
optRate(float) - Method in class ai.djl.nn.norm.Dropout.Builder: Sets the probability or the fraction of the input that gets dropped out during training time.
optRequiresGrad(boolean) - Method in class ai.djl.nn.Parameter.Builder: Sets if the Parameter requires gradient.
optRescaleSize(double, double) - Method in class ai.djl.modality.cv.translator.ObjectDetectionTranslator.ObjectDetectionBuilder: Sets the optional rescale size.
optReservedTokens(Collection<String>) - Method in class ai.djl.modality.nlp.DefaultVocabulary.Builder: Sets the optional parameter that sets the list of reserved tokens.
optReturnState(boolean) - Method in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder: Sets the optional flag that indicates whether to return state or not.
optRho(float) - Method in class ai.djl.training.optimizer.Adadelta.Builder: Sets the rho for Adadelta.
optRho(float) - Method in class ai.djl.training.optimizer.RmsProp.Builder: Sets the decay factor for the moving average over the past squared gradient.
optScale(boolean) - Method in class ai.djl.nn.norm.BatchNorm.Builder: If True, multiply result by `gamma`.
optScale(boolean) - Method in class ai.djl.nn.norm.LayerNorm.Builder: If True, multiply result by `gamma`.
optShape(Shape) - Method in class ai.djl.nn.Parameter.Builder: Sets the shape of the Parameter.
optShortEdge(int) - Method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslator.Builder: Sets the shorter edge length of the rescaled image.
optSlope(float) - Method in class ai.djl.training.tracker.LinearTracker.Builder: Sets the value of the linear slope.
optSparseFormat(SparseFormat) - Method in class ai.djl.nn.core.Embedding.BaseBuilder: Sets the optional parameter whether to compute row sparse gradient in the backward calculation.
optSteps(List<Float>) - Method in class ai.djl.modality.cv.MultiBoxPrior.Builder: Sets the step across \(x\) and \(y\) dimensions.
optStride(Shape) - Method in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder: Sets the stride of the convolution.
optStride(Shape) - Method in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder: Sets the stride of the deconvolution.
optSynset(List<String>) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.ClassificationBuilder: Sets the potential classes for an image.
optSynsetArtifactName(String) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.ClassificationBuilder: Sets the name of the synset file listing the potential classes for an image.
optSynsetUrl(String) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.ClassificationBuilder: Sets the URL of the synset file.
optTargetPipeline(Pipeline) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Sets the Pipeline of Transform to be applied on the labels.
optThreshold(float) - Method in class ai.djl.modality.cv.MultiBoxDetection.Builder: Sets the threshold score for a detection to be a positive prediction.
optThreshold(float) - Method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslator.Builder: Sets the threshold for prediction accuracy.
optThreshold(float) - Method in class ai.djl.modality.cv.translator.ObjectDetectionTranslator.ObjectDetectionBuilder: Sets the threshold for prediction accuracy.
optThreshold(float) - Method in class ai.djl.modality.cv.translator.SimplePoseTranslator.Builder: Sets the threshold for prediction accuracy.
optTokenizer(String) - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder: Sets the name of the tokenizer for the Translator.
optToLowerCase(boolean) - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder: Sets the if convert text to lower case for the Translator.
optTopK(int) - Method in class ai.djl.modality.cv.translator.ImageClassificationTranslator.Builder: Set the topK number of classes to be displayed.
optTransformerBlockCount(int) - Method in class ai.djl.nn.transformer.BertBlock.Builder: Sets the number of transformer blocks to use.
optTranslator(Translator<I, O>) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets the optional Translator to override default Translator.
optTranslatorFactory(TranslatorFactory) - Method in class ai.djl.repository.zoo.Criteria.Builder: Sets the optional TranslatorFactory to override default Translator.
optTruncation(boolean) - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder: Sets the if truncate the tokens for the Translator.
optTypeDictionarySize(int) - Method in class ai.djl.nn.transformer.BertBlock.Builder: Sets the number of possible token types.
optUnknownToken() - Method in class ai.djl.modality.nlp.DefaultVocabulary.Builder: Sets the optional parameter that specifies the unknown token's string value with ">unk<".
optUnknownToken(String) - Method in class ai.djl.modality.nlp.DefaultVocabulary.Builder: Sets the optional parameter that specifies the unknown token's string value.
optUnknownToken(String) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding.Builder: Sets the optional String value for the unknown token.
optUseDefault(boolean) - Method in class ai.djl.nn.core.Embedding.BaseBuilder: Sets whether to use a default embedding for undefined items (default true).
optVocab(String) - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder: Sets the name of the vocabulary file for the Translator.
optWarmUpBeginValue(float) - Method in class ai.djl.training.tracker.WarmUpTracker.Builder: Sets the value at the beginning of warm-up mode.
optWarmUpMode(WarmUpTracker.Mode) - Method in class ai.djl.training.tracker.WarmUpTracker.Builder: Sets the WarmUpTracker.Mode for the WarmUpTracker.
optWarmUpSteps(int) - Method in class ai.djl.training.tracker.WarmUpTracker.Builder: Sets the number of steps until the point the value is updated in warm-up mode.
optWeightDecays(float) - Method in class ai.djl.training.optimizer.Optimizer.OptimizerBuilder: Sets the value of weight decay.
OTHER - ai.djl.nn.Parameter.Type
OUT - ai.djl.training.initializer.XavierInitializer.FactorType
outPadding - Variable in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder
outPadding - Variable in class ai.djl.nn.convolutional.Deconvolution
Output - Class in ai.djl.modality: A class stores the generic inference results.
Output() - Constructor for class ai.djl.modality.Output: Constructs a Output instance.
Output(int, String) - Constructor for class ai.djl.modality.Output: Constructs a Output with specified requestId, code and message.
overlap(double, double, double, double) - Method in class ai.djl.modality.cv.translator.YoloV5Translator

P

pad(List<E>, E, int) - Method in class ai.djl.modality.nlp.bert.BertTokenizer: Pads the tokens to the required length.
padding - Variable in class ai.djl.modality.nlp.translator.QATranslator
padding - Variable in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder
padding - Variable in class ai.djl.nn.convolutional.Convolution
padding - Variable in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder
padding - Variable in class ai.djl.nn.convolutional.Deconvolution
PaddingStackBatchifier - Class in ai.djl.translate: The padding stack batchifier is a StackBatchifier that also pads elements to reach the same length.
PaddingStackBatchifier.Builder - Class in ai.djl.translate: Builder to build a PaddingStackBatchifier.
ParallelBlock - Class in ai.djl.nn: ParallelBlock is a Block whose children form a parallel branch in the network and are combined to produce a single output.
ParallelBlock(Function<List<NDList>, NDList>) - Constructor for class ai.djl.nn.ParallelBlock: Creates a parallel block whose branches are combined to form a single output by the given function.
ParallelBlock(Function<List<NDList>, NDList>, List<Block>) - Constructor for class ai.djl.nn.ParallelBlock: Creates a parallel block whose branches are formed by each block in the list of blocks, and are combined to form a single output by the given function.
Parameter - Class in ai.djl.nn: Parameter is a container class that holds a learnable parameter of a model.
Parameter.Builder - Class in ai.djl.nn: A Builder to construct a Parameter.
Parameter.Type - Enum in ai.djl.nn: Enumerates the types of Parameter.
ParameterList - Class in ai.djl.nn: Represents a set of names and Parameters.
ParameterList() - Constructor for class ai.djl.nn.ParameterList: Create an empty ParameterList.
ParameterList(int) - Constructor for class ai.djl.nn.ParameterList: Constructs an empty ParameterList with the specified initial capacity.
ParameterList(List<Pair<String, Parameter>>) - Constructor for class ai.djl.nn.ParameterList: Constructs a ParameterList containing the elements of the specified list of Pairs.
ParameterList(List<String>, List<Parameter>) - Constructor for class ai.djl.nn.ParameterList: Constructs a ParameterList containing the elements of the specified keys and values.
ParameterList(Map<String, Parameter>) - Constructor for class ai.djl.nn.ParameterList: Constructs a ParameterList containing the elements of the specified map.
parameters - Variable in class ai.djl.nn.AbstractBlock: All direct parameters of this Block.
ParameterServer - Interface in ai.djl.training: An interface for a key-value store to store parameters, and their corresponding gradients.
parameterStore - Variable in class ai.djl.inference.Predictor
ParameterStore - Class in ai.djl.training: The ParameterStore contains a map from a parameter to the mirrors of it on other devices.
ParameterStore() - Constructor for class ai.djl.training.ParameterStore: Constructs a new ParameterStore instance.
ParameterStore(NDManager, boolean) - Constructor for class ai.djl.training.ParameterStore: Constructs an empty ParameterStore.
paramPathResolver(String, Map<String, ?>) - Method in class ai.djl.BaseModel
parent - Variable in class ai.djl.ndarray.BaseNDManager
parse(String) - Static method in class ai.djl.metric.Metric: Returns a Metric instance parsed from the log string.
parse(String) - Static method in class ai.djl.repository.VersionRange: Creates a new version range from a string version range.
PERCENT - ai.djl.metric.Unit
percentile(Number) - Method in interface ai.djl.ndarray.NDArray: Returns percentile for this NDArray.
percentile(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns percentile for this NDArray.
percentile(Number, int[]) - Method in interface ai.djl.ndarray.NDArray: Returns median along given dimension(s).
percentile(Number, int[]) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns median along given dimension(s).
percentile(String, int) - Method in class ai.djl.metric.Metrics: Returns a percentile Metric object for the specified metric name.
pipeline - Variable in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder
pipeline - Variable in class ai.djl.modality.cv.translator.BaseImageTranslator
pipeline - Variable in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder
pipeline - Variable in class ai.djl.training.dataset.RandomAccessDataset
Pipeline - Class in ai.djl.translate: Pipeline allows applying multiple transforms on an input NDList.
Pipeline() - Constructor for class ai.djl.translate.Pipeline: Creates a new instance of Pipeline that has no Transform defined yet.
Pipeline(Transform...) - Constructor for class ai.djl.translate.Pipeline: Creates a new instance of Pipeline that can apply the given transforms on its input.
Point - Class in ai.djl.modality.cv.output: A point representing a location in (x,y) coordinate space, specified in double precision.
Point(double, double) - Constructor for class ai.djl.modality.cv.output.Point: Constructs and initializes a point at the specified (x,y) location in the coordinate space.
PointwiseFeedForwardBlock - Class in ai.djl.nn.transformer: Fully connected Feed-Forward network, only applied to the last dimension of the input.
PointwiseFeedForwardBlock(List<Integer>, int, Function<NDList, NDList>) - Constructor for class ai.djl.nn.transformer.PointwiseFeedForwardBlock: Creates a pointwise feed-forward block.
PolynomialDecayTracker - Class in ai.djl.training.tracker: Polynomial decay Tracker.
PolynomialDecayTracker(PolynomialDecayTracker.Builder) - Constructor for class ai.djl.training.tracker.PolynomialDecayTracker: Builds a PolynomialDecayTracker.
PolynomialDecayTracker.Builder - Class in ai.djl.training.tracker: Builder for PolynomialDecayTracker.
Pool - Class in ai.djl.nn.pooling: Utility class that provides Block and methods for different pooling functions.
POSE_ESTIMATION - Static variable in interface ai.djl.Application.CV: An application that accepts an image of a single person and returns the Joints locations of the person.
PostProcessor<O> - Interface in ai.djl.translate: An interface that provides post-processing functionality.
pow(NDArray) - Method in interface ai.djl.ndarray.NDArray: Takes the power of this NDArray with the other NDArray element-wise.
pow(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Takes the power of this NDArray with the other NDArray element-wise.
pow(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Takes the power of a NDArray with a NDArray element-wise.
pow(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Takes the power of the NDArray with a number element-wise.
pow(Number) - Method in interface ai.djl.ndarray.NDArray: Takes the power of this NDArray with a number element-wise.
pow(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Takes the power of this NDArray with a number element-wise.
pow(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Takes the power of a number with a NDArray element-wise.
powi(NDArray) - Method in interface ai.djl.ndarray.NDArray: Takes the power of this NDArray with the other NDArray element-wise in place.
powi(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Takes the power of this NDArray with the other NDArray element-wise in place.
powi(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Takes the power of a NDArray with a NDArray element-wise.
powi(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Takes the power of the NDArray with a number element-wise in place.
powi(Number) - Method in interface ai.djl.ndarray.NDArray: Takes the power of this NDArray with a number element-wise in place.
powi(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Takes the power of this NDArray with a number element-wise in place.
powi(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Takes the power of a number with a NDArray element-wise in place.
predict(I) - Method in class ai.djl.inference.Predictor: Predicts an item for inference.
predictInternal(TranslatorContext, NDList) - Method in class ai.djl.inference.Predictor: Predicts an item for inference.
Predictor<I,O> - Class in ai.djl.inference: The Predictor interface provides a session for model inference.
Predictor(Model, Translator<I, O>, Device, boolean) - Constructor for class ai.djl.inference.Predictor: Creates a new instance of BasePredictor with the given Model and Translator.
prefetchNumber - Variable in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder
prefetchNumber - Variable in class ai.djl.training.dataset.RandomAccessDataset
prelu(NDArray, NDArray) - Static method in class ai.djl.nn.core.Prelu: Applies a Prelu activation on the input NDArray.
Prelu - Class in ai.djl.nn.core: Applies Leaky Parametric ReLU activation element-wise to the input.
Prelu() - Constructor for class ai.djl.nn.core.Prelu: Creates a Parametric ReLU Block.
preluBlock() - Static method in class ai.djl.nn.Activation: Returns a Prelu block.
prepare() - Method in interface ai.djl.training.dataset.Dataset: Prepares the dataset for use.
prepare(Shape[]) - Method in class ai.djl.nn.AbstractBaseBlock: Sets the shape of Parameters.
prepare(Shape[]) - Method in class ai.djl.nn.convolutional.Convolution: Sets the shape of Parameters.
prepare(Shape[]) - Method in class ai.djl.nn.convolutional.Deconvolution: Sets the shape of Parameters.
prepare(Shape[]) - Method in class ai.djl.nn.core.Embedding: Sets the shape of Parameters.
prepare(Shape[]) - Method in class ai.djl.nn.core.Linear: Sets the shape of Parameters.
prepare(Shape[]) - Method in class ai.djl.nn.norm.BatchNorm: Sets the shape of Parameters.
prepare(Shape[]) - Method in class ai.djl.nn.norm.LayerNorm: Sets the shape of Parameters.
prepare(Shape[]) - Method in class ai.djl.nn.recurrent.RecurrentBlock: Sets the shape of Parameters.
prepare(Artifact) - Method in class ai.djl.repository.MRL: Prepares the artifact for use.
prepare(Artifact) - Method in interface ai.djl.repository.Repository: Prepares the artifact for use.
prepare(Artifact, Progress) - Method in class ai.djl.repository.AbstractRepository: Prepares the artifact for use with progress tracking.
prepare(Artifact, Progress) - Method in class ai.djl.repository.MRL: Prepares the artifact for use with progress tracking.
prepare(Artifact, Progress) - Method in interface ai.djl.repository.Repository: Prepares the artifact for use with progress tracking.
prepare(Artifact, Progress) - Method in class ai.djl.repository.SimpleRepository: Prepares the artifact for use with progress tracking.
prepare(TranslatorContext) - Method in class ai.djl.modality.cv.translator.ImageClassificationTranslator: Prepares the translator with the manager and model to use.
prepare(TranslatorContext) - Method in class ai.djl.modality.cv.translator.ImageServingTranslator: Prepares the translator with the manager and model to use.
prepare(TranslatorContext) - Method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslator: Prepares the translator with the manager and model to use.
prepare(TranslatorContext) - Method in class ai.djl.modality.cv.translator.ObjectDetectionTranslator: Prepares the translator with the manager and model to use.
prepare(TranslatorContext) - Method in class ai.djl.modality.cv.translator.wrapper.FileTranslator: Prepares the translator with the manager and model to use.
prepare(TranslatorContext) - Method in class ai.djl.modality.cv.translator.wrapper.InputStreamTranslator: Prepares the translator with the manager and model to use.
prepare(TranslatorContext) - Method in class ai.djl.modality.cv.translator.wrapper.UrlTranslator: Prepares the translator with the manager and model to use.
prepare(TranslatorContext) - Method in class ai.djl.modality.nlp.translator.QaServingTranslator: Prepares the translator with the manager and model to use.
prepare(TranslatorContext) - Method in class ai.djl.modality.nlp.translator.TextClassificationServingTranslator: Prepares the translator with the manager and model to use.
prepare(TranslatorContext) - Method in interface ai.djl.translate.Translator: Prepares the translator with the manager and model to use.
prepare(Progress) - Method in class ai.djl.training.dataset.ArrayDataset: Prepares the dataset for use with tracked progress.
prepare(Progress) - Method in interface ai.djl.training.dataset.Dataset: Prepares the dataset for use with tracked progress.
preprocess(List<String>) - Method in class ai.djl.modality.nlp.preprocess.HyphenNormalizer: Applies the preprocessing defined to the given input tokens.
preprocess(List<String>) - Method in class ai.djl.modality.nlp.preprocess.LambdaProcessor: Applies the preprocessing defined to the given input tokens.
preprocess(List<String>) - Method in class ai.djl.modality.nlp.preprocess.LowerCaseConvertor: Applies the preprocessing defined to the given input tokens.
preprocess(List<String>) - Method in class ai.djl.modality.nlp.preprocess.PunctuationSeparator: Applies the preprocessing defined to the given input tokens.
preprocess(List<String>) - Method in class ai.djl.modality.nlp.preprocess.TextCleaner: Applies the preprocessing defined to the given input tokens.
preprocess(List<String>) - Method in interface ai.djl.modality.nlp.preprocess.TextProcessor: Applies the preprocessing defined to the given input tokens.
preprocess(List<String>) - Method in class ai.djl.modality.nlp.preprocess.TextTerminator: Applies the preprocessing defined to the given input tokens.
preprocess(List<String>) - Method in class ai.djl.modality.nlp.preprocess.TextTruncator: Applies the preprocessing defined to the given input tokens.
preprocess(List<String>) - Method in interface ai.djl.modality.nlp.preprocess.Tokenizer: Applies the preprocessing defined to the given input tokens.
preprocess(List<String>) - Method in class ai.djl.modality.nlp.preprocess.UnicodeNormalizer: Applies the preprocessing defined to the given input tokens.
PreProcessor<I> - Interface in ai.djl.translate: An interface that provides pre-processing functionality.
preprocessTextToEmbed(List<String>) - Method in class ai.djl.modality.nlp.embedding.ModelZooTextEmbedding: Preprocesses the text to embed into an array to pass into the model.
preprocessTextToEmbed(List<String>) - Method in class ai.djl.modality.nlp.embedding.SimpleTextEmbedding: Preprocesses the text to embed into an array to pass into the model.
preprocessTextToEmbed(List<String>) - Method in interface ai.djl.modality.nlp.embedding.TextEmbedding: Preprocesses the text to embed into an array to pass into the model.
preprocessTextToEmbed(List<String>) - Method in class ai.djl.modality.nlp.embedding.TrainableTextEmbedding: Preprocesses the text to embed into an array to pass into the model.
preprocessWordToEmbed(String) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Pre-processes the word to embed into an array to pass into the model.
preprocessWordToEmbed(String) - Method in interface ai.djl.modality.nlp.embedding.WordEmbedding: Pre-processes the word to embed into an array to pass into the model.
probabilities - Variable in class ai.djl.modality.Classifications
probabilities(ParameterStore, NDArray, boolean) - Method in class ai.djl.nn.transformer.IdEmbedding: Turns an array of embeddings of shape (d0 ...
processInput(TranslatorContext, int[]) - Method in class ai.djl.modality.cv.translator.BigGANTranslator: Processes the input and converts it to NDList.
processInput(TranslatorContext, Image) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator: Processes the input and converts it to NDList.
processInput(TranslatorContext, Image) - Method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslator: Processes the input and converts it to NDList.
processInput(TranslatorContext, Image) - Method in class ai.djl.modality.cv.translator.StyleTransferTranslator: Processes the input and converts it to NDList.
processInput(TranslatorContext, Input) - Method in class ai.djl.modality.cv.translator.ImageServingTranslator: Processes the input and converts it to NDList.
processInput(TranslatorContext, Input) - Method in class ai.djl.modality.nlp.translator.QaServingTranslator: Processes the input and converts it to NDList.
processInput(TranslatorContext, Input) - Method in class ai.djl.modality.nlp.translator.TextClassificationServingTranslator: Processes the input and converts it to NDList.
processInput(TranslatorContext, NDList) - Method in class ai.djl.translate.NoopTranslator: Processes the input and converts it to NDList.
processInput(TranslatorContext, I) - Method in interface ai.djl.translate.PreProcessor: Processes the input and converts it to NDList.
processInput(TranslatorContext, InputStream) - Method in class ai.djl.modality.cv.translator.wrapper.InputStreamTranslator: Processes the input and converts it to NDList.
processInput(TranslatorContext, String) - Method in class ai.djl.modality.nlp.translator.SimpleText2TextTranslator: Processes the input and converts it to NDList.
processInput(TranslatorContext, URL) - Method in class ai.djl.modality.cv.translator.wrapper.UrlTranslator: Processes the input and converts it to NDList.
processInput(TranslatorContext, Path) - Method in class ai.djl.modality.cv.translator.wrapper.FileTranslator: Processes the input and converts it to NDList.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.BigGANTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.ImageClassificationTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.ImageServingTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.SimplePoseTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.SingleShotDetectionTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.StyleTransferTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.wrapper.FileTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.wrapper.InputStreamTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.wrapper.UrlTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.YoloTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.cv.translator.YoloV5Translator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.nlp.translator.QaServingTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.nlp.translator.SimpleText2TextTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.modality.nlp.translator.TextClassificationServingTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in class ai.djl.translate.NoopTranslator: Processes the output NDList to the corresponding output object.
processOutput(TranslatorContext, NDList) - Method in interface ai.djl.translate.PostProcessor: Processes the output NDList to the corresponding output object.
prod() - Method in interface ai.djl.ndarray.NDArray: Returns the product of this NDArray.
prod() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the product of this NDArray.
prod(int[]) - Method in interface ai.djl.ndarray.NDArray: Returns the product of this NDArray elements over the given axes.
prod(int[], boolean) - Method in interface ai.djl.ndarray.NDArray: Returns the product of this NDArray elements over the given axes.
prod(int[], boolean) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the product of this NDArray elements over the given axes.
ProgressBar - Class in ai.djl.training.util: ProgressBar is an implementation of Progress.
ProgressBar() - Constructor for class ai.djl.training.util.ProgressBar: Creates an instance of ProgressBar with a maximum value of 1.
ProgressBar(String, long) - Constructor for class ai.djl.training.util.ProgressBar: Creates an instance of ProgressBar with the given maximum value, and displays the given message.
ProgressBar(String, long, String) - Constructor for class ai.djl.training.util.ProgressBar: Creates an instance of ProgressBar with the given maximum value, and displays the given message.
properties - Variable in class ai.djl.BaseModel
PunctuationSeparator - Class in ai.djl.modality.nlp.preprocess: PunctuationSeparator separates punctuation into a separate token.
PunctuationSeparator() - Constructor for class ai.djl.modality.nlp.preprocess.PunctuationSeparator

Q

QAgent - Class in ai.djl.modality.rl.agent: An RlAgent that implements Q or Deep-Q Learning.
QAgent(Trainer, float) - Constructor for class ai.djl.modality.rl.agent.QAgent: Constructs a QAgent.
QAgent(Trainer, float, Batchifier) - Constructor for class ai.djl.modality.rl.agent.QAgent: Constructs a QAgent with a custom Batchifier.
QAInput - Class in ai.djl.modality.nlp.qa: The input container for a Application.NLP.QUESTION_ANSWER model.
QAInput(String, String) - Constructor for class ai.djl.modality.nlp.qa.QAInput: Creates the BERT QA model.
QaServingTranslator - Class in ai.djl.modality.nlp.translator: A Translator that can handle generic question answering Input and Output.
QaServingTranslator(Translator<QAInput, String>) - Constructor for class ai.djl.modality.nlp.translator.QaServingTranslator: Constructs a QaServingTranslator instance.
QATranslator - Class in ai.djl.modality.nlp.translator: An abstract class to define the question answering translator.
QATranslator(QATranslator.BaseBuilder<?>) - Constructor for class ai.djl.modality.nlp.translator.QATranslator
QATranslator.BaseBuilder<T extends QATranslator.BaseBuilder> - Class in ai.djl.modality.nlp.translator: The builder for question answering translator.
quantize() - Method in interface ai.djl.Model: Converts the model to use a lower precision quantized network.
QUESTION_ANSWER - Static variable in interface ai.djl.Application.NLP: An application that a reference document and a question about the document and returns text answering the question.

R

random() - Method in class ai.djl.training.hyperparameter.param.HpCategorical: Returns a random value for the hyperparameter for a range of a fixed value if it is a HpVal.
random() - Method in class ai.djl.training.hyperparameter.param.HpFloat: Returns a random value for the hyperparameter for a range of a fixed value if it is a HpVal.
random() - Method in class ai.djl.training.hyperparameter.param.HpInt: Returns a random value for the hyperparameter for a range of a fixed value if it is a HpVal.
random() - Method in class ai.djl.training.hyperparameter.param.HpSet: Returns a random value for the hyperparameter for a range of a fixed value if it is a HpVal.
random() - Method in class ai.djl.training.hyperparameter.param.HpVal: Returns a random value for the hyperparameter for a range of a fixed value if it is a HpVal.
random() - Method in class ai.djl.training.hyperparameter.param.Hyperparameter: Returns a random value for the hyperparameter for a range of a fixed value if it is a HpVal.
RandomAccessDataset - Class in ai.djl.training.dataset: RandomAccessDataset represent the dataset that support random access reads.
RandomAccessDataset(RandomAccessDataset.BaseBuilder<?>) - Constructor for class ai.djl.training.dataset.RandomAccessDataset: Creates a new instance of RandomAccessDataset with the given necessary configurations.
RandomAccessDataset.BaseBuilder<T extends RandomAccessDataset.BaseBuilder<T>> - Class in ai.djl.training.dataset: The Builder to construct a RandomAccessDataset.
randomAction() - Method in class ai.djl.modality.rl.ActionSpace: Returns a random action.
randomBrightness(NDArray, float) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Randomly jitters image brightness with a factor chosen from [max(0, 1 - brightness), 1 + brightness].
RandomBrightness - Class in ai.djl.modality.cv.transform: A Transform that randomly jitters image brightness with a factor chosen from [max(0, 1 - brightness), 1 + brightness].
RandomBrightness(float) - Constructor for class ai.djl.modality.cv.transform.RandomBrightness: Creates a RandomBrightness Transform.
randomColorJitter(NDArray, float, float, float, float) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Randomly jitters the brightness, contrast, saturation, and hue of an image.
RandomColorJitter - Class in ai.djl.modality.cv.transform: A Transform that randomly jitters the brightness, contrast, saturation, and hue of an image.
RandomColorJitter(float, float, float, float) - Constructor for class ai.djl.modality.cv.transform.RandomColorJitter: Creates a RandomColorJitter Transform.
randomFlipLeftRight(NDArray) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Randomly flip the input image left to right with a probability of 0.5.
RandomFlipLeftRight - Class in ai.djl.modality.cv.transform: A Transform that randomly flip the input image left to right with a probability of 0.5.
RandomFlipLeftRight() - Constructor for class ai.djl.modality.cv.transform.RandomFlipLeftRight
randomFlipTopBottom(NDArray) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Randomly flip the input image top to bottom with a probability of 0.5.
RandomFlipTopBottom - Class in ai.djl.modality.cv.transform: A Transform that randomly flip the input image top to bottom with a probability of 0.5.
RandomFlipTopBottom() - Constructor for class ai.djl.modality.cv.transform.RandomFlipTopBottom
randomHue(NDArray, float) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Randomly jitters image hue with a factor chosen from [max(0, 1 - hue), 1 + hue].
RandomHue - Class in ai.djl.modality.cv.transform: A Transform that randomly jitters image hue with a factor chosen from [max(0, 1 - hue), 1 + hue].
RandomHue(float) - Constructor for class ai.djl.modality.cv.transform.RandomHue: Creates a RandomHue Transform.
randomInteger(long, long, Shape, DataType) - Method in class ai.djl.ndarray.BaseNDManager: Returns random integer values from low (inclusive) to high (exclusive).
randomInteger(long, long, Shape, DataType) - Method in interface ai.djl.ndarray.NDManager: Returns random integer values from low (inclusive) to high (exclusive).
randomMultinomial(int, NDArray) - Method in class ai.djl.ndarray.BaseNDManager: Draw samples from a multinomial distribution.
randomMultinomial(int, NDArray) - Method in interface ai.djl.ndarray.NDManager: Draw samples from a multinomial distribution.
randomMultinomial(int, NDArray, Shape) - Method in class ai.djl.ndarray.BaseNDManager: Draw samples from a multinomial distribution.
randomMultinomial(int, NDArray, Shape) - Method in interface ai.djl.ndarray.NDManager: Draw samples from a multinomial distribution.
randomNormal(float, float, Shape, DataType) - Method in class ai.djl.ndarray.BaseNDManager: Draws random samples from a normal (Gaussian) distribution.
randomNormal(float, float, Shape, DataType) - Method in interface ai.djl.ndarray.NDManager: Draws random samples from a normal (Gaussian) distribution.
randomNormal(float, float, Shape, DataType, Device) - Method in interface ai.djl.ndarray.NDManager: Draws random samples from a normal (Gaussian) distribution.
randomNormal(Shape) - Method in interface ai.djl.ndarray.NDManager: Draws random samples from a normal (Gaussian) distribution with mean 0 and standard deviation 1.
randomNormal(Shape, DataType) - Method in interface ai.djl.ndarray.NDManager: Draws random samples from a normal (Gaussian) distribution with mean 0 and standard deviation 1.
randomResizedCrop(NDArray, int, int, double, double, double, double) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Crop the input image with random scale and aspect ratio.
RandomResizedCrop - Class in ai.djl.modality.cv.transform: A Transform that crop the input image with random scale and aspect ratio.
RandomResizedCrop(int, int, double, double, double, double) - Constructor for class ai.djl.modality.cv.transform.RandomResizedCrop: Creates a RandomResizedCrop Transform.
RandomSampler - Class in ai.djl.training.dataset: RandomSampler is an implementation of the Sampler.SubSampler interface.
RandomSampler() - Constructor for class ai.djl.training.dataset.RandomSampler: Creates a new instance of RandomSampler.
RandomSampler(int) - Constructor for class ai.djl.training.dataset.RandomSampler: Creates a new instance of RandomSampler with the given seed.
randomSplit(int...) - Method in class ai.djl.training.dataset.RandomAccessDataset: Splits the dataset set into multiple portions.
randomUniform(float, float, Shape) - Method in interface ai.djl.ndarray.NDManager: Draws samples from a uniform distribution.
randomUniform(float, float, Shape, DataType) - Method in class ai.djl.ndarray.BaseNDManager: Draws samples from a uniform distribution.
randomUniform(float, float, Shape, DataType) - Method in interface ai.djl.ndarray.NDManager: Draws samples from a uniform distribution.
randomUniform(float, float, Shape, DataType, Device) - Method in interface ai.djl.ndarray.NDManager: Draws samples from a uniform distribution.
readInputShapes(DataInputStream) - Method in class ai.djl.nn.AbstractBaseBlock
readParameters(Path, Map<String, ?>) - Method in class ai.djl.BaseModel
Record - Class in ai.djl.training.dataset: Record represents a single element of data and labels from Dataset.
Record(NDList, NDList) - Constructor for class ai.djl.training.dataset.Record: Creates a new instance of Record with a single element of data and its corresponding labels.
Rectangle - Class in ai.djl.modality.cv.output: A Rectangle specifies an area in a coordinate space that is enclosed by the Rectangle object's upper-left point Point in the coordinate space, its width, and its height.
Rectangle(double, double, double, double) - Constructor for class ai.djl.modality.cv.output.Rectangle: Constructs a new Rectangle whose upper-left corner is specified as (x,y) and whose width and height are specified by the arguments of the same name.
Rectangle(Point, double, double) - Constructor for class ai.djl.modality.cv.output.Rectangle: Constructs a new Rectangle whose upper-left corner is specified as coordinate point and whose width and height are specified by the arguments of the same name.
RecurrentBlock - Class in ai.djl.nn.recurrent: RecurrentBlock is an abstract implementation of recurrent neural networks.
RecurrentBlock(RecurrentBlock.BaseBuilder<?>) - Constructor for class ai.djl.nn.recurrent.RecurrentBlock: Creates a RecurrentBlock object.
RecurrentBlock.BaseBuilder<T extends RecurrentBlock.BaseBuilder> - Class in ai.djl.nn.recurrent: The Builder to construct a RecurrentBlock type of Block.
registerEngine(EngineProvider) - Static method in class ai.djl.engine.Engine: Registers a EngineProvider if not registered.
registerModelZoo(ZooProvider) - Static method in class ai.djl.repository.zoo.ModelZoo: Refreshes model zoo.
registerRepositoryFactory(RepositoryFactory) - Static method in interface ai.djl.repository.Repository: Registers a RepositoryFactory to handle the specified url scheme.
registerTranslator(Class<I>, Class<O>, Translator<I, O>) - Method in class ai.djl.translate.DefaultTranslatorFactory: Registers a Translator with the TranslatorFactory.
relu(NDArray) - Static method in class ai.djl.nn.Activation: Applies ReLU activation on the input NDArray.
relu(NDList) - Static method in class ai.djl.nn.Activation: Applies ReLU activation on the input singleton NDList.
RELU - ai.djl.nn.recurrent.RNN.Activation
reluBlock() - Static method in class ai.djl.nn.Activation: Creates a LambdaBlock that applies the ReLU activation function in its forward function.
RemoteRepository - Class in ai.djl.repository: A RemoteRepository is a Repository located on a remote web server.
RemoteRepository(String, URI) - Constructor for class ai.djl.repository.RemoteRepository: (Internal) Constructs a remote repository.
remove(String) - Method in class ai.djl.ndarray.NDList: Removes the first occurrence of the specified element from this NDList if it is present.
removeLastBlock() - Method in class ai.djl.nn.SequentialBlock: Removes the Block added last from the sequence of blocks.
removeLastBlock() - Method in interface ai.djl.nn.SymbolBlock: Removes the last block in the symbolic graph.
repeat(int, long) - Method in interface ai.djl.ndarray.NDArray: Repeats element of this NDArray the number of times given repeats along given axis.
repeat(int, long) - Method in class ai.djl.ndarray.NDArrayAdapter: Repeats element of this NDArray the number of times given repeats along given axis.
repeat(long) - Method in interface ai.djl.ndarray.NDArray: Repeats element of this NDArray the number of times given repeats.
repeat(long) - Method in class ai.djl.ndarray.NDArrayAdapter: Repeats element of this NDArray the number of times given repeats.
repeat(long[]) - Method in interface ai.djl.ndarray.NDArray: Repeats element of this NDArray the number of times given repeats along each axis.
repeat(long[]) - Method in class ai.djl.ndarray.NDArrayAdapter: Repeats element of this NDArray the number of times given repeats along each axis.
repeat(Shape) - Method in interface ai.djl.ndarray.NDArray: Repeats element of this NDArray to match the desired shape.
repeat(Shape) - Method in class ai.djl.ndarray.NDArrayAdapter: Repeats element of this NDArray to match the desired shape.
replaceLastBlock(Block) - Method in class ai.djl.nn.SequentialBlock: Replaces the Block last added from the sequence of blocks, and adds the given block.
ReplayBuffer - Interface in ai.djl.modality.rl: Records RlEnv.Steps so that they can be trained on.
Repository - Interface in ai.djl.repository: Repository is a format for storing data Artifacts for various uses including deep learning models and datasets.
RepositoryFactory - Interface in ai.djl.repository: A interface responsible to create Repository instances.
requiresGradient() - Method in class ai.djl.nn.Parameter: Returns whether this parameter needs gradients to be computed.
rescaleGrad - Variable in class ai.djl.training.optimizer.Optimizer
reset() - Method in interface ai.djl.modality.rl.env.RlEnv: Resets the environment to it's default state.
reset(String, long, String) - Method in class ai.djl.training.util.ProgressBar
resetAccumulator(String) - Method in class ai.djl.training.evaluator.AbstractAccuracy: Resets the evaluator value with the given key.
resetAccumulator(String) - Method in class ai.djl.training.evaluator.BoundingBoxError: Resets the evaluator value with the given key.
resetAccumulator(String) - Method in class ai.djl.training.evaluator.Evaluator: Resets the evaluator value with the given key.
resetAccumulator(String) - Method in class ai.djl.training.evaluator.IndexEvaluator: Resets the evaluator value with the given key.
resetAccumulator(String) - Method in class ai.djl.training.loss.AbstractCompositeLoss: Resets the evaluator value with the given key.
resetAccumulator(String) - Method in class ai.djl.training.loss.Loss: Resets the evaluator value with the given key.
reshape(long...) - Method in interface ai.djl.ndarray.NDArray: Reshapes this NDArray to the given Shape.
reshape(Shape) - Method in interface ai.djl.ndarray.NDArray: Reshapes this NDArray to the given Shape.
reshape(Shape) - Method in class ai.djl.ndarray.NDArrayAdapter: Reshapes this NDArray to the given Shape.
resize(NDArray, int) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Resizes an image to the given width and height.
resize(NDArray, int, int) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Resizes an image to the given width and height.
resize(NDArray, int, int, Image.Interpolation) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Resizes an image to the given width and height with given interpolation.
Resize - Class in ai.djl.modality.cv.transform: A Transform that resizes the image.
Resize(int) - Constructor for class ai.djl.modality.cv.transform.Resize: Creates a Resize Transform that resizes to the given size.
Resize(int, int) - Constructor for class ai.djl.modality.cv.transform.Resize: Creates a Resize Transform that resizes to the given width and height.
Resize(int, int, Image.Interpolation) - Constructor for class ai.djl.modality.cv.transform.Resize: Creates a Resize Transform that resizes to the given width and height with given interpolation.
resolve(MRL, Map<String, String>) - Method in class ai.djl.repository.JarRepository: Returns the artifact matching a mrl, version, and property filter.
resolve(MRL, Map<String, String>) - Method in class ai.djl.repository.LocalRepository: Returns the artifact matching a mrl, version, and property filter.
resolve(MRL, Map<String, String>) - Method in class ai.djl.repository.RemoteRepository: Returns the artifact matching a mrl, version, and property filter.
resolve(MRL, Map<String, String>) - Method in interface ai.djl.repository.Repository: Returns the artifact matching a mrl, version, and property filter.
resolve(MRL, Map<String, String>) - Method in class ai.djl.repository.SimpleRepository: Returns the artifact matching a mrl, version, and property filter.
resolve(MRL, Map<String, String>) - Method in class ai.djl.repository.SimpleUrlRepository: Returns the artifact matching a mrl, version, and property filter.
resolvePath(Artifact.Item, String) - Method in class ai.djl.repository.AbstractRepository
resolvePath(Artifact.Item, String) - Method in class ai.djl.repository.SimpleRepository
resources - Variable in class ai.djl.ndarray.BaseNDManager
results - Variable in class ai.djl.training.hyperparameter.optimizer.BaseHpOptimizer
ret(T) - Method in interface ai.djl.ndarray.NDManager: Returns a value outside of this manager by attaching to this manager's parent.
returnResource() - Method in class ai.djl.ndarray.BaseNDManager.TempResource
returnState - Variable in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder
returnState - Variable in class ai.djl.nn.recurrent.RecurrentBlock
RlAgent - Interface in ai.djl.modality.rl.agent: An RlAgent is the model or technique to decide the actions to take in an RlEnv.
RlEnv - Interface in ai.djl.modality.rl.env: An environment to use for reinforcement learning.
RlEnv.Step - Interface in ai.djl.modality.rl.env: A record of taking a step in the environment.
rmsprop() - Static method in class ai.djl.training.optimizer.Optimizer: Returns a new instance of RmsProp.Builder that can build an RmsProp optimizer.
RmsProp - Class in ai.djl.training.optimizer: The RMSProp Optimizer.
RmsProp(RmsProp.Builder) - Constructor for class ai.djl.training.optimizer.RmsProp: Creates a new instance of RMSProp optimizer.
RmsProp.Builder - Class in ai.djl.training.optimizer: The Builder to construct an RmsProp object.
RNN - Class in ai.djl.nn.recurrent: RNN is an implementation of recurrent neural networks which applies a single-gate recurrent layer to input.
RNN.Activation - Enum in ai.djl.nn.recurrent: An enum that enumerates the type of activation.
RNN.Builder - Class in ai.djl.nn.recurrent: The Builder to construct a RNN type of Block.
rotate90(int, int[]) - Method in interface ai.djl.ndarray.NDArray: Rotates an array by 90 degrees in the plane specified by axes.
rotate90(int, int[]) - Method in class ai.djl.ndarray.NDArrayAdapter: Rotates an array by 90 degrees in the plane specified by axes.
rotate90(NDArray, int) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Rotate an image NDArray counter-clockwise 90 degree.
round() - Method in interface ai.djl.ndarray.NDArray: Returns the round of this NDArray element-wise.
round() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the round of this NDArray element-wise.
ROW_SPARSE - ai.djl.ndarray.types.SparseFormat
runEnvironment(RlAgent, boolean) - Method in interface ai.djl.modality.rl.env.RlEnv: Runs the environment from reset until done.
RUNNING_MEAN - ai.djl.nn.Parameter.Type
RUNNING_VAR - ai.djl.nn.Parameter.Type

S

sample(RandomAccessDataset) - Method in class ai.djl.training.dataset.BatchSampler: Fetches an iterator that iterates through the given RandomAccessDataset in mini-batches of indices.
sample(RandomAccessDataset) - Method in class ai.djl.training.dataset.RandomSampler: Fetches an iterator that iterates through the indices of the given RandomAccessDataset.
sample(RandomAccessDataset) - Method in interface ai.djl.training.dataset.Sampler: Fetches an iterator that iterates through the given RandomAccessDataset in mini-batches of indices.
sample(RandomAccessDataset) - Method in interface ai.djl.training.dataset.Sampler.SubSampler: Fetches an iterator that iterates through the indices of the given RandomAccessDataset.
sample(RandomAccessDataset) - Method in class ai.djl.training.dataset.SequenceSampler: Fetches an iterator that iterates through the indices of the given RandomAccessDataset.
sampler - Variable in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder
sampler - Variable in class ai.djl.training.dataset.RandomAccessDataset
Sampler - Interface in ai.djl.training.dataset: An interface for sampling data items from a RandomAccessDataset.
Sampler.SubSampler - Interface in ai.djl.training.dataset: An interface that samples a single data item at a time.
save(BufferedImage, OutputStream, String) - Method in class ai.djl.modality.cv.BufferedImageFactory
save(DataOutputStream) - Method in class ai.djl.nn.Parameter: Writes the parameter NDArrays to the given output stream.
save(InputStream, Path, Artifact.Item, Progress) - Method in class ai.djl.repository.AbstractRepository
save(OutputStream, String) - Method in interface ai.djl.modality.cv.Image: Save the image to file.
save(Path, String) - Method in class ai.djl.BaseModel: Saves the model to the specified modelPath with the name provided.
save(Path, String) - Method in interface ai.djl.Model: Saves the model to the specified modelPath with the name provided.
save(Path, String) - Method in class ai.djl.repository.zoo.ZooModel: Saves the model to the specified modelPath with the name provided.
saveInputShapes(DataOutputStream) - Method in class ai.djl.nn.AbstractBaseBlock
saveMetadata(DataOutputStream) - Method in class ai.djl.nn.AbstractBaseBlock: Override this method to save additional data apart from parameter values.
saveMetadata(DataOutputStream) - Method in class ai.djl.nn.core.Linear: Override this method to save additional data apart from parameter values.
saveMetadata(DataOutputStream) - Method in class ai.djl.nn.norm.BatchNorm: Override this method to save additional data apart from parameter values.
saveMetadata(DataOutputStream) - Method in class ai.djl.nn.norm.LayerNorm: Override this method to save additional data apart from parameter values.
saveModel(Model, TrainingResult) - Method in class ai.djl.training.hyperparameter.EasyHpo: Saves the best hyperparameter set.
saveModel(Trainer) - Method in class ai.djl.training.listener.SaveModelTrainingListener
SaveModelTrainingListener - Class in ai.djl.training.listener: A TrainingListener that saves a model and can save checkpoints.
SaveModelTrainingListener(String) - Constructor for class ai.djl.training.listener.SaveModelTrainingListener: Constructs a SaveModelTrainingListener using the model's name.
SaveModelTrainingListener(String, String) - Constructor for class ai.djl.training.listener.SaveModelTrainingListener: Constructs a SaveModelTrainingListener.
SaveModelTrainingListener(String, String, int) - Constructor for class ai.djl.training.listener.SaveModelTrainingListener: Constructs a SaveModelTrainingListener.
saveParameters(DataOutputStream) - Method in class ai.djl.modality.nlp.Decoder: Writes the parameters of the block to the given outputStream.
saveParameters(DataOutputStream) - Method in class ai.djl.modality.nlp.Encoder: Writes the parameters of the block to the given outputStream.
saveParameters(DataOutputStream) - Method in class ai.djl.modality.nlp.EncoderDecoder: Writes the parameters of the block to the given outputStream.
saveParameters(DataOutputStream) - Method in class ai.djl.nn.AbstractBaseBlock: Writes the parameters of the block to the given outputStream.
saveParameters(DataOutputStream) - Method in interface ai.djl.nn.Block: Writes the parameters of the block to the given outputStream.
saveParameters(DataOutputStream) - Method in class ai.djl.nn.core.ConstantEmbedding: Writes the parameters of the block to the given outputStream.
saveParameters(DataOutputStream) - Method in class ai.djl.nn.core.Embedding: Writes the parameters of the block to the given outputStream.
ScaledDotProductAttentionBlock - Class in ai.djl.nn.transformer: A Block implementing scaled product attention according to Vaswani et.
ScaledDotProductAttentionBlock.Builder - Class in ai.djl.nn.transformer: A builder for ScaledDotProductAttentionBlocks.
scaleGradient(double) - Method in interface ai.djl.ndarray.NDArray: Returns an NDArray equal to this that magnifies the gradient propagated to this by a constant.
search(VersionRange, Map<String, String>) - Method in class ai.djl.repository.Metadata.MatchAllMetadata: Returns the artifacts matching the version and property requirements.
search(VersionRange, Map<String, String>) - Method in class ai.djl.repository.Metadata: Returns the artifacts matching the version and property requirements.
self() - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder
self() - Method in class ai.djl.modality.cv.translator.ImageClassificationTranslator.Builder
self() - Method in class ai.djl.modality.cv.translator.InstanceSegmentationTranslator.Builder
self() - Method in class ai.djl.modality.cv.translator.SimplePoseTranslator.Builder
self() - Method in class ai.djl.modality.cv.translator.SingleShotDetectionTranslator.Builder
self() - Method in class ai.djl.modality.cv.translator.YoloTranslator.Builder
self() - Method in class ai.djl.modality.cv.translator.YoloV5Translator.Builder
self() - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding.Builder: Returns this {code Builder} object.
self() - Method in class ai.djl.modality.nlp.translator.QATranslator.BaseBuilder
self() - Method in class ai.djl.nn.convolutional.Conv1d.Builder
self() - Method in class ai.djl.nn.convolutional.Conv1dTranspose.Builder
self() - Method in class ai.djl.nn.convolutional.Conv2d.Builder
self() - Method in class ai.djl.nn.convolutional.Conv2dTranspose.Builder
self() - Method in class ai.djl.nn.convolutional.Conv3d.Builder
self() - Method in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder
self() - Method in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder
self() - Method in class ai.djl.nn.core.Embedding.BaseBuilder: Returns this {code Builder} object.
self() - Method in class ai.djl.nn.recurrent.GRU.Builder
self() - Method in class ai.djl.nn.recurrent.LSTM.Builder
self() - Method in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder
self() - Method in class ai.djl.nn.recurrent.RNN.Builder
self() - Method in class ai.djl.training.dataset.ArrayDataset.Builder: Returns this {code Builder} object.
self() - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Returns this {code Builder} object.
self() - Method in class ai.djl.training.optimizer.Adadelta.Builder
self() - Method in class ai.djl.training.optimizer.Adagrad.Builder
self() - Method in class ai.djl.training.optimizer.Adam.Builder
self() - Method in class ai.djl.training.optimizer.Nag.Builder
self() - Method in class ai.djl.training.optimizer.Optimizer.OptimizerBuilder
self() - Method in class ai.djl.training.optimizer.RmsProp.Builder
self() - Method in class ai.djl.training.optimizer.Sgd.Builder
selu(NDArray) - Static method in class ai.djl.nn.Activation: Applies Scaled ELU activation on the input NDArray.
selu(NDList) - Static method in class ai.djl.nn.Activation: Applies Scaled ELU activation on the input singleton NDList.
seluBlock() - Static method in class ai.djl.nn.Activation: Creates a LambdaBlock that applies the SELU activation function in its forward function.
SEMANTIC_SEGMENTATION - Static variable in interface ai.djl.Application.CV: An application that classifies each pixel in an image into a category.
SENTIMENT_ANALYSIS - Static variable in interface ai.djl.Application.NLP: An application that classifies text into positive or negative, an specific case of Application.NLP.TEXT_CLASSIFICATION.
sequenceMask(NDArray) - Method in interface ai.djl.ndarray.NDArray: Sets all elements outside the sequence to 0.
sequenceMask(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Sets all elements outside the sequence to 0.
sequenceMask(NDArray, float) - Method in interface ai.djl.ndarray.NDArray: Sets all elements outside the sequence to a constant value.
sequenceMask(NDArray, float) - Method in class ai.djl.ndarray.NDArrayAdapter: Sets all elements outside the sequence to a constant value.
sequenceMask(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Sets all elements of the given NDArray outside the sequence NDArray to 0.
sequenceMask(NDArray, NDArray, float) - Static method in class ai.djl.ndarray.NDArrays: Sets all elements of the given NDArray outside the sequence NDArray to a constant value.
SequenceSampler - Class in ai.djl.training.dataset: SequenceSampler is an implementation of the Sampler.SubSampler interface.
SequenceSampler() - Constructor for class ai.djl.training.dataset.SequenceSampler
SequentialBlock - Class in ai.djl.nn: SequentialBlock is a Block whose children form a chain of blocks with each child block feeding its output to the next.
SequentialBlock() - Constructor for class ai.djl.nn.SequentialBlock: Creates an empty sequential block.
serialize(Classifications, Type, JsonSerializationContext) - Method in class ai.djl.modality.Classifications.ClassificationsSerializer
ServingTranslator - Interface in ai.djl.translate: A Translator that can handle generic Input and Output.
ServingTranslatorFactory - Class in ai.djl.translate: A TranslatorFactory that creates an generic Translator.
ServingTranslatorFactory() - Constructor for class ai.djl.translate.ServingTranslatorFactory
set(byte[]) - Method in interface ai.djl.ndarray.NDArray: Sets this NDArray value from an array of bytes.
set(double[]) - Method in interface ai.djl.ndarray.NDArray: Sets this NDArray value from an array of doubles.
set(float[]) - Method in interface ai.djl.ndarray.NDArray: Sets this NDArray value from an array of floats.
set(int[]) - Method in interface ai.djl.ndarray.NDArray: Sets this NDArray value from an array of ints.
set(long[]) - Method in interface ai.djl.ndarray.NDArray: Sets this NDArray value from an array of longs.
set(NDIndex, NDArray) - Method in interface ai.djl.ndarray.NDArray: Sets the specified index in this NDArray with the given values.
set(NDIndex, NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Sets the specified index in this NDArray with the given values.
set(NDIndex, Number) - Method in interface ai.djl.ndarray.NDArray: Sets the specified index in this NDArray with the given value.
set(NDIndex, Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Sets the specified index in this NDArray with the given value.
set(NDIndex, Function<NDArray, NDArray>) - Method in interface ai.djl.ndarray.NDArray: Sets the specific index by a function.
set(NDIndex, Function<NDArray, NDArray>) - Method in class ai.djl.ndarray.NDArrayAdapter: Sets the specific index by a function.
set(NDArray, NDIndexBooleans, NDArray) - Method in class ai.djl.ndarray.index.NDArrayIndexer: Sets the values of the array at the boolean locations with an array.
set(NDArray, NDIndexFullSlice, NDArray) - Method in class ai.djl.ndarray.index.NDArrayIndexer: Sets the values of the array at the fullSlice with an array.
set(NDArray, NDIndexFullSlice, Number) - Method in class ai.djl.ndarray.index.NDArrayIndexer: Sets the values of the array at the fullSlice with a number.
set(NDArray, NDIndex, NDArray) - Method in class ai.djl.ndarray.index.NDArrayIndexer: Sets the values of the array at the index locations with an array.
set(NDArray, NDIndex, Number) - Method in class ai.djl.ndarray.index.NDArrayIndexer: Sets the values of the array at the index locations with a number.
set(NDArray, Number) - Method in interface ai.djl.ndarray.NDArray: Sets the NDArray by boolean mask.
set(NDArray, Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Sets the NDArray by boolean mask.
set(Buffer) - Method in interface ai.djl.ndarray.NDArray: Sets this NDArray value from Buffer.
set(Buffer) - Method in class ai.djl.ndarray.NDArrayAdapter: Sets this NDArray value from Buffer.
setActivation(RNN.Activation) - Method in class ai.djl.nn.recurrent.RNN.Builder: Sets the activation for the RNN - ReLu or Tanh.
setApplication(Application) - Method in class ai.djl.repository.Metadata: Sets the Application.
setArguments(Map<String, ?>) - Method in interface ai.djl.translate.ServingTranslator: Sets the configurations for the Translator instance.
setArguments(Map<String, Object>) - Method in class ai.djl.repository.Artifact: Sets the artifact arguments.
setArray(NDArray) - Method in class ai.djl.nn.Parameter: Sets the values of this Parameter.
setArtifact(Artifact) - Method in class ai.djl.repository.Artifact.Item: Sets the artifact associated with this item.
setArtifactId(String) - Method in class ai.djl.repository.Metadata: Sets the artifactId.
setArtifacts(List<Artifact>) - Method in class ai.djl.repository.Metadata: Sets the artifacts for the metadata.
setAttachment(String, Object) - Method in interface ai.djl.translate.TranslatorContext: Set a key-value pair of attachments.
setBaseValue(float) - Method in class ai.djl.training.tracker.CosineTracker.Builder: Sets the initial value after no steps.
setBaseValue(float) - Method in class ai.djl.training.tracker.FactorTracker.Builder: Sets the initial value after no steps.
setBaseValue(float) - Method in class ai.djl.training.tracker.LinearTracker.Builder: Sets the initial value after no steps.
setBaseValue(float) - Method in class ai.djl.training.tracker.MultiFactorTracker.Builder: Sets the initial value after no steps.
setBaseValue(float) - Method in class ai.djl.training.tracker.PolynomialDecayTracker.Builder: Sets the initial value after no steps.
setBatchifier(Batchifier) - Method in class ai.djl.translate.NoopTranslator: Sets the Batchifier for the Translator.
setBlock(Block) - Method in class ai.djl.BaseModel: Sets the block for the Model for training and inference.
setBlock(Block) - Method in interface ai.djl.Model: Sets the block for the Model for training and inference.
setBlock(Block) - Method in class ai.djl.repository.zoo.ZooModel: Sets the block for the Model for training and inference.
setCheckpoint(int) - Method in class ai.djl.training.listener.SaveModelTrainingListener: Sets the checkpoint frequency in SaveModelTrainingListener.
setCode(int) - Method in class ai.djl.modality.Output: Sets the status code of the output.
setContent(PairList<String, BytesSupplier>) - Method in class ai.djl.modality.Input: Sets the content of the input.
setData(NDArray...) - Method in class ai.djl.training.dataset.ArrayDataset.Builder: Sets the data as an NDArray for the ArrayDataset.
setDataType(DataType) - Method in class ai.djl.BaseModel: Sets the standard data type used within the model.
setDataType(DataType) - Method in interface ai.djl.Model: Sets the standard data type used within the model.
setDataType(DataType) - Method in class ai.djl.ndarray.types.DataDesc: Sets the DataType of the NDArray.
setDataType(DataType) - Method in class ai.djl.repository.zoo.ZooModel: Sets the standard data type used within the model.
setDecaySteps(int) - Method in class ai.djl.training.tracker.PolynomialDecayTracker.Builder: Sets the number of training steps to decay learning rate in.
setDescription(String) - Method in class ai.djl.repository.Metadata: Sets the description.
setDictionarySize(int) - Method in class ai.djl.nn.transformer.IdEmbedding.Builder: Sets the number of ids that should be embedded.
setEmbeddingSize(int) - Method in class ai.djl.nn.core.Embedding.BaseBuilder: Sets the size of the embeddings.
setEmbeddingSize(int) - Method in class ai.djl.nn.transformer.IdEmbedding.Builder: Sets the size of the embeddings.
setEmbeddingSize(int) - Method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock.Builder: Sets the embedding Size to be used for the internal token representation.
setEndLearningRate(float) - Method in class ai.djl.training.tracker.PolynomialDecayTracker.Builder: Sets the learning rate at which to end rate decay.
setEpoch(int) - Method in class ai.djl.training.TrainingResult: Sets the actual number of epoch.
setEvaluations(Map<String, Float>) - Method in class ai.djl.training.TrainingResult: Sets the raw evaluation metrics.
setExtension(String) - Method in class ai.djl.repository.Artifact.Item: Sets the file extension.
setFactor(float) - Method in class ai.djl.training.tracker.FactorTracker.Builder: Sets the value of the multiplicative factor.
setFiles(Map<String, Artifact.Item>) - Method in class ai.djl.repository.Artifact: Sets the file items.
setFilters(int) - Method in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder: Sets the Required number of filters.
setFilters(int) - Method in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder: Sets the Required number of filters.
setGroupId(String) - Method in class ai.djl.repository.Metadata: Sets the groupId.
setHeadCount(int) - Method in class ai.djl.nn.transformer.ScaledDotProductAttentionBlock.Builder: Sets the number of attention Heads, must divide the embedding size without rest.
setId(String) - Method in class ai.djl.repository.License: Sets the identifier of the license.
setImageFactory(ImageFactory) - Static method in class ai.djl.modality.cv.ImageFactory: Sets a custom instance of ImageFactory.
setInitializer(Initializer) - Method in class ai.djl.nn.Parameter: Sets the Initializer for this Parameter, if not already set.
setInitializer(Initializer, Parameter.Type) - Method in class ai.djl.nn.AbstractBaseBlock: Sets an Initializer to all the parameters that match parameter type in the block.
setInitializer(Initializer, Parameter.Type) - Method in interface ai.djl.nn.Block: Sets an Initializer to all the parameters that match parameter type in the block.
setInitializer(Initializer, String) - Method in class ai.djl.nn.AbstractBaseBlock: Sets an Initializer to the specified direct parameter of the block, overriding the initializer of the parameter, if already set.
setInitializer(Initializer, String) - Method in interface ai.djl.nn.Block: Sets an Initializer to the specified direct parameter of the block, overriding the initializer of the parameter, if already set.
setInitializer(Initializer, Predicate<Parameter>) - Method in class ai.djl.nn.AbstractBaseBlock: Sets an Initializer to all the parameters that match Predicate in the block.
setInitializer(Initializer, Predicate<Parameter>) - Method in interface ai.djl.nn.Block: Sets an Initializer to all the parameters that match Predicate in the block.
setKernelShape(Shape) - Method in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder: Sets the shape of the kernel.
setKernelShape(Shape) - Method in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder: Sets the shape of the kernel.
setLastUpdated(Date) - Method in class ai.djl.repository.Metadata: Sets the last update date for the metadata.
setLearningRateTracker(Tracker) - Method in class ai.djl.training.optimizer.Nag.Builder: Sets the Tracker for this optimizer.
setLearningRateTracker(Tracker) - Method in class ai.djl.training.optimizer.Sgd.Builder: Sets the Tracker for this optimizer.
setLicense(Map<String, License>) - Method in class ai.djl.repository.Metadata: Sets the License.
setMainTracker(Tracker) - Method in class ai.djl.training.tracker.WarmUpTracker.Builder: Sets the base value.
setMaxUpdates(int) - Method in class ai.djl.training.tracker.CosineTracker.Builder: Sets the maximum number of updates after which the value should remain constant.
setMessage(String) - Method in class ai.djl.modality.Output: Sets the status message of the output.
setMetadata(Metadata) - Method in class ai.djl.repository.Artifact: Sets the associated metadata.
setMetadataVersion(String) - Method in class ai.djl.repository.Artifact: Sets the metadata format version.
setMetadataVersion(String) - Method in class ai.djl.repository.Metadata: Sets the metadata format version.
setMetrics(Metrics) - Method in class ai.djl.inference.Predictor: Attaches a Metrics param to use for benchmark.
setMetrics(Metrics) - Method in class ai.djl.training.Trainer: Attaches a Metrics param to use for benchmarking.
setModelDir(Path) - Method in class ai.djl.BaseModel
setMomentum(float) - Method in class ai.djl.training.optimizer.Nag.Builder: Sets the momentum for Nag.
setName(String) - Method in class ai.djl.ndarray.BaseNDManager: Sets the name for the NDManager.
setName(String) - Method in interface ai.djl.ndarray.NDArray: Sets name of this NDArray.
setName(String) - Method in class ai.djl.ndarray.NDArrayAdapter: Sets name of this NDArray.
setName(String) - Method in interface ai.djl.ndarray.NDManager: Sets the name for the NDManager.
setName(String) - Method in class ai.djl.ndarray.types.DataDesc: Sets the name of the NDArray.
setName(String) - Method in class ai.djl.nn.Parameter.Builder: Sets the name of the Parameter.
setName(String) - Method in class ai.djl.repository.Artifact.Item: Sets the item name.
setName(String) - Method in class ai.djl.repository.Artifact: Sets the artifact name.
setName(String) - Method in class ai.djl.repository.License: Sets the name of the license.
setName(String) - Method in class ai.djl.repository.Metadata: Sets the metadata-level name.
setNumLayers(int) - Method in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder: Sets the Required number of stacked layers.
setOptions(Map<String, String>) - Method in class ai.djl.repository.Artifact: Sets the artifact arguments.
setOverrideModelName(String) - Method in class ai.djl.training.listener.SaveModelTrainingListener: Sets the override model name to save checkpoints with.
setParameterServer(ParameterServer, Device[]) - Method in class ai.djl.training.ParameterStore: Sets the parameterServer used to apply updates to the parameters.
setPipeline(Pipeline) - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder: Sets the Pipeline to use for pre-processing the image.
setProperties(Map<String, String>) - Method in class ai.djl.modality.Input: Sets the properties of the input.
setProperties(Map<String, String>) - Method in class ai.djl.repository.Artifact: Sets the artifact properties.
setProperty(String, String) - Method in class ai.djl.BaseModel: Sets a property to the model.
setProperty(String, String) - Method in interface ai.djl.Model: Sets a property to the model.
setProperty(String, String) - Method in class ai.djl.repository.zoo.ZooModel: Sets a property to the model.
setRandomSeed(int) - Method in class ai.djl.engine.Engine: Seeds the random number generator in DJL Engine.
setRatios(List<Float>) - Method in class ai.djl.modality.cv.MultiBoxPrior.Builder: Sets the aspect ratios of the anchor boxes to be generated around each pixel.
setRepositoryUri(URI) - Method in class ai.djl.repository.Metadata: Sets the repository URI.
setRequiresGradient(boolean) - Method in interface ai.djl.ndarray.NDArray: Attaches a gradient NDArray to this NDArray and marks it so GradientCollector.backward(NDArray) can compute the gradient with respect to it.
setRequiresGradient(boolean) - Method in class ai.djl.ndarray.NDArrayAdapter: Attaches a gradient NDArray to this NDArray and marks it so GradientCollector.backward(NDArray) can compute the gradient with respect to it.
setRescaleGrad(float) - Method in class ai.djl.training.optimizer.Optimizer.OptimizerBuilder: Sets the value used to rescale the gradient.
setResourceType(String) - Method in class ai.djl.repository.Metadata: Returns the resource type.
setSampling(int, boolean) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Sets the Sampler with the given batch size.
setSampling(int, boolean, boolean) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Sets the Sampler with the given batch size.
setSampling(Sampler) - Method in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder: Sets the Sampler for the dataset.
setSaveModelCallback(Consumer<Trainer>) - Method in class ai.djl.training.listener.SaveModelTrainingListener: Sets the callback function on model saving.
setScalar(NDIndex, Number) - Method in interface ai.djl.ndarray.NDArray: Sets the specified scalar in this NDArray with the given value.
setScalar(NDIndex, Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Sets the specified scalar in this NDArray with the given value.
setScalar(NDArray, NDIndex, Number) - Method in class ai.djl.ndarray.index.NDArrayIndexer: Sets a scalar value in the array at the indexed location.
setSha1Hash(String) - Method in class ai.djl.repository.Artifact.Item: Sets the sha1hash of the item.
setShape(Shape) - Method in class ai.djl.ndarray.types.DataDesc: Sets the Shape of the NDArray.
setShape(Shape) - Method in class ai.djl.nn.Parameter: Sets the shape of this Parameter.
setSize(long) - Method in class ai.djl.repository.Artifact.Item: Sets the file size.
setSizes(List<Float>) - Method in class ai.djl.modality.cv.MultiBoxPrior.Builder: Sets the sizes of the anchor boxes to be generated around each pixel.
setSnapshot(boolean) - Method in class ai.djl.repository.Artifact: Sets if the artifact is a snapshot.
setStateSize(int) - Method in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder: Sets the Required size of the state for each layer.
setSteps(int[]) - Method in class ai.djl.training.tracker.MultiFactorTracker.Builder: Sets an array of integers indicating when the value should be changed, usually in an uneven interval of steps.
setTokenDictionarySize(int) - Method in class ai.djl.nn.transformer.BertBlock.Builder: Sets the number of tokens in the dictionary.
setTopK(int) - Method in class ai.djl.modality.Classifications: Set the topK number of classes to be displayed.
setType(Parameter.Type) - Method in class ai.djl.nn.Parameter.Builder: Sets the Type of the Parameter.
setType(Class<String>) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding.Builder: Creates a new Embedding.BaseBuilder with the specified embedding type.
setType(Class<T>) - Method in class ai.djl.nn.core.Embedding.BaseBuilder: Creates a new Embedding.BaseBuilder with the specified embedding type.
setType(String) - Method in class ai.djl.repository.Artifact.Item: Sets the type of the item.
setTypes(Class<P>, Class<Q>) - Method in class ai.djl.repository.zoo.Criteria.Builder: Creates a new @{code Builder} class with the specified input and output data type.
setUnits(long) - Method in class ai.djl.nn.core.Linear.Builder: Sets the number of output channels.
setupHyperParams() - Method in class ai.djl.training.hyperparameter.EasyHpo: Returns the initial hyperparameters.
setupTrainingConfig(HpSet) - Method in class ai.djl.training.hyperparameter.EasyHpo: Returns the TrainingConfig to use to train each hyperparameter set.
setUri(String) - Method in class ai.djl.repository.Artifact.Item: Sets the URI of the item.
setUrl(String) - Method in class ai.djl.repository.License: Sets the url of the license.
setVersion(String) - Method in class ai.djl.repository.Artifact: Sets the artifact version.
setVocabulary(Vocabulary) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding.Builder: Sets the Vocabulary to be used.
setWebsite(String) - Method in class ai.djl.repository.Metadata: Sets the website.
sgd() - Static method in class ai.djl.training.optimizer.Optimizer: Returns a new instance of Sgd.Builder that can build an Sgd optimizer.
Sgd - Class in ai.djl.training.optimizer: Sgd is a Stochastic Gradient Descent (SGD) optimizer.
Sgd(Sgd.Builder) - Constructor for class ai.djl.training.optimizer.Sgd: Creates a new instance of Sgd.
Sgd.Builder - Class in ai.djl.training.optimizer: The Builder to construct an Sgd object.
shape - Variable in class ai.djl.ndarray.NDArrayAdapter
Shape - Class in ai.djl.ndarray.types: A class that presents the NDArray's shape information.
Shape(long...) - Constructor for class ai.djl.ndarray.types.Shape: Constructs and initializes a Shape with specified dimension as (long... shape).
Shape(long[], LayoutType[]) - Constructor for class ai.djl.ndarray.types.Shape: Constructs and initializes a Shape with specified dimension and layout.
Shape(long[], String) - Constructor for class ai.djl.ndarray.types.Shape: Constructs and initializes a Shape with specified dimension and layout.
Shape(PairList<Long, LayoutType>) - Constructor for class ai.djl.ndarray.types.Shape: Constructs and initializes a Shape with specified shape and layout pairList.
Shape(List<Long>) - Constructor for class ai.djl.ndarray.types.Shape: Constructs and initializes a Shape with specified dimension.
shapeEquals(NDArray) - Method in interface ai.djl.ndarray.NDArray: Checks 2 NDArrays for equal shapes.
shapeEquals(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Checks 2 NDArrays for equal shapes.
sigmoid(NDArray) - Static method in class ai.djl.nn.Activation: Applies Sigmoid activation on the input NDArray.
sigmoid(NDList) - Static method in class ai.djl.nn.Activation: Applies Sigmoid activation on the input singleton NDList.
sigmoidBinaryCrossEntropyLoss() - Static method in class ai.djl.training.loss.Loss: Returns a new instance of SigmoidBinaryCrossEntropyLoss with default arguments.
sigmoidBinaryCrossEntropyLoss(String) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of SigmoidBinaryCrossEntropyLoss with default arguments.
sigmoidBinaryCrossEntropyLoss(String, float, boolean) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of SigmoidBinaryCrossEntropyLoss with the given arguments.
SigmoidBinaryCrossEntropyLoss - Class in ai.djl.training.loss: SigmoidBinaryCrossEntropyLoss is a type of Loss.
SigmoidBinaryCrossEntropyLoss() - Constructor for class ai.djl.training.loss.SigmoidBinaryCrossEntropyLoss: Performs Sigmoid cross-entropy loss for binary classification.
SigmoidBinaryCrossEntropyLoss(String) - Constructor for class ai.djl.training.loss.SigmoidBinaryCrossEntropyLoss: Performs Sigmoid cross-entropy loss for binary classification.
SigmoidBinaryCrossEntropyLoss(String, float, boolean) - Constructor for class ai.djl.training.loss.SigmoidBinaryCrossEntropyLoss: Performs Sigmoid cross-entropy loss for binary classification.
sigmoidBlock() - Static method in class ai.djl.nn.Activation: Creates a LambdaBlock that applies the Sigmoid activation function in its forward function.
sign() - Method in interface ai.djl.ndarray.NDArray: Returns the element-wise sign.
sign() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the element-wise sign.
signi() - Method in interface ai.djl.ndarray.NDArray: Returns the element-wise sign in-place.
signi() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the element-wise sign in-place.
SimpleCompositeLoss - Class in ai.djl.training.loss: SimpleCompositeLoss is an implementation of the Loss abstract class that can combine different Loss functions by adding the individual losses together.
SimpleCompositeLoss() - Constructor for class ai.djl.training.loss.SimpleCompositeLoss: Creates a new empty instance of CompositeLoss that can combine the given Loss components.
SimpleCompositeLoss(String) - Constructor for class ai.djl.training.loss.SimpleCompositeLoss: Creates a new empty instance of CompositeLoss that can combine the given Loss components.
SimplePoseTranslator - Class in ai.djl.modality.cv.translator: A BaseImageTranslator that post-process the NDArray into human Joints.
SimplePoseTranslator(SimplePoseTranslator.Builder) - Constructor for class ai.djl.modality.cv.translator.SimplePoseTranslator: Creates the Pose Estimation translator from the given builder.
SimplePoseTranslator.Builder - Class in ai.djl.modality.cv.translator: The builder for Pose Estimation translator.
SimplePoseTranslatorFactory - Class in ai.djl.modality.cv.translator: An TranslatorFactory that creates a SimplePoseTranslator instance.
SimplePoseTranslatorFactory() - Constructor for class ai.djl.modality.cv.translator.SimplePoseTranslatorFactory
SimpleRepository - Class in ai.djl.repository: A SimpleRepository is a Repository containing only a single artifact without requiring a "metadata.json" file.
SimpleRepository(String, URI, Path) - Constructor for class ai.djl.repository.SimpleRepository: (Internal) Constructs a SimpleRepository.
SimpleText2TextTranslator - Class in ai.djl.modality.nlp.translator: A Translator that performs pre-process and post-processing for a sequence-to-sequence text model.
SimpleText2TextTranslator() - Constructor for class ai.djl.modality.nlp.translator.SimpleText2TextTranslator
SimpleTextEmbedding - Class in ai.djl.modality.nlp.embedding: A TextEmbedding that applies a WordEmbedding to each word independently.
SimpleTextEmbedding(WordEmbedding) - Constructor for class ai.djl.modality.nlp.embedding.SimpleTextEmbedding: Constructs a SimpleTextEmbedding.
SimpleTokenizer - Class in ai.djl.modality.nlp.preprocess: SimpleTokenizer is an implementation of the Tokenizer interface that converts sentences into token by splitting them by a given delimiter.
SimpleTokenizer() - Constructor for class ai.djl.modality.nlp.preprocess.SimpleTokenizer: Creates an instance of SimpleTokenizer with the default delimiter.
SimpleTokenizer(String) - Constructor for class ai.djl.modality.nlp.preprocess.SimpleTokenizer: Creates an instance of SimpleTokenizer with the given delimiter.
SimpleUrlRepository - Class in ai.djl.repository: A SimpleUrlRepository is a Repository contains an archive file from a HTTP URL.
sin() - Method in interface ai.djl.ndarray.NDArray: Returns the trigonometric sine of this NDArray element-wise.
sin() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the trigonometric sine of this NDArray element-wise.
SingleShotDetectionAccuracy - Class in ai.djl.training.evaluator: SingleShotDetectionAccuracy is an implementation of AbstractAccuracy.
SingleShotDetectionAccuracy(String) - Constructor for class ai.djl.training.evaluator.SingleShotDetectionAccuracy: Creates a new instance of SingleShotDetectionAccuracy with the given name.
SingleShotDetectionLoss - Class in ai.djl.training.loss: SingleShotDetectionLoss is an implementation of Loss.
SingleShotDetectionLoss() - Constructor for class ai.djl.training.loss.SingleShotDetectionLoss: Base class for metric with abstract update methods.
SingleShotDetectionTranslator - Class in ai.djl.modality.cv.translator: A BaseImageTranslator that post-process the NDArray into DetectedObjects with boundaries.
SingleShotDetectionTranslator(SingleShotDetectionTranslator.Builder) - Constructor for class ai.djl.modality.cv.translator.SingleShotDetectionTranslator: Creates the SSD translator from the given builder.
SingleShotDetectionTranslator.Builder - Class in ai.djl.modality.cv.translator: The builder for SSD translator.
SingleShotDetectionTranslatorFactory - Class in ai.djl.modality.cv.translator: An TranslatorFactory that creates a SingleShotDetectionTranslator instance.
SingleShotDetectionTranslatorFactory() - Constructor for class ai.djl.modality.cv.translator.SingleShotDetectionTranslatorFactory
singleton(Function<NDArray, NDArray>) - Static method in class ai.djl.nn.LambdaBlock: Creates a LambdaBlock for a singleton function.
singletonOrThrow() - Method in class ai.djl.ndarray.NDList: Returns the only element if this is a singleton NDList or throws an exception if multiple elements.
sinh() - Method in interface ai.djl.ndarray.NDArray: Returns the hyperbolic sine of this NDArray element-wise.
sinh() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the hyperbolic sine of this NDArray element-wise.
size() - Method in class ai.djl.modality.nlp.DefaultVocabulary: Returns the size of the Vocabulary.
size() - Method in interface ai.djl.modality.nlp.Vocabulary: Returns the size of the Vocabulary.
size() - Method in interface ai.djl.ndarray.NDArray: Returns the total number of elements in this NDArray.
size() - Method in class ai.djl.ndarray.types.Shape: Returns the total size.
size() - Method in class ai.djl.training.dataset.RandomAccessDataset: Returns the size of this Dataset.
size(int) - Method in interface ai.djl.ndarray.NDArray: Returns the size of this NDArray along a given axis.
size(int...) - Method in class ai.djl.ndarray.types.Shape: Returns the size of a specific dimension or several specific dimensions.
slice(int) - Method in class ai.djl.ndarray.types.Shape: Creates a new Shape whose content is a slice of this shape.
slice(int, int) - Method in class ai.djl.ndarray.types.Shape: Creates a new Shape whose content is a slice of this shape.
sliceAxis(int, long, long) - Static method in class ai.djl.ndarray.index.NDIndex: Creates an NDIndex that just has one slice in the given axis.
softmax(int) - Method in interface ai.djl.ndarray.NDArray: Applies the softmax function along the given axis.
softmax(int) - Method in class ai.djl.ndarray.NDArrayAdapter: Applies the softmax function along the given axis.
SOFTMAX_REGRESSION - Static variable in interface ai.djl.Application.Tabular: An application that takes a feature vector (table row) and predicts a categorical feature based on it.
softmaxCrossEntropyLoss() - Static method in class ai.djl.training.loss.Loss: Returns a new instance of SoftmaxCrossEntropyLoss with default arguments.
softmaxCrossEntropyLoss(String) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of SoftmaxCrossEntropyLoss with default arguments.
softmaxCrossEntropyLoss(String, float, int, boolean, boolean) - Static method in class ai.djl.training.loss.Loss: Returns a new instance of SoftmaxCrossEntropyLoss with the given arguments.
SoftmaxCrossEntropyLoss - Class in ai.djl.training.loss: SoftmaxCrossEntropyLoss is a type of Loss that calculates the softmax cross entropy loss.
SoftmaxCrossEntropyLoss() - Constructor for class ai.djl.training.loss.SoftmaxCrossEntropyLoss: Creates a new instance of SoftmaxCrossEntropyLoss with default parameters.
SoftmaxCrossEntropyLoss(String) - Constructor for class ai.djl.training.loss.SoftmaxCrossEntropyLoss: Creates a new instance of SoftmaxCrossEntropyLoss with default parameters.
SoftmaxCrossEntropyLoss(String, float, int, boolean, boolean) - Constructor for class ai.djl.training.loss.SoftmaxCrossEntropyLoss: Creates a new instance of SoftmaxCrossEntropyLoss with the given parameters.
softPlus(NDArray) - Static method in class ai.djl.nn.Activation: Applies softPlus activation on the input NDArray.
softPlus(NDList) - Static method in class ai.djl.nn.Activation: Applies softPlus activation on the input singleton NDList.
softPlusBlock() - Static method in class ai.djl.nn.Activation: Creates a LambdaBlock that applies the Activation.softPlus(NDList) activation function in its forward function.
softSign(NDArray) - Static method in class ai.djl.nn.Activation: Applies softSign activation on the input NDArray.
softSign(NDList) - Static method in class ai.djl.nn.Activation: Applies softPlus activation on the input singleton NDList.
softSignBlock() - Static method in class ai.djl.nn.Activation: Creates a LambdaBlock that applies the Activation.softSign(NDList) activation function in its forward function.
sort() - Method in interface ai.djl.ndarray.NDArray: Sorts the flattened NDArray.
sort() - Method in class ai.djl.ndarray.NDArrayAdapter: Sorts the flattened NDArray.
sort(int) - Method in interface ai.djl.ndarray.NDArray: Sorts the flattened NDArray.
sort(int) - Method in class ai.djl.ndarray.NDArrayAdapter: Sorts the flattened NDArray.
sparseFormat - Variable in class ai.djl.nn.core.Embedding.BaseBuilder
sparseFormat - Variable in class ai.djl.nn.core.Embedding
SparseFormat - Enum in ai.djl.ndarray.types: An enum representing Sparse matrix storage formats.
SparseNDArray - Interface in ai.djl.ndarray: An interface representing a Sparse NDArray.
split(long) - Method in interface ai.djl.ndarray.NDArray: Splits this NDArray into multiple subNDArrays given sections along first axis.
split(long[]) - Method in interface ai.djl.ndarray.NDArray: Splits this NDArray into multiple sub-NDArrays given indices along first axis.
split(long[], int) - Method in interface ai.djl.ndarray.NDArray: Splits this NDArray into multiple sub-NDArrays given indices along given axis.
split(long[], int) - Method in class ai.djl.ndarray.NDArrayAdapter: Splits this NDArray into multiple sub-NDArrays given indices along given axis.
split(long, int) - Method in interface ai.djl.ndarray.NDArray: Splits this NDArray into multiple subNDArrays given sections along the given axis.
split(long, int) - Method in class ai.djl.ndarray.NDArrayAdapter: Splits this NDArray into multiple subNDArrays given sections along the given axis.
split(Device[], boolean) - Method in class ai.djl.training.dataset.Batch: Splits the data and labels in the Batch across the given devices.
split(NDList, int, boolean) - Method in interface ai.djl.translate.Batchifier: Splits the given NDList into the given number of slices.
split(NDList, int, boolean) - Method in class ai.djl.translate.PaddingStackBatchifier: Splits the given NDList into the given number of slices.
split(NDList, int, boolean) - Method in class ai.djl.translate.StackBatchifier: Splits the given NDList into the given number of slices.
sqrt() - Method in interface ai.djl.ndarray.NDArray: Returns the square root of this NDArray element-wise.
sqrt() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the square root of this NDArray element-wise.
square() - Method in interface ai.djl.ndarray.NDArray: Returns the square of this NDArray element-wise.
square() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the square of this NDArray element-wise.
squeeze() - Method in interface ai.djl.ndarray.NDArray: Removes all singleton dimensions from this NDArray Shape.
squeeze(int) - Method in interface ai.djl.ndarray.NDArray: Removes a singleton dimension at the given axis.
squeeze(int[]) - Method in interface ai.djl.ndarray.NDArray: Removes singleton dimensions at the given axes.
squeeze(int[]) - Method in class ai.djl.ndarray.NDArrayAdapter: Removes singleton dimensions at the given axes.
stack(NDArray) - Method in interface ai.djl.ndarray.NDArray: Joins a NDArray along the first axis.
stack(NDArray, int) - Method in interface ai.djl.ndarray.NDArray: Joins a NDArray along a new axis.
stack(NDList) - Static method in class ai.djl.ndarray.NDArrays: Joins a sequence of NDArrays in NDList along the first axis.
stack(NDList, int) - Static method in class ai.djl.ndarray.NDArrays: Joins a sequence of NDArrays in NDList along a new axis.
STACK - Static variable in interface ai.djl.translate.Batchifier
StackBatchifier - Class in ai.djl.translate: StackBatchifier is used to merge a list of samples to form a mini-batch of NDArray(s).
StackBatchifier() - Constructor for class ai.djl.translate.StackBatchifier
StandardCapabilities - Class in ai.djl.engine: Constant definitions for the standard capability.
start(long) - Method in class ai.djl.training.util.ProgressBar
stateSize - Variable in class ai.djl.nn.recurrent.RecurrentBlock.BaseBuilder
stateSize - Variable in class ai.djl.nn.recurrent.RecurrentBlock
step() - Method in class ai.djl.training.Trainer: Updates all of the parameters of the model once.
step(NDList, boolean) - Method in interface ai.djl.modality.rl.env.RlEnv: Takes a step by performing an action in this environment.
stopGradient() - Method in interface ai.djl.ndarray.NDArray: Returns an NDArray equal to this that stop gradient propagation through it.
stopGradient() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns an NDArray equal to this that stop gradient propagation through it.
stream() - Method in class ai.djl.ndarray.index.NDIndex: Returns a stream of the NDIndexElements.
stream() - Method in class ai.djl.ndarray.types.Shape: Returns a stream of the Shape.
stride - Variable in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder
stride - Variable in class ai.djl.nn.convolutional.Convolution
stride - Variable in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder
stride - Variable in class ai.djl.nn.convolutional.Deconvolution
STRING - ai.djl.ndarray.types.DataType.Format
STRING - ai.djl.ndarray.types.DataType
stringValue(Map<String, ?>, String) - Static method in class ai.djl.translate.ArgumentsUtil: Returns the string value from the arguments.
stringValue(Map<String, ?>, String, String) - Static method in class ai.djl.translate.ArgumentsUtil: Returns the string value from the arguments.
StyleTransferTranslator - Class in ai.djl.modality.cv.translator: Built-in Translator that provides preprocessing and postprocessing for StyleTransfer.
StyleTransferTranslator() - Constructor for class ai.djl.modality.cv.translator.StyleTransferTranslator
StyleTransferTranslatorFactory - Class in ai.djl.modality.cv.translator: A TranslatorFactory that creates a StyleTransferTranslator instance.
StyleTransferTranslatorFactory() - Constructor for class ai.djl.modality.cv.translator.StyleTransferTranslatorFactory
sub(NDArray) - Method in interface ai.djl.ndarray.NDArray: Subtracts the other NDArray from this NDArray element-wise.
sub(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Subtracts the other NDArray from this NDArray element-wise.
sub(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Subtracts a NDArray from a NDArray element-wise.
sub(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Subtracts a number from the NDArray element-wise.
sub(Number) - Method in interface ai.djl.ndarray.NDArray: Subtracts a number from this NDArray element-wise.
sub(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Subtracts a number from this NDArray element-wise.
sub(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Subtracts a NDArray from a number element-wise.
subDataset(int, int) - Method in class ai.djl.training.dataset.RandomAccessDataset: Returns a view of the portion of this data between the specified fromIndex, inclusive, and toIndex, exclusive.
subi(NDArray) - Method in interface ai.djl.ndarray.NDArray: Subtracts the other NDArray from this NDArray element-wise in place.
subi(NDArray) - Method in class ai.djl.ndarray.NDArrayAdapter: Subtracts the other NDArray from this NDArray element-wise in place.
subi(NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Subtracts a NDArray from a NDArray element-wise in place.
subi(NDArray, Number) - Static method in class ai.djl.ndarray.NDArrays: Subtracts a number from the NDArray element-wise in place.
subi(Number) - Method in interface ai.djl.ndarray.NDArray: Subtracts a number from this NDArray element-wise in place.
subi(Number) - Method in class ai.djl.ndarray.NDArrayAdapter: Subtracts a number from this NDArray element-wise in place.
subi(Number, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Subtracts a NDArray from a number element-wise in place.
subManagerOf(NDResource) - Static method in interface ai.djl.ndarray.NDManager: Creates a new manager based on the given resource.
subNDList(int) - Method in class ai.djl.ndarray.NDList: Returns a view of the portion of this NDList between the specified fromIndex, inclusive, and to the end.
sum() - Method in interface ai.djl.ndarray.NDArray: Returns the sum of this NDArray.
sum() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the sum of this NDArray.
sum(int[]) - Method in interface ai.djl.ndarray.NDArray: Returns the sum of this NDArray along given axes.
sum(int[], boolean) - Method in interface ai.djl.ndarray.NDArray: Returns the sum of this NDArray along given axes.
sum(int[], boolean) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the sum of this NDArray along given axes.
swapAxes(int, int) - Method in interface ai.djl.ndarray.NDArray: Interchanges two axes of this NDArray.
swish(NDArray, float) - Static method in class ai.djl.nn.Activation: Applies Swish activation on the input NDArray.
swish(NDList, float) - Static method in class ai.djl.nn.Activation: Applies SWish activation on the input singleton NDList.
swishBlock(float) - Static method in class ai.djl.nn.Activation: Creates a LambdaBlock that applies the Swish activation function in its forward function.
SymbolBlock - Interface in ai.djl.nn: SymbolBlock is a Block is used to load models that were exported directly from the engine in its native format.
sync() - Method in class ai.djl.training.ParameterStore: Synchronizes the values on all mirrors with the main parameter.
synsetLoader - Variable in class ai.djl.modality.cv.translator.BaseImageTranslator.ClassificationBuilder
SynsetLoader(String) - Constructor for class ai.djl.modality.cv.translator.BaseImageTranslator.SynsetLoader
SynsetLoader(URL) - Constructor for class ai.djl.modality.cv.translator.BaseImageTranslator.SynsetLoader
SynsetLoader(List<String>) - Constructor for class ai.djl.modality.cv.translator.BaseImageTranslator.SynsetLoader

T

tail() - Method in class ai.djl.ndarray.types.Shape: Returns the tail index of the shape.
tan() - Method in interface ai.djl.ndarray.NDArray: Returns the trigonometric tangent of this NDArray element-wise.
tan() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the trigonometric tangent of this NDArray element-wise.
tanh() - Method in interface ai.djl.ndarray.NDArray: Returns the hyperbolic tangent of this NDArray element-wise.
tanh() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the hyperbolic tangent of this NDArray element-wise.
tanh(NDArray) - Static method in class ai.djl.nn.Activation: Applies Tanh activation on the input NDArray.
tanh(NDList) - Static method in class ai.djl.nn.Activation: Applies Tanh activation on the input singleton NDList.
TANH - ai.djl.nn.recurrent.RNN.Activation
tanhBlock() - Static method in class ai.djl.nn.Activation: Creates a LambdaBlock that applies the Tanh activation function in its forward function.
target(NDList) - Method in class ai.djl.modality.cv.MultiBoxTarget: Computes multi-box training targets.
targetPipeline - Variable in class ai.djl.training.dataset.RandomAccessDataset.BaseBuilder
targetPipeline - Variable in class ai.djl.training.dataset.RandomAccessDataset
tempAttach(NDManager) - Method in class ai.djl.ndarray.NDArrayAdapter: Temporarily attaches this NDResource to the specified NDManager.
tempAttach(NDManager) - Method in class ai.djl.ndarray.NDList: Temporarily attaches this NDResource to the specified NDManager.
tempAttach(NDManager) - Method in interface ai.djl.ndarray.NDResource: Temporarily attaches this NDResource to the specified NDManager.
tempAttachAll(NDResource...) - Method in interface ai.djl.ndarray.NDManager: Temporarily attaches all resources to this manager.
tempAttachInternal(NDManager, String, NDResource) - Method in class ai.djl.ndarray.BaseNDManager: Temporarily attaches a resource to this NDManager to be returned when this is closed.
tempAttachInternal(NDManager, String, NDResource) - Method in interface ai.djl.ndarray.NDManager: Temporarily attaches a resource to this NDManager to be returned when this is closed.
TempResource(NDResource, NDManager) - Constructor for class ai.djl.ndarray.BaseNDManager.TempResource
tempResources - Variable in class ai.djl.ndarray.BaseNDManager
TERABITS - ai.djl.metric.Unit
TERABITS_PER_SECOND - ai.djl.metric.Unit
TERABYTES - ai.djl.metric.Unit
TERABYTES_PER_SECOND - ai.djl.metric.Unit
TEST - ai.djl.training.dataset.Dataset.Usage
TEXT_CLASSIFICATION - Static variable in interface ai.djl.Application.NLP: An application that classifies text data.
TEXT_EMBEDDING - Static variable in interface ai.djl.Application.NLP: An application that takes text and returns a feature vector that represents the text.
TextClassificationServingTranslator - Class in ai.djl.modality.nlp.translator: A Translator that can handle generic text classification Input and Output.
TextClassificationServingTranslator(Translator<String, Classifications>) - Constructor for class ai.djl.modality.nlp.translator.TextClassificationServingTranslator: Constructs a TextClassificationServingTranslator instance.
TextCleaner - Class in ai.djl.modality.nlp.preprocess: Applies remove or replace of certain characters based on condition.
TextCleaner(Function<Character, Boolean>) - Constructor for class ai.djl.modality.nlp.preprocess.TextCleaner: Remove a character if it meets the condition supplied.
TextCleaner(Function<Character, Boolean>, char) - Constructor for class ai.djl.modality.nlp.preprocess.TextCleaner: Replace a character if it meets the condition supplied.
TextEmbedding - Interface in ai.djl.modality.nlp.embedding: A class to manage 1-D NDArray representations of multiple words.
TextProcessor - Interface in ai.djl.modality.nlp.preprocess: TextProcessor allows applying pre-processing to input tokens for natural language applications.
TextTerminator - Class in ai.djl.modality.nlp.preprocess: A TextProcessor that adds a beginning of string and end of string token.
TextTerminator() - Constructor for class ai.djl.modality.nlp.preprocess.TextTerminator: Constructs a default TextTerminator.
TextTerminator(boolean, boolean) - Constructor for class ai.djl.modality.nlp.preprocess.TextTerminator: Constructs a TextTerminator using the default tokens.
TextTerminator(boolean, boolean, String, String) - Constructor for class ai.djl.modality.nlp.preprocess.TextTerminator: Constructs a TextTerminator.
TextTruncator - Class in ai.djl.modality.nlp.preprocess: TextProcessor that truncates text to a maximum size.
TextTruncator(int) - Constructor for class ai.djl.modality.nlp.preprocess.TextTruncator: Constructs a TextTruncator.
threshold - Variable in class ai.djl.modality.cv.translator.ObjectDetectionTranslator.ObjectDetectionBuilder
threshold - Variable in class ai.djl.modality.cv.translator.ObjectDetectionTranslator
tile(int, long) - Method in interface ai.djl.ndarray.NDArray: Constructs a NDArray by repeating this NDArray the number of times given by repeats along given axis.
tile(int, long) - Method in class ai.djl.ndarray.NDArrayAdapter: Constructs a NDArray by repeating this NDArray the number of times given by repeats along given axis.
tile(long) - Method in interface ai.djl.ndarray.NDArray: Constructs a NDArray by repeating this NDArray the number of times given repeats.
tile(long) - Method in class ai.djl.ndarray.NDArrayAdapter: Constructs a NDArray by repeating this NDArray the number of times given repeats.
tile(long[]) - Method in interface ai.djl.ndarray.NDArray: Constructs a NDArray by repeating this NDArray the number of times given by repeats.
tile(long[]) - Method in class ai.djl.ndarray.NDArrayAdapter: Constructs a NDArray by repeating this NDArray the number of times given by repeats.
tile(Shape) - Method in interface ai.djl.ndarray.NDArray: Constructs a NDArray by repeating this NDArray the number of times to match the desired shape.
tile(Shape) - Method in class ai.djl.ndarray.NDArrayAdapter: Constructs a NDArray by repeating this NDArray the number of times to match the desired shape.
TIME - ai.djl.ndarray.types.LayoutType
TimeMeasureTrainingListener - Class in ai.djl.training.listener: TrainingListener that outputs the training time metrics after training is done.
TimeMeasureTrainingListener(String) - Constructor for class ai.djl.training.listener.TimeMeasureTrainingListener: Constructs a TimeMeasureTrainingListener.
toArray() - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray to a Number array based on its DataType.
toArray() - Method in class ai.djl.training.dataset.RandomAccessDataset: Returns the dataset contents as a Java array.
toBooleanArray() - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray to a boolean array.
toByteArray() - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray to a byte array.
toByteBuffer() - Method in class ai.djl.modality.Classifications: Returns the ByteBuffer presentation of the object.
toByteBuffer() - Method in interface ai.djl.ndarray.BytesSupplier: Returns the ByteBuffer presentation of the object.
toByteBuffer() - Method in class ai.djl.ndarray.NDList: Returns the ByteBuffer presentation of the object.
toDebugString() - Method in interface ai.djl.ndarray.NDArray: Runs the debug string representation of this NDArray.
toDebugString(int, int, int, int) - Method in interface ai.djl.ndarray.NDArray: Runs the debug string representation of this NDArray.
toDegrees() - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray from radians to degrees element-wise.
toDegrees() - Method in class ai.djl.ndarray.NDArrayAdapter: Converts this NDArray from radians to degrees element-wise.
toDense() - Method in interface ai.djl.ndarray.NDArray: Returns a dense representation of the sparse NDArray.
toDense() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns a dense representation of the sparse NDArray.
toDevice(Device, boolean) - Method in interface ai.djl.ndarray.NDArray: Moves this NDArray to a different Device.
toDevice(Device, boolean) - Method in class ai.djl.ndarray.NDArrayAdapter: Moves this NDArray to a different Device.
toDevice(Device, boolean) - Method in class ai.djl.ndarray.NDList: Converts all the NDArray in NDList to a different Device.
toDeviceType(Device) - Static method in interface ai.djl.DeviceType: Map device to its type number.
toDoubleArray() - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray to a double array.
toFloatArray() - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray to a float array.
toIntArray() - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray to an int array.
toJson() - Method in class ai.djl.modality.Classifications
toJson() - Method in class ai.djl.modality.cv.output.DetectedObjects
tokenize(String) - Method in class ai.djl.modality.nlp.bert.BertFullTokenizer: Breaks down the given sentence into a list of tokens that can be represented by embeddings.
tokenize(String) - Method in class ai.djl.modality.nlp.bert.BertTokenizer: Breaks down the given sentence into a list of tokens that can be represented by embeddings.
tokenize(String) - Method in class ai.djl.modality.nlp.bert.WordpieceTokenizer: Breaks down the given sentence into a list of tokens that can be represented by embeddings.
tokenize(String) - Method in class ai.djl.modality.nlp.preprocess.SimpleTokenizer: Breaks down the given sentence into a list of tokens that can be represented by embeddings.
tokenize(String) - Method in interface ai.djl.modality.nlp.preprocess.Tokenizer: Breaks down the given sentence into a list of tokens that can be represented by embeddings.
Tokenizer - Interface in ai.djl.modality.nlp.preprocess: Tokenizer interface provides the ability to break-down sentences into embeddable tokens.
tokenizerName - Variable in class ai.djl.modality.nlp.translator.QATranslator
tokenToString(List<String>) - Method in class ai.djl.modality.nlp.bert.BertFullTokenizer: Returns a string presentation of the tokens.
tokenToString(List<String>) - Method in class ai.djl.modality.nlp.bert.BertTokenizer: Returns a string presentation of the tokens.
toLayoutString() - Method in class ai.djl.ndarray.types.Shape: Returns the string layout type for each axis in this shape.
toLongArray() - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray to a long array.
toLowerCase - Variable in class ai.djl.modality.nlp.translator.QATranslator
toNDArray(NDManager) - Method in interface ai.djl.modality.cv.Image: Converts image to a RGB NDArray.
toNDArray(NDManager, Image.Flag) - Method in interface ai.djl.modality.cv.Image: Converts image to a NDArray.
topK() - Method in class ai.djl.modality.Classifications: Returns a list of the top classes.
topK(int) - Method in class ai.djl.modality.Classifications: Returns a list of the top k best classes.
TopKAccuracy - Class in ai.djl.training.evaluator: TopKAccuracy is an Evaluator that computes the accuracy of the top k predictions.
TopKAccuracy(int) - Constructor for class ai.djl.training.evaluator.TopKAccuracy: Creates an instance of TopKAccuracy evaluator that computes topK accuracy across axis 1 along the 0th index.
TopKAccuracy(String, int) - Constructor for class ai.djl.training.evaluator.TopKAccuracy: Creates a TopKAccuracy instance.
toRadians() - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray from degrees to radians element-wise.
toRadians() - Method in class ai.djl.ndarray.NDArrayAdapter: Converts this NDArray from degrees to radians element-wise.
toSparse(SparseFormat) - Method in interface ai.djl.ndarray.NDArray: Returns a sparse representation of NDArray.
toSparse(SparseFormat) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns a sparse representation of NDArray.
toString() - Method in class ai.djl.Application
toString() - Method in class ai.djl.BaseModel
toString() - Method in class ai.djl.Device
toString() - Method in class ai.djl.metric.Metric
toString() - Method in class ai.djl.modality.Classifications.Classification
toString() - Method in class ai.djl.modality.Classifications
toString() - Method in class ai.djl.modality.cv.output.DetectedObjects.DetectedObject
toString() - Method in class ai.djl.modality.cv.output.Joints.Joint
toString() - Method in class ai.djl.modality.cv.output.Joints
toString() - Method in class ai.djl.modality.cv.output.Rectangle
toString() - Method in class ai.djl.modality.Input: *
toString() - Method in class ai.djl.ndarray.BaseNDManager
toString() - Method in class ai.djl.ndarray.NDArrayAdapter
toString() - Method in class ai.djl.ndarray.NDList
toString() - Method in class ai.djl.ndarray.types.DataDesc
toString() - Method in enum ai.djl.ndarray.types.DataType
toString() - Method in class ai.djl.ndarray.types.Shape
toString() - Method in class ai.djl.nn.AbstractBaseBlock
toString() - Method in class ai.djl.nn.LambdaBlock
toString() - Method in class ai.djl.nn.norm.Dropout
toString() - Method in class ai.djl.nn.ParallelBlock
toString() - Method in class ai.djl.nn.SequentialBlock
toString() - Method in class ai.djl.repository.Artifact
toString() - Method in class ai.djl.repository.MRL
toString() - Method in class ai.djl.repository.Version
toString() - Method in class ai.djl.repository.VersionRange
toString() - Method in class ai.djl.repository.zoo.BaseModelLoader
toString() - Method in class ai.djl.repository.zoo.Criteria
toString() - Method in class ai.djl.training.hyperparameter.param.HpCategorical
toString() - Method in class ai.djl.training.hyperparameter.param.HpFloat
toString() - Method in class ai.djl.training.hyperparameter.param.HpInt
toString() - Method in class ai.djl.training.hyperparameter.param.HpSet
toString() - Method in class ai.djl.training.hyperparameter.param.HpVal
toString() - Method in class ai.djl.training.TrainingResult: *
toString(LayoutType[]) - Static method in enum ai.djl.ndarray.types.LayoutType: Converts a layout type array to a string of the character representations.
toStringArray() - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray to a String array.
toStringArray(Charset) - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray to a String array with the specified charset.
toStringArray(Charset) - Method in class ai.djl.ndarray.NDArrayAdapter: Converts this NDArray to a String array with the specified charset.
totalInstances - Variable in class ai.djl.training.evaluator.Evaluator
toTensor(NDArray) - Static method in class ai.djl.modality.cv.util.NDImageUtils: Converts an image NDArray from preprocessing format to Neural Network format.
ToTensor - Class in ai.djl.modality.cv.transform: A Transform that converts an image NDArray from preprocessing format to Neural Network format.
ToTensor() - Constructor for class ai.djl.modality.cv.transform.ToTensor
toType(DataType, boolean) - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray to a different DataType.
toType(DataType, boolean) - Method in class ai.djl.ndarray.NDArrayAdapter: Converts this NDArray to a different DataType.
toUint8Array() - Method in interface ai.djl.ndarray.NDArray: Converts this NDArray to a uint8 array.
toURI() - Method in class ai.djl.repository.MRL: Returns the URI to the metadata location (used for Repository implementations).
trace() - Method in interface ai.djl.ndarray.NDArray: Returns the sum along diagonals of this NDArray.
trace(int) - Method in interface ai.djl.ndarray.NDArray: Returns the sum along diagonals of this NDArray.
trace(int, int, int) - Method in interface ai.djl.ndarray.NDArray: Returns the sum along diagonals of this NDArray.
trace(int, int, int) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the sum along diagonals of this NDArray.
Tracker - Interface in ai.djl.training.tracker: A Tracker represents a hyper-parameter that changes gradually through the training process.
TRAIN - ai.djl.training.dataset.Dataset.Usage
TRAIN_ALL - Static variable in class ai.djl.training.listener.EvaluatorTrainingListener
TRAIN_EPOCH - Static variable in class ai.djl.training.listener.EvaluatorTrainingListener
TRAIN_PROGRESS - Static variable in class ai.djl.training.listener.EvaluatorTrainingListener
TrainableTextEmbedding - Class in ai.djl.modality.nlp.embedding: TrainableTextEmbedding is an implementation of TextEmbedding based on TrainableWordEmbedding block.
TrainableTextEmbedding(TrainableWordEmbedding) - Constructor for class ai.djl.modality.nlp.embedding.TrainableTextEmbedding: Constructs a TrainableTextEmbedding.
TrainableWordEmbedding - Class in ai.djl.modality.nlp.embedding: TrainableWordEmbedding is an implementation of WordEmbedding and Embedding based on a DefaultVocabulary.
TrainableWordEmbedding(TrainableWordEmbedding.Builder) - Constructor for class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Constructs a new instance of TrainableWordEmbedding from the TrainableWordEmbedding.Builder.
TrainableWordEmbedding(Vocabulary, int) - Constructor for class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Constructs a new instance of TrainableWordEmbedding from a DefaultVocabulary and a given embedding size.
TrainableWordEmbedding(NDArray, List<String>) - Constructor for class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Constructs a pretrained embedding.
TrainableWordEmbedding(NDArray, List<String>, SparseFormat) - Constructor for class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Constructs a pretrained embedding.
TrainableWordEmbedding.Builder - Class in ai.djl.modality.nlp.embedding: A builder for a TrainableWordEmbedding.
trainBatch(RlEnv.Step[]) - Method in class ai.djl.modality.rl.agent.EpsilonGreedy: Trains this RlAgent on a batch of RlEnv.Steps.
trainBatch(RlEnv.Step[]) - Method in class ai.djl.modality.rl.agent.QAgent: Trains this RlAgent on a batch of RlEnv.Steps.
trainBatch(RlEnv.Step[]) - Method in interface ai.djl.modality.rl.agent.RlAgent: Trains this RlAgent on a batch of RlEnv.Steps.
trainBatch(Trainer, Batch) - Static method in class ai.djl.training.EasyTrain: Trains the model with one iteration of the given Batch of data.
Trainer - Class in ai.djl.training: The Trainer interface provides a session for model training.
Trainer(Model, TrainingConfig) - Constructor for class ai.djl.training.Trainer: Creates an instance of Trainer with the given Model and TrainingConfig.
TrainingConfig - Interface in ai.djl.training: An interface that is responsible for holding the configuration required by Trainer.
TrainingDivergedException - Exception in ai.djl: Thrown to indicate when there is a divergence during Training.
TrainingDivergedException(String) - Constructor for exception ai.djl.TrainingDivergedException: Constructs a new exception with the specified detail message.
TrainingDivergedException(String, Throwable) - Constructor for exception ai.djl.TrainingDivergedException: Constructs a new exception with the specified detail message and cause.
TrainingDivergedException(Throwable) - Constructor for exception ai.djl.TrainingDivergedException: Constructs a new exception with the specified cause and a detail message of (cause==null ? null : cause.toString()) which typically contains the class and detail message of cause.
TrainingListener - Interface in ai.djl.training.listener: TrainingListener offers an interface that performs some actions when certain events have occurred in the Trainer.
TrainingListener.BatchData - Class in ai.djl.training.listener: A class to pass data from the batch into the training listeners.
TrainingListener.Defaults - Interface in ai.djl.training.listener: Contains default TrainingListener sets.
TrainingListenerAdapter - Class in ai.djl.training.listener: Base implementation of the training listener that does nothing.
TrainingListenerAdapter() - Constructor for class ai.djl.training.listener.TrainingListenerAdapter
TrainingResult - Class in ai.djl.training: A class that is responsible for holding the training result produced by Trainer.
TrainingResult() - Constructor for class ai.djl.training.TrainingResult
transform(NDArray) - Method in class ai.djl.modality.cv.transform.CenterCrop: Applies the Transform to the given NDArray.
transform(NDArray) - Method in class ai.djl.modality.cv.transform.Crop: Applies the Transform to the given NDArray.
transform(NDArray) - Method in class ai.djl.modality.cv.transform.Normalize: Applies the Transform to the given NDArray.
transform(NDArray) - Method in class ai.djl.modality.cv.transform.RandomBrightness: Applies the Transform to the given NDArray.
transform(NDArray) - Method in class ai.djl.modality.cv.transform.RandomColorJitter: Applies the Transform to the given NDArray.
transform(NDArray) - Method in class ai.djl.modality.cv.transform.RandomFlipLeftRight: Applies the Transform to the given NDArray.
transform(NDArray) - Method in class ai.djl.modality.cv.transform.RandomFlipTopBottom: Applies the Transform to the given NDArray.
transform(NDArray) - Method in class ai.djl.modality.cv.transform.RandomHue: Applies the Transform to the given NDArray.
transform(NDArray) - Method in class ai.djl.modality.cv.transform.RandomResizedCrop: Applies the Transform to the given NDArray.
transform(NDArray) - Method in class ai.djl.modality.cv.transform.Resize: Applies the Transform to the given NDArray.
transform(NDArray) - Method in class ai.djl.modality.cv.transform.ToTensor: Applies the Transform to the given NDArray.
transform(NDArray) - Method in class ai.djl.training.util.MinMaxScaler: Transforms the data using the previous calculated minimum and maximum.
transform(NDArray) - Method in interface ai.djl.translate.Transform: Applies the Transform to the given NDArray.
transform(NDList) - Method in class ai.djl.translate.Pipeline: Applies the transforms configured in this object on the input NDList.
Transform - Interface in ai.djl.translate: An interface to apply various transforms to the input.
TransformerEncoderBlock - Class in ai.djl.nn.transformer: Self-Attention based transformer encoder block.
TransformerEncoderBlock(int, int, int, float, Function<NDList, NDList>) - Constructor for class ai.djl.nn.transformer.TransformerEncoderBlock: Creates a transformer encoder block.
transformi(NDArray) - Method in class ai.djl.training.util.MinMaxScaler: Transforms the data in-place using the previous calculated minimum and maximum.
TranslateException - Exception in ai.djl.translate: Thrown to indicate that an error is raised during processing of the input or output.
TranslateException(String) - Constructor for exception ai.djl.translate.TranslateException: Constructs a new exception with the specified detail message.
TranslateException(String, Throwable) - Constructor for exception ai.djl.translate.TranslateException: Constructs a new exception with the specified detail message and cause.
TranslateException(Throwable) - Constructor for exception ai.djl.translate.TranslateException: Constructs a new exception with the specified cause and a detail message of (cause==null ? null : cause.toString()) which typically contains the class and detail message of cause.
Translator<I,O> - Interface in ai.djl.translate: The Translator interface provides model pre-processing and postprocessing functionality.
TranslatorContext - Interface in ai.djl.translate: The TranslatorContext interface provides a toolkit for pre-processing and postprocessing functionality.
TranslatorFactory - Interface in ai.djl.translate: A utility class creates Translator instances.
translators - Variable in class ai.djl.translate.DefaultTranslatorFactory
transpose() - Method in interface ai.djl.ndarray.NDArray: Returns this NDArray with axes transposed.
transpose() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns this NDArray with axes transposed.
transpose(int...) - Method in interface ai.djl.ndarray.NDArray: Returns this NDArray with given axes transposed.
transpose(int...) - Method in class ai.djl.ndarray.NDArrayAdapter: Returns this NDArray with given axes transposed.
trunc() - Method in interface ai.djl.ndarray.NDArray: Returns the truncated value of this NDArray element-wise.
trunc() - Method in class ai.djl.ndarray.NDArrayAdapter: Returns the truncated value of this NDArray element-wise.
truncatedNormal(float, float, Shape, DataType) - Method in class ai.djl.ndarray.BaseNDManager: Draws random samples from a normal (Gaussian) distribution, discarding and re-drawing any samples that are more than two standard deviations from the mean.
truncatedNormal(float, float, Shape, DataType) - Method in interface ai.djl.ndarray.NDManager: Draws random samples from a normal (Gaussian) distribution, discarding and re-drawing any samples that are more than two standard deviations from the mean.
truncatedNormal(float, float, Shape, DataType, Device) - Method in interface ai.djl.ndarray.NDManager: Draws random samples from a normal (Gaussian) distribution, discarding and re-drawing any samples that are more than two standard deviations from the mean.
truncatedNormal(Shape) - Method in interface ai.djl.ndarray.NDManager: Draws random samples from a normal (Gaussian) distribution with mean 0 and standard deviation 1, discarding and re-drawing any samples that are more than two standard deviations from the mean.
truncatedNormal(Shape, DataType) - Method in interface ai.djl.ndarray.NDManager: Draws random samples from a normal (Gaussian) distribution with mean 0 and standard deviation 1, discarding and re-drawing any samples that are more than two standard deviations from the mean.
TruncatedNormalInitializer - Class in ai.djl.training.initializer: Naive implementation of a truncated normal initializer.
TruncatedNormalInitializer() - Constructor for class ai.djl.training.initializer.TruncatedNormalInitializer: Creates an instance of TruncatedNormalInitializer with a default sigma of 0.01.
TruncatedNormalInitializer(float) - Constructor for class ai.djl.training.initializer.TruncatedNormalInitializer: Creates a TruncatedNormalInitializer initializer.
truncation - Variable in class ai.djl.modality.nlp.translator.QATranslator

U

uid - Variable in class ai.djl.ndarray.BaseNDManager
uid - Variable in class ai.djl.ndarray.NDArrayAdapter
UINT - ai.djl.ndarray.types.DataType.Format
UINT8 - ai.djl.ndarray.types.DataType
unbatchify(NDList) - Method in interface ai.djl.translate.Batchifier: Reverses the batchify operation.
unbatchify(NDList) - Method in class ai.djl.translate.PaddingStackBatchifier: Reverses the batchify operation.
unbatchify(NDList) - Method in class ai.djl.translate.StackBatchifier: Reverses the batchify operation.
undefined(Repository, String, String) - Static method in class ai.djl.repository.MRL: Creates a dataset MRL with specified application.
UNDEFINED - Static variable in class ai.djl.Application
unembed(long) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Returns the item corresponding to the given index.
unembed(long) - Method in interface ai.djl.nn.core.AbstractIndexedEmbedding: Returns the item corresponding to the given index.
unembed(long) - Method in class ai.djl.nn.core.ConstantEmbedding: Returns the item corresponding to the given index.
unembed(long) - Method in class ai.djl.nn.core.Embedding.DefaultEmbedding: Returns the item corresponding to the given index.
unembed(long) - Method in class ai.djl.nn.core.Embedding.DefaultItem: Returns the item corresponding to the given index.
unembedText(NDArray) - Method in class ai.djl.modality.nlp.embedding.ModelZooTextEmbedding: Returns the closest matching text for a given embedding.
unembedText(NDArray) - Method in class ai.djl.modality.nlp.embedding.SimpleTextEmbedding: Returns the closest matching text for a given embedding.
unembedText(NDArray) - Method in interface ai.djl.modality.nlp.embedding.TextEmbedding: Returns the closest matching text for a given embedding.
unembedText(NDArray) - Method in class ai.djl.modality.nlp.embedding.TrainableTextEmbedding: Returns the closest matching text for a given embedding.
unembedWord(NDArray) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Returns the closest matching word for the given index.
unembedWord(NDArray) - Method in interface ai.djl.modality.nlp.embedding.WordEmbedding: Returns the closest matching word for the given index.
UnicodeNormalizer - Class in ai.djl.modality.nlp.preprocess: Applies unicode normalization to input strings.
UnicodeNormalizer() - Constructor for class ai.djl.modality.nlp.preprocess.UnicodeNormalizer: Default version of the Unicode Normalizer using NFKC normal form.
UnicodeNormalizer(Normalizer.Form) - Constructor for class ai.djl.modality.nlp.preprocess.UnicodeNormalizer: Unicode normalizer with a configurable normal form.
UNIFORM - ai.djl.training.initializer.XavierInitializer.RandomType
UniformInitializer - Class in ai.djl.training.initializer: UniformInitializer initializes weights with random values uniformly sampled from a given range.
UniformInitializer() - Constructor for class ai.djl.training.initializer.UniformInitializer: Creates an instance of UniformInitializer with a default scale of 0.07.
UniformInitializer(float) - Constructor for class ai.djl.training.initializer.UniformInitializer: Initializes a uniform initializer.
Unit - Enum in ai.djl.metric: An interface holds metric unit constants.
UNKNOWN - ai.djl.ndarray.types.DataType.Format
UNKNOWN - ai.djl.ndarray.types.DataType
UNKNOWN - ai.djl.ndarray.types.LayoutType
update(long, String) - Method in class ai.djl.training.util.ProgressBar
update(Shape, int, long) - Static method in class ai.djl.ndarray.types.Shape: Returns a new shape altering the given dimension.
update(HpSet, float) - Method in class ai.djl.training.hyperparameter.optimizer.BaseHpOptimizer: Updates the optimizer with the results of a hyperparameter test.
update(HpSet, float) - Method in interface ai.djl.training.hyperparameter.optimizer.HpOptimizer: Updates the optimizer with the results of a hyperparameter test.
update(String, NDArray[]) - Method in interface ai.djl.training.ParameterServer: Updates the parameter of a key from Parameter Server.
update(String, NDArray[], NDArray[]) - Method in class ai.djl.training.LocalParameterServer: Updates the parameter of a key from Parameter Server.
update(String, NDArray[], NDArray[]) - Method in interface ai.djl.training.ParameterServer: Updates the parameter of a key from Parameter Server.
update(String, NDArray, NDArray) - Method in class ai.djl.training.optimizer.Adadelta: Updates the parameters according to the gradients.
update(String, NDArray, NDArray) - Method in class ai.djl.training.optimizer.Adagrad: Updates the parameters according to the gradients.
update(String, NDArray, NDArray) - Method in class ai.djl.training.optimizer.Adam: Updates the parameters according to the gradients.
update(String, NDArray, NDArray) - Method in class ai.djl.training.optimizer.Nag: Updates the parameters according to the gradients.
update(String, NDArray, NDArray) - Method in class ai.djl.training.optimizer.Optimizer: Updates the parameters according to the gradients.
update(String, NDArray, NDArray) - Method in class ai.djl.training.optimizer.RmsProp: Updates the parameters according to the gradients.
update(String, NDArray, NDArray) - Method in class ai.djl.training.optimizer.Sgd: Updates the parameters according to the gradients.
updateAccumulator(String, NDList, NDList) - Method in class ai.djl.training.evaluator.AbstractAccuracy: Updates the evaluator with the given key based on a NDList of labels and predictions.
updateAccumulator(String, NDList, NDList) - Method in class ai.djl.training.evaluator.BoundingBoxError: Updates the evaluator with the given key based on a NDList of labels and predictions.
updateAccumulator(String, NDList, NDList) - Method in class ai.djl.training.evaluator.Evaluator: Updates the evaluator with the given key based on a NDList of labels and predictions.
updateAccumulator(String, NDList, NDList) - Method in class ai.djl.training.evaluator.IndexEvaluator: Updates the evaluator with the given key based on a NDList of labels and predictions.
updateAccumulator(String, NDList, NDList) - Method in class ai.djl.training.loss.AbstractCompositeLoss: Updates the evaluator with the given key based on a NDList of labels and predictions.
updateAccumulator(String, NDList, NDList) - Method in class ai.djl.training.loss.Loss: Updates the evaluator with the given key based on a NDList of labels and predictions.
updateAllParameters() - Method in class ai.djl.training.ParameterStore: Updates all the mirrored parameters.
updateCount(String) - Method in class ai.djl.training.optimizer.Optimizer
uri - Variable in class ai.djl.repository.AbstractRepository
UrlTranslator<T> - Class in ai.djl.modality.cv.translator.wrapper: Built-in Translator that provides image pre-processing from URL.
UrlTranslator(Translator<Image, T>) - Constructor for class ai.djl.modality.cv.translator.wrapper.UrlTranslator: Creates a UrlTranslator instance.
useDefault - Variable in class ai.djl.nn.core.Embedding.BaseBuilder

V

validate() - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder
validate() - Method in class ai.djl.modality.cv.translator.BaseImageTranslator.ClassificationBuilder
validate() - Method in class ai.djl.nn.convolutional.Convolution.ConvolutionBuilder: Validates that the required arguments are set.
validate() - Method in class ai.djl.nn.convolutional.Deconvolution.DeconvolutionBuilder: Validates that the required arguments are set.
VALIDATE_EPOCH - Static variable in class ai.djl.training.listener.EvaluatorTrainingListener
validateBatch(Trainer, Batch) - Static method in class ai.djl.training.EasyTrain: Validates the given batch of data.
validateBufferSize(Buffer, DataType, int) - Static method in class ai.djl.ndarray.BaseNDManager: Checks if the input buffer size is match expected data type.
validateLayout(LayoutType[], LayoutType[]) - Static method in interface ai.djl.nn.Block: Validates that actual layout matches the expected layout.
VALIDATION - ai.djl.training.dataset.Dataset.Usage
valueOf(String) - Static method in enum ai.djl.metric.Unit: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.modality.cv.Image.Flag: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.modality.cv.Image.Interpolation: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.modality.cv.translator.YoloV5Translator.YoloOutputType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.ndarray.types.DataType.Format: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.ndarray.types.DataType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.ndarray.types.LayoutType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.ndarray.types.SparseFormat: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.nn.Parameter.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.nn.recurrent.RNN.Activation: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.training.dataset.Dataset.Usage: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.training.initializer.XavierInitializer.FactorType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.training.initializer.XavierInitializer.RandomType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum ai.djl.training.tracker.WarmUpTracker.Mode: Returns the enum constant of this type with the specified name.
values() - Static method in enum ai.djl.metric.Unit: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.modality.cv.Image.Flag: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.modality.cv.Image.Interpolation: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.modality.cv.translator.YoloV5Translator.YoloOutputType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.ndarray.types.DataType.Format: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.ndarray.types.DataType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.ndarray.types.LayoutType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.ndarray.types.SparseFormat: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.nn.Parameter.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.nn.recurrent.RNN.Activation: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.training.dataset.Dataset.Usage: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.training.initializer.XavierInitializer.FactorType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.training.initializer.XavierInitializer.RandomType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum ai.djl.training.tracker.WarmUpTracker.Mode: Returns an array containing the constants of this enum type, in the order they are declared.
version - Variable in class ai.djl.nn.AbstractBaseBlock: The model version of this block, used for checking if parameters are still valid during parameter loading.
Version - Class in ai.djl.repository: A Version is used for the versioning of an Artifact.
Version(String) - Constructor for class ai.djl.repository.Version: Constructs a version with the version string.
VersionComparator() - Constructor for class ai.djl.repository.Artifact.VersionComparator
VersionRange - Class in ai.djl.repository: A VersionRange is a set of Restrictions that match some Versions.
vocab - Variable in class ai.djl.modality.nlp.translator.QATranslator
Vocabulary - Interface in ai.djl.modality.nlp: Vocabulary is a collection of tokens.
vocabularyContains(String) - Method in class ai.djl.modality.nlp.embedding.TrainableWordEmbedding: Returns whether an embedding exists for a word.
vocabularyContains(String) - Method in interface ai.djl.modality.nlp.embedding.WordEmbedding: Returns whether an embedding exists for a word.

W

waitAll() - Method in interface ai.djl.ndarray.LazyNDArray: Runs all NDArrays and sleeps until their values are fully computed.
waitToRead() - Method in interface ai.djl.ndarray.LazyNDArray: Runs the current NDArray and sleeps until the value is ready to read.
waitToWrite() - Method in interface ai.djl.ndarray.LazyNDArray: Runs the current NDArray and sleeps until the value is ready to write.
warmUp() - Static method in interface ai.djl.training.tracker.Tracker: Returns a new instance of WarmUpTracker.Builder that can build an WarmUpTracker.
WarmUpTracker - Class in ai.djl.training.tracker: A WarmUpTracker applies a simple warm-up before executing a main Tracker.
WarmUpTracker.Builder - Class in ai.djl.training.tracker: The Builder to construct a WarmUpTracker.
WarmUpTracker.Mode - Enum in ai.djl.training.tracker: An enum that enumerates the types of warm-up modes for a WarmUpTracker.
weight - Variable in class ai.djl.nn.convolutional.Convolution
weight - Variable in class ai.djl.nn.convolutional.Deconvolution
WEIGHT - ai.djl.nn.Parameter.Type
where(NDArray, NDArray, NDArray) - Static method in class ai.djl.ndarray.NDArrays: Returns elements chosen from the NDArray or the other NDArray depending on condition.
width - Variable in class ai.djl.modality.cv.translator.BaseImageTranslator.BaseBuilder
WIDTH - ai.djl.ndarray.types.LayoutType
withDefaultState(Map<String, Map<Device, NDArray>>, String, Device, Function<String, NDArray>) - Method in class ai.djl.training.optimizer.Optimizer
WORD_EMBEDDING - Static variable in interface ai.djl.Application.NLP: An application that takes a word and returns a feature vector that represents the word.
WORD_RECOGNITION - Static variable in interface ai.djl.Application.CV: An application that accepts an image of a single word and returns the String text of the word.
WordEmbedding - Interface in ai.djl.modality.nlp.embedding: A class to manage 1-D NDArray representations of words.
WordpieceTokenizer - Class in ai.djl.modality.nlp.bert: WordpieceTokenizer tokenizes a piece of text into its word pieces.
WordpieceTokenizer(Vocabulary, String, int) - Constructor for class ai.djl.modality.nlp.bert.WordpieceTokenizer: Creates an instance of WordpieceTokenizer.
wrap(byte[]) - Static method in interface ai.djl.ndarray.BytesSupplier: Wraps a byte array into a {code BytesSupplier}.
wrap(String) - Static method in interface ai.djl.ndarray.BytesSupplier: Wraps a string into a {code BytesSupplier}.
wrapAsJson(Object) - Static method in interface ai.djl.ndarray.BytesSupplier: Wraps an object as json into a {code BytesSupplier}.

X

XavierInitializer - Class in ai.djl.training.initializer: XavierInitializer is an Initializer that performs "Xavier" initialization for parameters.
XavierInitializer() - Constructor for class ai.djl.training.initializer.XavierInitializer: Creates a new instance of XavierInitializer.
XavierInitializer(XavierInitializer.RandomType, XavierInitializer.FactorType, float) - Constructor for class ai.djl.training.initializer.XavierInitializer: Initializes a Xavier initializer.
XavierInitializer.FactorType - Enum in ai.djl.training.initializer: Enum for different types of factor type.
XavierInitializer.RandomType - Enum in ai.djl.training.initializer: Enum for different types of random distributions.

Y

YoloTranslator - Class in ai.djl.modality.cv.translator: A translator for yolo models.
YoloTranslator(YoloTranslator.Builder) - Constructor for class ai.djl.modality.cv.translator.YoloTranslator: Constructs an ImageTranslator with the provided builder.
YoloTranslator.Builder - Class in ai.djl.modality.cv.translator: The builder for YoloTranslator.
YoloTranslatorFactory - Class in ai.djl.modality.cv.translator: An TranslatorFactory that creates a YoloTranslator instance.
YoloTranslatorFactory() - Constructor for class ai.djl.modality.cv.translator.YoloTranslatorFactory
YoloV5Translator - Class in ai.djl.modality.cv.translator: A translator for YoloV5 models.
YoloV5Translator(YoloV5Translator.Builder) - Constructor for class ai.djl.modality.cv.translator.YoloV5Translator: Constructs an ImageTranslator with the provided builder.
YoloV5Translator.Builder - Class in ai.djl.modality.cv.translator: The builder for YoloV5Translator.
YoloV5Translator.YoloOutputType - Enum in ai.djl.modality.cv.translator: A enum represents the Yolo output type.
YoloV5TranslatorFactory - Class in ai.djl.modality.cv.translator: An TranslatorFactory that creates a YoloV5Translator instance.
YoloV5TranslatorFactory() - Constructor for class ai.djl.modality.cv.translator.YoloV5TranslatorFactory

Z

zeros(Shape) - Method in interface ai.djl.ndarray.NDManager: Creates an instance of NDArray with specified Shape filled with zeros.
zeros(Shape, DataType) - Method in class ai.djl.ndarray.BaseNDManager: Creates an instance of NDArray with specified Shape filled with zeros.
zeros(Shape, DataType) - Method in interface ai.djl.ndarray.NDManager: Creates an instance of NDArray with specified Shape filled with zeros.
zeros(Shape, DataType, Device) - Method in interface ai.djl.ndarray.NDManager: Creates an instance of NDArray with specified Device, Shape, and DataType filled with zeros.
ZEROS - Static variable in interface ai.djl.training.initializer.Initializer
zerosLike() - Method in interface ai.djl.ndarray.NDArray: Returns an NDArray of zeros with the same Shape, DataType and SparseFormat as the input NDArray.
ZooModel<I,O> - Class in ai.djl.repository.zoo: A ZooModel is a Model loaded from a model zoo and includes a default Translator.
ZooModel(Model, Translator<I, O>) - Constructor for class ai.djl.repository.zoo.ZooModel: Constructs a ZooModel given the model and translator.
ZooProvider - Interface in ai.djl.repository.zoo: The ZooProvider is a service provider that enables ServiceLoader to locate and load at the run time.
ZooProviderNotFoundException - Exception in ai.djl.repository.zoo: Runtime exception thrown when a provider of the required type cannot be found.
ZooProviderNotFoundException(String) - Constructor for exception ai.djl.repository.zoo.ZooProviderNotFoundException: Constructs a new exception with the specified detail message.
ZooProviderNotFoundException(String, Throwable) - Constructor for exception ai.djl.repository.zoo.ZooProviderNotFoundException: Constructs a new exception with the specified detail message and cause.
ZooProviderNotFoundException(Throwable) - Constructor for exception ai.djl.repository.zoo.ZooProviderNotFoundException: Constructs a new exception with the specified cause and a detail message of (cause==null ? null : cause.toString()) (which typically contains the class and detail message of cause).

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