R-Index

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

R

randomDoubleBetween(double, double) - Static method in class org.deeplearning4j.util.MathUtils
randomFloatBetween(float, float) - Static method in class org.deeplearning4j.util.MathUtils
RandomizedInputTest - Class in com.atilika.kuromoji.ipadic
RandomizedInputTest() - Constructor for class com.atilika.kuromoji.ipadic.RandomizedInputTest
randomNumberBetween(double, double) - Static method in class org.deeplearning4j.util.MathUtils: Generates a random integer between the specified numbers
randomNumberBetween(double, double, RandomGenerator) - Static method in class org.deeplearning4j.util.MathUtils: Generates a random integer between the specified numbers
RandomUtils - Class in org.deeplearning4j.models.embeddings.learning.impl.elements: RandomUtils is a wrapper that supports all possible Random methods via the Math.random() method and its system-wide Random object.
RandomUtils() - Constructor for class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
RandomUtils - Class in org.deeplearning4j.util: Created by Alex on 24/01/2017.
RandomUtils() - Constructor for class org.deeplearning4j.util.RandomUtils
RandomWalker<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl: This is Random-based walker for SequenceVectors-based DeepWalk implementation Original DeepWalk paper: http://arxiv.org/pdf/1403.6652v2
RandomWalker() - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
RandomWalker.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
RandomWalkerTest - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
RandomWalkerTest() - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalkerTest
RandomWalkGraphIteratorProvider<V> - Class in org.deeplearning4j.graph.iterator.parallel: Random walk graph iterator provider: given a graph, split up the generation of random walks for parallel learning.
RandomWalkGraphIteratorProvider(IGraph<V, ?>, int) - Constructor for class org.deeplearning4j.graph.iterator.parallel.RandomWalkGraphIteratorProvider
RandomWalkGraphIteratorProvider(IGraph<V, ?>, int, long, NoEdgeHandling) - Constructor for class org.deeplearning4j.graph.iterator.parallel.RandomWalkGraphIteratorProvider
RandomWalkIterator<V> - Class in org.deeplearning4j.graph.iterator: Given a graph, iterate through random walks on that graph of a specified length.
RandomWalkIterator(IGraph<V, ?>, int) - Constructor for class org.deeplearning4j.graph.iterator.RandomWalkIterator
RandomWalkIterator(IGraph<V, ?>, int, long) - Constructor for class org.deeplearning4j.graph.iterator.RandomWalkIterator: Construct a RandomWalkIterator for a given graph, with a specified walk length and random number generator seed.
Uses NoEdgeHandling.EXCEPTION_ON_DISCONNECTED - hence exception will be thrown when generating random walks on graphs with vertices containing having no edges, or no outgoing edges (for directed graphs)
RandomWalkIterator(IGraph<V, ?>, int, long, NoEdgeHandling) - Constructor for class org.deeplearning4j.graph.iterator.RandomWalkIterator
RandomWalkIterator(IGraph<V, ?>, int, long, NoEdgeHandling, int, int) - Constructor for class org.deeplearning4j.graph.iterator.RandomWalkIterator: Constructor used to generate random walks starting at a subset of the vertices in the graph.
RawMnistDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl: Mnist data with scaled pixels
RawMnistDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.RawMnistDataSetIterator
RBM - Class in org.deeplearning4j.nn.conf.layers: Restricted Boltzmann Machine.
RBM - Static variable in class org.deeplearning4j.nn.conf.layers.setup.ConvolutionLayerSetup: Deprecated.
RBM - Class in org.deeplearning4j.nn.layers.feedforward.rbm: Restricted Boltzmann Machine.
RBM(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
RBM(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.feedforward.rbm.RBM
RBM.Builder - Class in org.deeplearning4j.nn.conf.layers
RBM.HiddenUnit - Enum in org.deeplearning4j.nn.conf.layers
RBM.VisibleUnit - Enum in org.deeplearning4j.nn.conf.layers
RBMTests - Class in org.deeplearning4j.nn.layers.feedforward.rbm: Created by agibsonccc on 8/27/14.
RBMTests() - Constructor for class org.deeplearning4j.nn.layers.feedforward.rbm.RBMTests
RBMUtil - Class in org.deeplearning4j.util: Handles various cooccurrences for RBM specific cooccurrences
RDDMiniBatches - Class in org.deeplearning4j.spark.datavec: RDD mini batch partitioning
RDDMiniBatches(int, JavaRDD<DataSet>) - Constructor for class org.deeplearning4j.spark.datavec.RDDMiniBatches
RDDMiniBatches.MiniBatchFunction - Class in org.deeplearning4j.spark.datavec
RDDTrainingApproach - Enum in org.deeplearning4j.spark.api: Approach to use when training from a JavaRDD<DataSet> or JavaRDD<MultiDataSet>.
rddTrainingApproach(RDDTrainingApproach) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder: The approach to use when training on a RDD<DataSet> or RDD<MultiDataSet>.
read(InputStream) - Method in class com.atilika.kuromoji.dict.UserDictionary
read(InputStream) - Static method in class com.atilika.kuromoji.io.ByteBufferIO
read(InputStream) - Static method in class com.atilika.kuromoji.trie.DoubleArrayTrie: Load Stored data
readArray(InputStream) - Static method in class com.atilika.kuromoji.io.IntegerArrayIO
readArray(InputStream) - Static method in class com.atilika.kuromoji.io.StringArrayIO
readArray2D(InputStream) - Static method in class com.atilika.kuromoji.io.IntegerArrayIO
readArray2D(InputStream) - Static method in class com.atilika.kuromoji.io.StringArrayIO
readAttributeAsJson(String, String...) - Method in class org.deeplearning4j.nn.modelimport.keras.Hdf5Archive: Read JSON-formatted string attribute from group path.
readCharacterDefinition(InputStream, String) - Method in class com.atilika.kuromoji.compile.CharacterDefinitionsCompiler
readCosts(InputStream) - Method in class com.atilika.kuromoji.compile.ConnectionCostsCompiler
readDataSet(String, String...) - Method in class org.deeplearning4j.nn.modelimport.keras.Hdf5Archive: Read data set as ND4J array from group path.
reader - Variable in class org.deeplearning4j.text.sentenceiterator.UimaSentenceIterator
readFloat(InputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: Read a float from a data input stream Credit to: https://github.com/NLPchina/Word2VEC_java/blob/master/src/com/ansj/vec/Word2VEC.java
readFromPath(Path) - Method in class org.deeplearning4j.keras.NDArrayHDF5Reader: Reads an HDF5 file into an NDArray.
readImage() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile: Reads the image at the current position.
readImage() - Method in class org.deeplearning4j.datasets.mnist.MnistManager: Reads the current image.
readImagesUnsafe(int) - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile: Read the specified number of images from the current position, to a byte[nImages][rows*cols] Note that MNIST data set is stored as unsigned bytes; this method returns signed bytes without conversion (i.e., same bits, but requires conversion before use)
readImageUnsafe(int) - Method in class org.deeplearning4j.datasets.mnist.MnistManager
READING - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
READING_FEATURE - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
readingFeature - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
readjustToData() - Method in class org.deeplearning4j.datasets.mnist.draw.DrawReconstruction
readLabel() - Method in class org.deeplearning4j.datasets.mnist.MnistLabelFile: Reads the integer at the current position.
readLabel() - Method in class org.deeplearning4j.datasets.mnist.MnistManager: Reads the current label.
readLabel(int) - Method in class org.deeplearning4j.datasets.mnist.MnistManager
readLabels(int) - Method in class org.deeplearning4j.datasets.mnist.MnistLabelFile: Read the specified number of labels from the current position
readNeuralNetwork(EntryPointFitParameters) - Method in class org.deeplearning4j.keras.NeuralNetworkReader
readObject(File) - Static method in class org.deeplearning4j.util.SerializationUtils
readObject(InputStream) - Static method in class org.deeplearning4j.util.SerializationUtils: Reads an object from the given input stream
readObjectFromFile(String, Class<T>, JavaSparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils: Read an object from HDFS (or local) using default Java object serialization
readObjectFromFile(String, Class<T>, SparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils: Read an object from HDFS (or local) using default Java object serialization
readOnly - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
readOnly(boolean) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
readOnly - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
readParagraphVectors(String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method restores ParagraphVectors model previously saved with writeParagraphVectors()
readParagraphVectors(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method restores ParagraphVectors model previously saved with writeParagraphVectors()
readParagraphVectors(InputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method restores ParagraphVectors model previously saved with writeParagraphVectors()
readParagraphVectorsFromText(String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: Deprecated.
readParagraphVectorsFromText(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: Deprecated.
readParagraphVectorsFromText(InputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: Deprecated.
readSequenceVectors(SequenceElementFactory<T>, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method loads previously saved SequenceVectors model from File
readSequenceVectors(SequenceElementFactory<T>, InputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method loads previously saved SequenceVectors model from InputStream
readSparseArray2D(InputStream) - Static method in class com.atilika.kuromoji.io.IntegerArrayIO
readSparseArray2D(InputStream) - Static method in class com.atilika.kuromoji.io.StringArrayIO
readStream(InputStream) - Method in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
readString(DataInputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: Read a string from a data input stream Credit to: https://github.com/NLPchina/Word2VEC_java/blob/master/src/com/ansj/vec/Word2VEC.java
readString(DataInputStream, int) - Static method in class org.deeplearning4j.util.ByteUtil
readStringFromFile(String, JavaSparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils: Read a UTF-8 format String from HDFS (or local)
readStringFromFile(String, SparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils: Read a UTF-8 format String from HDFS (or local)
readTokenInfo(InputStream) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
readUnknownDefinition(InputStream, String) - Method in class com.atilika.kuromoji.compile.UnknownDictionaryCompiler
readVocabCache(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method reads vocab cache from provided file.
readVocabCache(InputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method reads vocab cache from provided InputStream.
readWord2Vec(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: Deprecated.
readWord2VecFromText(File, File, File, File, VectorsConfiguration) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method allows you to read ParagraphVectors from externaly originated vectors and syn1.
readWord2VecModel(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method 1) Binary model, either compressed or not.
readWord2VecModel(String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method 1) Binary model, either compressed or not.
readWord2VecModel(String, boolean) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method 1) Binary model, either compressed or not.
readWord2VecModel(File, boolean) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer: This method 1) Binary model, either compressed or not.
realMin - Variable in class org.deeplearning4j.plot.BarnesHutTsne
realMin - Variable in class org.deeplearning4j.plot.Tsne.Builder
realMin - Variable in class org.deeplearning4j.plot.Tsne
rearrange() - Method in class org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter
reassignExistingModel() - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
recall(Integer) - Method in class org.deeplearning4j.eval.Evaluation: Returns the recall for a given label
recall(Integer, double) - Method in class org.deeplearning4j.eval.Evaluation: Returns the recall for a given label
recall() - Method in class org.deeplearning4j.eval.Evaluation: Recall based on guesses so far Takes into account all known classes and outputs average recall across all of them
recall(int) - Method in class org.deeplearning4j.eval.EvaluationBinary: Get the recall (tp / (tp + fn)) for the specified output
reconstruct(INDArray, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Reconstructs the input.
ReconstructionDataSetIterator - Class in org.deeplearning4j.datasets.iterator: Wraps a data applyTransformToDestination iterator setting the first (feature matrix) as the labels.
ReconstructionDataSetIterator(DataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
ReconstructionDistribution - Interface in org.deeplearning4j.nn.conf.layers.variational: The ReconstructionDistribution is used with variational autoencoders VariationalAutoencoder to specify the form of the distribution p(data|x).
reconstructionDistribution(ReconstructionDistribution) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder: The reconstruction distribution for the data given the hidden state - i.e., P(data|Z).
This should be selected carefully based on the type of data being modelled.
reconstructionDistribution - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
reconstructionError(INDArray) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder: Return the reconstruction error for this variational autoencoder.
NOTE (important): This method is used ONLY for VAEs that have a standard neural network loss function (i.e., an ILossFunction instance such as mean squared error) instead of using a probabilistic reconstruction distribution P(x|z) for the reconstructions (as presented in the VAE architecture by Kingma and Welling).
You can check if the VAE has a loss function using VariationalAutoencoder.hasLossFunction()
Consequently, the reconstruction error is a simple deterministic function (no Monte-Carlo sampling is required, unlike VariationalAutoencoder.reconstructionProbability(INDArray, int) and VariationalAutoencoder.reconstructionLogProbability(INDArray, int))
reconstructionLogProbability(INDArray, int) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder: Return the log reconstruction probability given the specified number of samples.
See VariationalAutoencoder.reconstructionLogProbability(INDArray, int) for more details
reconstructionProbability(INDArray, int) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder: Calculate the reconstruction probability, as described in An & Cho, 2015 - "Variational Autoencoder based Anomaly Detection using Reconstruction Probability" (Algorithm 4)
The authors describe it as follows: "This is essentially the probability of the data being generated from a given latent variable drawn from the approximate posterior distribution."

Specifically, for each example x in the input, calculate p(x).
Record - Class in org.deeplearning4j: Created by agibsonccc on 6/7/16.
Record() - Constructor for class org.deeplearning4j.Record
recordReader - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
RecordReaderDataSetIterator - Class in org.deeplearning4j.datasets.datavec: Record reader dataset iterator
RecordReaderDataSetIterator(RecordReader, WritableConverter, int) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader, int) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader, int, int, int) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator: Main constructor for classification.
RecordReaderDataSetIterator(RecordReader, WritableConverter, int, int, int, boolean) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader, WritableConverter, int, int, int) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader, int, int, int, int) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader, int, int, int, boolean) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator: Main constructor for multi-label regression (i.e., regression with multiple outputs)
RecordReaderDataSetIterator(RecordReader, WritableConverter, int, int, int, int, boolean) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
RecordReaderDataSetIterator(RecordReader, WritableConverter, int, int, int, int, int, boolean) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator: Main constructor
RecordReaderDataSetiteratorTest - Class in org.deeplearning4j.datasets.datavec: Created by agibsonccc on 3/6/15.
RecordReaderDataSetiteratorTest() - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetiteratorTest
RecordReaderFunction - Class in org.deeplearning4j.spark.datavec: Turn a string in to a dataset based on a record reader
RecordReaderFunction(RecordReader, int, int, WritableConverter) - Constructor for class org.deeplearning4j.spark.datavec.RecordReaderFunction
RecordReaderFunction(RecordReader, int, int) - Constructor for class org.deeplearning4j.spark.datavec.RecordReaderFunction
RecordReaderMultiDataSetIterator - Class in org.deeplearning4j.datasets.datavec: RecordReaderMultiDataSetIterator: A MultiDataSetIterator for data from one or more RecordReaders and SequenceRecordReaders
The idea: generate multiple inputs and multiple outputs from one or more Sequence/RecordReaders.
RecordReaderMultiDataSetIterator.AlignmentMode - Enum in org.deeplearning4j.datasets.datavec: When dealing with time series data of different lengths, how should we align the input/labels time series? For equal length: use EQUAL_LENGTH For sequence classification: use ALIGN_END
RecordReaderMultiDataSetIterator.Builder - Class in org.deeplearning4j.datasets.datavec
RecordReaderMultiDataSetIteratorTest - Class in org.deeplearning4j.datasets.datavec
RecordReaderMultiDataSetIteratorTest() - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIteratorTest
RecordToDataSet - Interface in org.deeplearning4j.streaming.conversion.dataset: Converts a list of records in to a dataset.
RecordToNDArray - Interface in org.deeplearning4j.streaming.conversion.ndarray: A function convert from record to ndarrays
recurrent(int) - Static method in class org.deeplearning4j.nn.conf.inputs.InputType: InputType for recurrent neural network (time series) data
RECURRENT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer: Weights for previous time step -> current time step connections
RECURRENT_WEIGHT_KEY_BACKWARDS - Static variable in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
RECURRENT_WEIGHT_KEY_FORWARDS - Static variable in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer: Weights for previous time step -> current time step connections
RecurrentLayer - Interface in org.deeplearning4j.nn.api.layers: Created by Alex on 28/08/2016.
RECURSIVE_AUTO_ENCODER - Static variable in class org.deeplearning4j.nn.conf.layers.setup.ConvolutionLayerSetup: Deprecated.
ReduceSentenceCount - Class in org.deeplearning4j.spark.text.functions
ReduceSentenceCount() - Constructor for class org.deeplearning4j.spark.text.functions.ReduceSentenceCount
ReflectionsHelper - Class in org.deeplearning4j.nn.conf: Original credit: https://gist.github.com/nonrational/287ed109bb0852f982e8
ReflectionsHelper() - Constructor for class org.deeplearning4j.nn.conf.ReflectionsHelper
ReflectionUtils - Class in org.deeplearning4j.util: General reflection utils
refreshClusterCenter(Cluster, ClusterInfo) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
refreshClustersCenters(ClusterSet, ClusterSetInfo, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
registerStatsStorageListener(StatsStorageListener) - Method in interface org.deeplearning4j.api.storage.StatsStorage: Add a new StatsStorageListener.
registerStatsStorageListener(StatsStorageListener) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
registerStatsStorageListener(StatsStorageListener) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
registerUrlTypes() - Static method in class org.deeplearning4j.nn.conf.ReflectionsHelper: OSX contains file:// resources on the classpath including .mar and .jnilib files.
regression - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
RegressionEvalTest - Class in org.deeplearning4j.eval
RegressionEvalTest() - Constructor for class org.deeplearning4j.eval.RegressionEvalTest
RegressionEvaluation - Class in org.deeplearning4j.eval: Evaluation method for the evaluation of regression algorithms.
Provides the following metrics, for each column:
- MSE: mean squared error
- MAE: mean absolute error
- RMSE: root mean squared error
- RSE: relative squared error
- correlation coefficient
See for example: http://www.saedsayad.com/model_evaluation_r.htm For classification, see Evaluation
RegressionEvaluation(int) - Constructor for class org.deeplearning4j.eval.RegressionEvaluation: Create a regression evaluation object with the specified number of columns, and default precision for the stats() method.
RegressionEvaluation(int, int) - Constructor for class org.deeplearning4j.eval.RegressionEvaluation: Create a regression evaluation object with the specified number of columns, and specified precision for the stats() method.
RegressionEvaluation(String...) - Constructor for class org.deeplearning4j.eval.RegressionEvaluation: Create a regression evaluation object with default precision for the stats() method
RegressionEvaluation(List<String>) - Constructor for class org.deeplearning4j.eval.RegressionEvaluation: Create a regression evaluation object with default precision for the stats() method
RegressionEvaluation(List<String>, int) - Constructor for class org.deeplearning4j.eval.RegressionEvaluation: Create a regression evaluation object with specified precision for the stats() method
RegressionTest050 - Class in org.deeplearning4j.regressiontest: Regression tests for DL4J 0.5.0 - i.e., can we still load basic models generated in 0.5.0? See dl4j-test-resources/src/main/resources/regression_testing/050/050_regression_test_readme.md
RegressionTest050() - Constructor for class org.deeplearning4j.regressiontest.RegressionTest050
RegressionTest060 - Class in org.deeplearning4j.regressiontest: Regression tests for DL4J 0.5.0 - i.e., can we still load basic models generated in 0.5.0? See dl4j-test-resources/src/main/resources/regression_testing/050/050_regression_test_readme.md
RegressionTest060() - Constructor for class org.deeplearning4j.regressiontest.RegressionTest060
RegressionTest071 - Class in org.deeplearning4j.regressiontest: Regression tests for DL4J 0.5.0 - i.e., can we still load basic models generated in 0.5.0? See dl4j-test-resources/src/main/resources/regression_testing/050/050_regression_test_readme.md
RegressionTest071() - Constructor for class org.deeplearning4j.regressiontest.RegressionTest071
regressionTestCGLSTM1() - Method in class org.deeplearning4j.regressiontest.RegressionTest060
regressionTestCGLSTM1() - Method in class org.deeplearning4j.regressiontest.RegressionTest071
regressionTestCNN1() - Method in class org.deeplearning4j.regressiontest.RegressionTest050
regressionTestCNN1() - Method in class org.deeplearning4j.regressiontest.RegressionTest060
regressionTestCNN1() - Method in class org.deeplearning4j.regressiontest.RegressionTest071
regressionTestLSTM1() - Method in class org.deeplearning4j.regressiontest.RegressionTest060
regressionTestLSTM1() - Method in class org.deeplearning4j.regressiontest.RegressionTest071
regressionTestMLP1() - Method in class org.deeplearning4j.regressiontest.RegressionTest050
regressionTestMLP1() - Method in class org.deeplearning4j.regressiontest.RegressionTest060
regressionTestMLP1() - Method in class org.deeplearning4j.regressiontest.RegressionTest071
regressionTestMLP2() - Method in class org.deeplearning4j.regressiontest.RegressionTest050
regressionTestMLP2() - Method in class org.deeplearning4j.regressiontest.RegressionTest060
regressionTestMLP2() - Method in class org.deeplearning4j.regressiontest.RegressionTest071
regularization(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder: Whether to use regularization (l1, l2, dropout, etc
regularization(boolean) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
REGULARIZATION_TYPE_L1 - Static variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
REGULARIZATION_TYPE_L2 - Static variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
reinitMapperWithSubtypes(Collection<NamedType>) - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration: Reinitialize and return the Jackson/json ObjectMapper with additional named types.
relativeDifferance(double, double) - Static method in class org.deeplearning4j.berkeley.SloppyMath
relativeSquaredError(int) - Method in class org.deeplearning4j.eval.RegressionEvaluation
release(CAS) - Method in class org.deeplearning4j.text.uima.UimaResource
remainingCapacity() - Method in class org.deeplearning4j.parallelism.MagicQueue
RemoteConvolutionalIterationListener - Class in org.deeplearning4j.ui.weights
RemoteConvolutionalIterationListener(int, UiConnectionInfo) - Constructor for class org.deeplearning4j.ui.weights.RemoteConvolutionalIterationListener
RemoteFlowIterationListener - Class in org.deeplearning4j.ui.flow: This IterationListener is suited for general model performance/architecture overview PLEASE NOTE: WORK IN PROGRESS, DO NOT USE IT UNLESS YOU HAVE TO
RemoteFlowIterationListener() - Constructor for class org.deeplearning4j.ui.flow.RemoteFlowIterationListener: Creates IterationListener and keeps it detached from any UiServer instances
RemoteFlowIterationListener(UiConnectionInfo, int) - Constructor for class org.deeplearning4j.ui.flow.RemoteFlowIterationListener
RemoteHistogramIterationListener - Class in org.deeplearning4j.ui.weights: A histogram iteration listener that updates the weights of the model with a web based ui.
RemoteHistogramIterationListener(UiConnectionInfo, int) - Constructor for class org.deeplearning4j.ui.weights.RemoteHistogramIterationListener
RemoteReceiverModule - Class in org.deeplearning4j.ui.module.remote: Used to receive UI updates remotely.
RemoteReceiverModule() - Constructor for class org.deeplearning4j.ui.module.remote.RemoteReceiverModule
RemoteUIStatsStorageRouter - Class in org.deeplearning4j.api.storage.impl: Asynchronously post all updates to a remote UI that has remote listening enabled.
Typically used with UIServer (don't forget to enable remote listener support - UIServer.getInstance().enableRemoteListener()
RemoteUIStatsStorageRouter(String) - Constructor for class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter: Create remote UI with defaults for all values except address
RemoteUIStatsStorageRouter(String, int, long, double) - Constructor for class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
RemoteUIStatsStorageRouter(String, String, int, long, double) - Constructor for class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
remove(Object) - Method in class com.atilika.kuromoji.trie.PatriciaTrie: Removes entry identified by key from this trie (currently unsupported)
remove() - Method in class org.deeplearning4j.aws.s3.reader.BucketIterator
remove() - Method in class org.deeplearning4j.berkeley.Iterators.FilteredIterator
remove() - Method in class org.deeplearning4j.berkeley.Iterators.IteratorIterator
remove() - Method in class org.deeplearning4j.berkeley.Iterators.Transform
remove() - Method in class org.deeplearning4j.berkeley.Iterators.TransformingIterator
remove() - Method in class org.deeplearning4j.berkeley.PriorityQueue
remove() - Method in interface org.deeplearning4j.berkeley.PriorityQueueInterface: Not supported -- next() already removes the head of the queue.
remove() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator: Removes from the underlying collection the last element returned by this iterator (optional operation).
remove() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
remove() - Method in class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Removes from the underlying collection the last element returned by this iterator (optional operation).
remove() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: Removes from the underlying collection the last element returned by this iterator (optional operation).
remove() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
remove() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
remove() - Method in class org.deeplearning4j.graph.graph.VertexSequence
remove() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
remove() - Method in class org.deeplearning4j.keras.HDF5MiniBatchDataSetIterator
remove() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.WeightIterator
remove() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.BasicTransformerIterator
remove() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator: Removes from the underlying collection the last element returned by this iterator (optional operation).
remove() - Method in class org.deeplearning4j.parallelism.AsyncIterator
remove(Object) - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
remove(Object) - Method in class org.deeplearning4j.parallelism.MagicQueue: This method isn't supported
remove() - Method in class org.deeplearning4j.parallelism.MagicQueue
remove() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
remove() - Method in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
remove() - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
remove() - Method in class org.deeplearning4j.text.corpora.treeparser.TreeIterator: Removes from the underlying collection the last element returned by this iterator (optional operation).
remove() - Method in class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
remove() - Method in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator
remove() - Method in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
remove() - Method in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
remove() - Method in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
remove() - Method in class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator
remove() - Method in class org.deeplearning4j.text.sentenceiterator.interoperability.SentenceIteratorConverter
remove() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
remove(Object) - Method in class org.deeplearning4j.util.DiskBasedQueue
remove() - Method in class org.deeplearning4j.util.DiskBasedQueue
remove(Object) - Method in class org.deeplearning4j.util.MultiDimensionalMap: Removes the mapping for a key from this map if it is present (optional operation).
remove(Object) - Method in class org.deeplearning4j.util.MultiDimensionalSet: Removes the specified element from this applyTransformToDestination if it is present (optional operation).
REMOVE_STOPWORDS - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables: Deprecated.
removeAll(Collection<?>) - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
removeAll(Collection<?>) - Method in class org.deeplearning4j.parallelism.MagicQueue: This method isn't supported
removeAll(Collection<?>) - Method in class org.deeplearning4j.util.DiskBasedQueue
removeAll(Collection<?>) - Method in class org.deeplearning4j.util.MultiDimensionalSet: Removes from this applyTransformToDestination all of its elements that are contained in the specified collection (optional operation).
removeAllListeners() - Method in interface org.deeplearning4j.api.storage.StatsStorage: Remove all listeners from the StatsStorage instance
removeAllListeners() - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
removeAllListeners() - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
removeClusterInfos(List<Cluster>) - Method in class org.deeplearning4j.clustering.cluster.info.ClusterSetInfo
removeColumns(Integer...) - Method in class org.deeplearning4j.util.StringGrid: Removes the specified columns from the grid
removeElement(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
removeElement(T) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
removeElement(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache: Deprecated.
removeElement(VocabWord) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache: Deprecated.
removeElement(String) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache: Removes element with specified label from vocabulary Please note: Huffman index should be updated after element removal
removeElement(T) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache: Removes specified element from vocabulary Please note: Huffman index should be updated after element removal
removeEmptyClusters(ClusterSetInfo) - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
removeEmptyClusters() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
removeFirst() - Method in class org.deeplearning4j.berkeley.PriorityQueue
removeHook(TrainingHook) - Method in interface org.deeplearning4j.spark.api.TrainingMaster: Remove a training hook from the worker
removeHook(TrainingHook) - Method in interface org.deeplearning4j.spark.api.TrainingWorker: Remove a training hook from the worker
removeHook(TrainingHook) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster: Remove a training hook from the worker
removeHook(TrainingHook) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker: Remove a training hook from the worker
removeKey(E) - Method in class org.deeplearning4j.berkeley.Counter
removeKey(K) - Method in class org.deeplearning4j.berkeley.CounterMap
removeKeyFromEntries(E) - Method in class org.deeplearning4j.berkeley.Counter
removeLayersFromOutput(int) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder: Remove last "n" layers of the net At least an output layer must be added back in
removeOutputLayer() - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder: Helper method to remove the outputLayer of the net.
removePair(T, T) - Method in class org.deeplearning4j.models.glove.count.CountMap
removePair(Pair<T, T>) - Method in class org.deeplearning4j.models.glove.count.CountMap
removePoint(String) - Method in class org.deeplearning4j.clustering.cluster.Cluster
removePoints() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
removePoints() - Method in class org.deeplearning4j.clustering.cluster.Cluster
removePoints() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
removeRowsWithEmptyColumn(int) - Method in class org.deeplearning4j.util.StringGrid: Removes all rows with a column of NONE
removeRowsWithEmptyColumn(int, String) - Method in class org.deeplearning4j.util.StringGrid: Removes all rows with a column of missingValue
removeVertex(String) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder: Intended for use with the transfer learning API.
removeVertex(String, boolean) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder: Intended for use with the transfer learning API.
removeVertexAndConnections(String) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder: Remove specified vertex and it's connections from the computation graph
removeVertexKeepConnections(String) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder: Remove the specified vertex from the computation graph but keep it's connections.
renderHistogram() - Method in class org.deeplearning4j.ui.TestRenders
renderHistogram2() - Method in class org.deeplearning4j.ui.TestRenders
renderHTML(Collection<Component>) - Static method in class org.deeplearning4j.ui.standalone.StaticPageUtil: Given the specified components, render them to a stand-alone HTML page (which is returned as a String)
renderHTML(Component...) - Static method in class org.deeplearning4j.ui.standalone.StaticPageUtil: Given the specified components, render them to a stand-alone HTML page (which is returned as a String)
renderHTMLContent(Component...) - Static method in class org.deeplearning4j.ui.standalone.StaticPageUtil
repartionData(Repartition) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder: Set if/when repartitioning should be conducted for the training data.
Default value: always repartition (if required to guarantee correct number of partitions and correct number of examples in each partition).
Repartition - Enum in org.deeplearning4j.spark.api: Enumeration that is used for specifying the behaviour of repartitioning in ParameterAveragingTrainingMaster (and possibly elsewhere.
repartition(JavaRDD<T>, Repartition, RepartitionStrategy, int, int) - Static method in class org.deeplearning4j.spark.util.SparkUtils: Repartition the specified RDD (or not) using the given Repartition and RepartitionStrategy settings
repartitionBalanceIfRequired(JavaRDD<T>, Repartition, int, int) - Static method in class org.deeplearning4j.spark.util.SparkUtils: Repartition a RDD (given the Repartition setting) such that we have approximately numPartitions partitions, each of which has objectsPerPartition objects.
RepartitionStrategy - Enum in org.deeplearning4j.spark.api: RepartitionStrategy: different strategies for conducting repartitioning on training data, when repartitioning is required.
SparkDefault: repartition using Spark's standard RDD.repartition(int) method.
repartitionStrategy(RepartitionStrategy) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder: Used in conjunction with ParameterAveragingTrainingMaster.Builder.repartionData(Repartition) (which defines when repartitioning should be conducted), repartitionStrategy defines how the repartitioning should be done.
replicatedModel(Model) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer.ParameterServerTrainerBuilder
replicatedModel - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
reportBatch(boolean) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder: This method defines, if batches/sec should be reported together with other data
reportDataSetMetaData(List<Serializable>, Class<?>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report any metadata for the DataSet
reportDataSetMetaData(List<Serializable>, String) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report any metadata for the DataSet
reportDataSetMetaData(List<Serializable>, Class<?>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportDataSetMetaData(List<Serializable>, String) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportDataSetMetaData(List<Serializable>, Class<?>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportDataSetMetaData(List<Serializable>, String) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportGarbageCollection(String, int, int) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report Garbage collection stats
reportGarbageCollection(String, int, int) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportGarbageCollection(String, int, int) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportHardwareInfo(int, int, long, long, long[], String[], String) - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
reportHardwareInfo(int, int, long, long, long[], String[], String) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
reportHardwareInfo(int, int, long, long, long[], String[], String) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
reportHistograms(StatsType, Map<String, Histogram>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report histograms for all parameters, for a given StatsType
reportHistograms(StatsType, Map<String, Histogram>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportHistograms(StatsType, Map<String, Histogram>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportIDs(String, String, String, long) - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
reportIDs(String, String, String, long) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
reportIDs(String, String, String, long) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
reportIDs(String, String, String, long) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportIDs(String, String, String, long) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
reportIDs(String, String, String, long) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportingFrequency() - Method in interface org.deeplearning4j.ui.stats.api.StatsUpdateConfiguration: Get the reporting frequency, in terms of listener calls
reportingFrequency(int) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
reportingFrequency() - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
reportIteration(boolean) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder: This method defines, if iteration number should be reported together with other data
reportIterationCount(int) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report the current iteration number
reportIterationCount(int) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportIterationCount(int) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportLearningRates(Map<String, Double>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report the learning rates by parameter
reportLearningRates(Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportLearningRates(Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportMean(StatsType, Map<String, Double>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report the mean values for each parameter, the given StatsType (Parameters/Updates/Activations)
reportMean(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportMean(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportMeanMagnitudes(StatsType, Map<String, Double>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report the mean magnitude values for each parameter for the given StatsType (Parameters/Updates/Activations)
reportMeanMagnitudes(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportMeanMagnitudes(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportMemoryUse(long, long, long, long, long[], long[]) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report the memory stats at this iteration
reportMemoryUse(long, long, long, long, long[], long[]) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportMemoryUse(long, long, long, long, long[], long[]) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportModelInfo(String, String, String[], int, long) - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport: Report the model information
reportModelInfo(String, String, String[], int, long) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
reportModelInfo(String, String, String[], int, long) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
reportPerformance(long, long, long, double, double) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report the performance stats (since the last report)
reportPerformance(long, long, long, double, double) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportPerformance(long, long, long, double, double) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportSample(boolean) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder: This method defines, if samples/sec should be reported together with other data
reportScore(boolean) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder: This method defines, if score should be reported together with other data
reportScore - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
reportScore - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
reportScore(double) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report model score at the current iteration
reportScore(double) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportScore(double) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportScoreAfterAveraging(boolean) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: This method enables/disables averaged model score reporting
reportSoftwareInfo(String, String, String, String, String, String, String, String, String, Map<String, String>) - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
reportSoftwareInfo(String, String, String, String, String, String, String, String, String, Map<String, String>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
reportSoftwareInfo(String, String, String, String, String, String, String, String, String, Map<String, String>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
reportStatsCollectionDurationMS(int) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report the number of milliseconds required to calculate all of the stats.
reportStatsCollectionDurationMS(int) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportStatsCollectionDurationMS(int) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportStdev(StatsType, Map<String, Double>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport: Report the standard deviation values for each parameter for the given StatsType (Parameters/Updates/Activations)
reportStdev(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
reportStdev(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
reportStorageEvents(Collection<StatsStorageEvent>) - Method in interface org.deeplearning4j.ui.api.UIModule: Whenever the UIServer receives some StatsStorageEvents from one of the registered StatsStorage instances, it will filter these and pass on to the UI module those ones that match one of the Type IDs from UIModule.getCallbackTypeIDs().
Typically, these will be batched together at least somewhat, rather than being reported individually.
reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.convolutional.ConvolutionalListenerModule
reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.defaultModule.DefaultModule
reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.flow.FlowListenerModule
reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.histogram.HistogramModule
reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.remote.RemoteReceiverModule
reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.train.TrainModule
reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.tsne.TsneModule
reportTime(boolean) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder: This method defines, if time per iteration should be reported together with other data
reset() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.fetchers.BaseDataFetcher
reset() - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
reset() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator: Resets the iterator back to the beginning
reset() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
reset() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher: Deprecated.

Returns the fetcher back to the beginning of the dataset
reset() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
reset() - Method in class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator: Resets the iterator back to the beginning
reset() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator: Resets the iterator back to the beginning
reset() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
reset() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
reset() - Method in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
reset() - Method in interface org.deeplearning4j.graph.iterator.GraphWalkIterator: Reset the graph walk iterator.
reset() - Method in class org.deeplearning4j.graph.iterator.RandomWalkIterator
reset() - Method in class org.deeplearning4j.graph.iterator.WeightedRandomWalkIterator
reset() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
reset() - Method in interface org.deeplearning4j.iterator.LabeledSentenceProvider: Reset the iterator - including shuffling the order, if necessary/appropriate
reset() - Method in class org.deeplearning4j.iterator.provider.CollectionLabeledSentenceProvider
reset() - Method in class org.deeplearning4j.iterator.provider.FileLabeledSentenceProvider
reset() - Method in class org.deeplearning4j.iterator.provider.LabelAwareConverter
reset() - Method in class org.deeplearning4j.keras.HDF5MiniBatchDataSetIterator
reset(boolean) - Method in interface org.deeplearning4j.models.sequencevectors.graph.walkers.GraphWalker: This method resets walker
reset(boolean) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
reset(boolean) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker
reset(boolean) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker: This method resets walker
reset(boolean) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker: This method resets walker
reset() - Method in interface org.deeplearning4j.models.sequencevectors.interfaces.SequenceIterator
reset() - Method in class org.deeplearning4j.models.sequencevectors.iterators.AbstractSequenceIterator: Resets iterator to first position
reset() - Method in class org.deeplearning4j.models.sequencevectors.iterators.FilteredSequenceIterator: Resets iterator down to first sequence
reset() - Method in class org.deeplearning4j.models.sequencevectors.iterators.SynchronizedSequenceIterator: This method resets underlying iterator
reset() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.BasicTransformerIterator
reset() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.ParallelTransformerIterator
reset() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
reset() - Method in interface org.deeplearning4j.models.sequencevectors.transformers.SequenceTransformer
reset() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
reset() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
reset() - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
reset() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
reset() - Method in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
reset() - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
reset() - Method in class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
reset() - Method in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator: This methods resets LabelAwareIterator
reset() - Method in interface org.deeplearning4j.text.documentiterator.DocumentIterator: Reset the iterator to the beginning
reset() - Method in class org.deeplearning4j.text.documentiterator.FileDocumentIterator
reset() - Method in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
reset() - Method in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
reset() - Method in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
reset() - Method in interface org.deeplearning4j.text.documentiterator.LabelAwareIterator
reset() - Method in class org.deeplearning4j.text.documentiterator.LabelsSource: This method should be called from Iterator's reset() method, to keep labels in sync with iterator
reset() - Method in class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator: This methods resets LabelAwareIterator by creating new Iterator from Iterable internally
reset() - Method in class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator
reset() - Method in class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
reset() - Method in class org.deeplearning4j.text.sentenceiterator.BasicResultSetIterator
reset() - Method in class org.deeplearning4j.text.sentenceiterator.CollectionSentenceIterator
reset() - Method in class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
reset() - Method in class org.deeplearning4j.text.sentenceiterator.interoperability.SentenceIteratorConverter
reset() - Method in class org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareListSentenceIterator: Resets the iterator to the beginning
reset() - Method in class org.deeplearning4j.text.sentenceiterator.LineSentenceIterator
reset() - Method in class org.deeplearning4j.text.sentenceiterator.MutipleEpochsSentenceIterator
reset() - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator: Deprecated.
reset() - Method in interface org.deeplearning4j.text.sentenceiterator.SentenceIterator: Resets the iterator to the beginning
reset() - Method in class org.deeplearning4j.text.sentenceiterator.StreamLineIterator
reset() - Method in class org.deeplearning4j.text.sentenceiterator.SynchronizedSentenceIterator
reset() - Method in class org.deeplearning4j.text.sentenceiterator.UimaSentenceIterator
resetLayerDefaultConfig() - Method in class org.deeplearning4j.nn.conf.layers.Layer: Reset the learning related configs of the layer to default.
resetModel - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
resetModel(boolean) - Method in class org.deeplearning4j.models.glove.Glove.Builder
resetModel(boolean) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder: Deprecated.
resetModel(boolean) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder: This method defines whether model should be totally wiped out prior building, or not
resetModel - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
resetModel(boolean) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder: This method defines, should all model be reset before training.
resetModel(boolean) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder: This method defines whether model should be totally wiped out prior building, or not
resetSupported() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
resetSupported() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
resetSupported() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
resetSupported() - Method in class org.deeplearning4j.keras.HDF5MiniBatchDataSetIterator
resetSupported() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
resetSupported() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
resetSupported() - Method in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
resetSupported() - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
resetWeights() - Method in interface org.deeplearning4j.graph.models.embeddings.GraphVectorLookupTable: Reset (randomize) the weights.
resetWeights() - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
resetWeights(boolean) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
resetWeights() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable: Reset the weights of the cache
resetWeights(boolean) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable: Clear out all weights regardless
resetWeights() - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable: Reset the weights of the cache
resetWeights(boolean) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable: Deprecated.
resetWeights() - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable: Deprecated.

Reset the weights of the cache
resetWordCounters() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder: This methods reset counters for all words in vocabulary
reshape2dTo3d(INDArray, int) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
reshape3dTo2d(INDArray) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
reshapePerOutputTimeSeriesMaskTo2d(INDArray) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
reshapeTimeSeriesMaskToVector(INDArray) - Static method in class org.deeplearning4j.util.TimeSeriesUtils: Reshape time series mask arrays.
reshapeTimeSeriesTo2d(INDArray) - Static method in class org.deeplearning4j.eval.EvaluationUtils
reshapeVectorToTimeSeriesMask(INDArray, int) - Static method in class org.deeplearning4j.util.TimeSeriesUtils: Reshape time series mask arrays.
reshapeWeights(int[], INDArray) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil: Reshape the parameters view, without modifying the paramsView array values.
reshapeWeights(int[], INDArray, char) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil: Reshape the parameters view, without modifying the paramsView array values.
resolve(String) - Method in class com.atilika.kuromoji.util.FileResourceResolver
resolve(String) - Method in interface com.atilika.kuromoji.util.ResourceResolver: Resolve the resource name and return an open input stream to it.
resolve(String) - Method in class com.atilika.kuromoji.util.SimpleResourceResolver
resolver - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
ResourceResolver - Interface in com.atilika.kuromoji.util: An adapter to resolve the required resources into data streams.
restoreComputationGraph(String) - Static method in class org.deeplearning4j.util.ModelSerializer: Load a computation graph from a file
restoreComputationGraph(String, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer: Load a computation graph from a file
restoreComputationGraph(InputStream, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer: Load a computation graph from a InputStream
restoreComputationGraph(InputStream) - Static method in class org.deeplearning4j.util.ModelSerializer: Load a computation graph from a InputStream
restoreComputationGraph(File) - Static method in class org.deeplearning4j.util.ModelSerializer: Load a computation graph from a file
restoreComputationGraph(File, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer: Load a computation graph from a file
restoreMultiLayerNetwork(File) - Static method in class org.deeplearning4j.util.ModelSerializer: Load a multi layer network from a file
restoreMultiLayerNetwork(File, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer: Load a multi layer network from a file
restoreMultiLayerNetwork(InputStream, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer: Load a MultiLayerNetwork from InputStream from a file
restoreMultiLayerNetwork(InputStream) - Static method in class org.deeplearning4j.util.ModelSerializer
restoreMultiLayerNetwork(String) - Static method in class org.deeplearning4j.util.ModelSerializer: Load a MultilayerNetwork model from a file
restoreMultiLayerNetwork(String, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer: Load a MultilayerNetwork model from a file
restoreNormalizerFromFile(File) - Static method in class org.deeplearning4j.util.ModelSerializer: This method restores normalizer from a given persisted model file PLEASE NOTE: File should be model file saved earlier with ModelSerializer with addNormalizerToModel being called
retainAll(Collection<?>) - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
retainAll(Collection<?>) - Method in class org.deeplearning4j.parallelism.MagicQueue: This method isn't supported
retainAll(Collection<?>) - Method in class org.deeplearning4j.util.DiskBasedQueue
retainAll(Collection<?>) - Method in class org.deeplearning4j.util.MultiDimensionalSet: Retains only the elements in this applyTransformToDestination that are contained in the specified collection (optional operation).
retentionDelay - Variable in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache.Builder
retrieve() - Method in class org.deeplearning4j.text.uima.UimaResource
reverse() - Method in class org.deeplearning4j.berkeley.Pair
reverse() - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
ReverseFirstComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.ReverseFirstComparator
ReverseSecondComparator() - Constructor for class org.deeplearning4j.berkeley.Pair.ReverseSecondComparator
rewind() - Method in class org.deeplearning4j.spark.models.sequencevectors.utils.NetworkOrganizer.VirtualNode
rho(double) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder: Ada delta coefficient, rho.
rho - Variable in class org.deeplearning4j.nn.conf.layers.Layer.Builder
rho(double) - Method in class org.deeplearning4j.nn.conf.layers.Layer.Builder: Ada delta coefficient, rho.
rho - Variable in class org.deeplearning4j.nn.conf.layers.Layer
rho - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
rho(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder: Ada delta coefficient
rho - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
RIGHT_ID - Static variable in class com.atilika.kuromoji.dict.DictionaryField
rightChild(int) - Method in class org.deeplearning4j.berkeley.PriorityQueue
rightId - Variable in class com.atilika.kuromoji.dict.DictionaryEntryBase
rightId(short) - Method in class com.atilika.kuromoji.dict.GenericDictionaryEntry.Builder
rmsDecay(double) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder: Decay rate for RMSProp.
rmsDecay - Variable in class org.deeplearning4j.nn.conf.layers.Layer.Builder
rmsDecay(double) - Method in class org.deeplearning4j.nn.conf.layers.Layer.Builder: Decay rate for RMSProp.
rmsDecay - Variable in class org.deeplearning4j.nn.conf.layers.Layer
rmsDecay - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
rmsDecay(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder: Decay rate for RMSProp.
rmsDecay - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
rng - Variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
rng - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
rng - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
rng - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
rngSeed(long) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder: Random number generator seed, used mainly for enforcing repeatable splitting on RDDs Default: no seed set (i.e., random seed)
RNN_OUTPUT_LAYER - Static variable in class org.deeplearning4j.nn.conf.layers.setup.ConvolutionLayerSetup: Deprecated.
rnnActivateUsingStoredState(INDArray, boolean, boolean) - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer: Similar to rnnTimeStep, this method is used for activations using the state stored in the stateMap as the initialization.
rnnActivateUsingStoredState(INDArray[], boolean, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Similar to rnnTimeStep and feedForward() methods.
rnnActivateUsingStoredState(INDArray, boolean, boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
rnnActivateUsingStoredState(INDArray, boolean, boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
rnnActivateUsingStoredState(INDArray, boolean, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Similar to rnnTimeStep and feedForward() methods.
rnnClearPreviousState() - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer: Reset/clear the stateMap for rnnTimeStep() and tBpttStateMap for rnnActivateUsingStoredState()
rnnClearPreviousState() - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Clear the previous state of the RNN layers (if any), used in ComputationGraph.rnnTimeStep(INDArray...)
rnnClearPreviousState() - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer: Reset/clear the stateMap for rnnTimeStep() and tBpttStateMap for rnnActivateUsingStoredState()
rnnClearPreviousState() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Clear the previous state of the RNN layers (if any).
rnnGetPreviousState() - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer: Returns a shallow copy of the RNN stateMap (that contains the stored history for use in methods such as rnnTimeStep
rnnGetPreviousState(int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Get the state of the RNN layer, as used in ComputationGraph.rnnTimeStep(INDArray...).
rnnGetPreviousState(String) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Get the state of the RNN layer, as used in ComputationGraph.rnnTimeStep(INDArray...).
rnnGetPreviousState() - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer: Returns a shallow copy of the stateMap
rnnGetPreviousState(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Get the state of the RNN layer, as used in rnnTimeStep().
rnnGetPreviousStates() - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Get a map of states for ALL RNN layers, as used in ComputationGraph.rnnTimeStep(INDArray...).
rnnGetTBPTTState() - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer: Get the RNN truncated backpropagations through time (TBPTT) state for the recurrent layer.
rnnGetTBPTTState() - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
RnnOutputLayer - Class in org.deeplearning4j.nn.conf.layers
RnnOutputLayer - Class in org.deeplearning4j.nn.layers.recurrent: Recurrent Neural Network Output Layer.
Handles calculation of gradients etc for various objective functions.
Functionally the same as OutputLayer, but handles output and label reshaping automatically.
Input and output activations are same as other RNN layers: 3 dimensions with shape [miniBatchSize,nIn,timeSeriesLength] and [miniBatchSize,nOut,timeSeriesLength] respectively.
RnnOutputLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
RnnOutputLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
RnnOutputLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
rnnSetPreviousState(Map<String, INDArray>) - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer: Set the stateMap (stored history).
rnnSetPreviousState(int, Map<String, INDArray>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Set the state of the RNN layer, for use in ComputationGraph.rnnTimeStep(INDArray...)
rnnSetPreviousState(String, Map<String, INDArray>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Set the state of the RNN layer, for use in ComputationGraph.rnnTimeStep(INDArray...)
rnnSetPreviousState(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer: Set the state map.
rnnSetPreviousState(int, Map<String, INDArray>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: Set the state of the RNN layer.
rnnSetPreviousStates(Map<String, Map<String, INDArray>>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Set the states for all RNN layers, for use in ComputationGraph.rnnTimeStep(INDArray...)
rnnSetTBPTTState(Map<String, INDArray>) - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer: Set the RNN truncated backpropagations through time (TBPTT) state for the recurrent layer.
rnnSetTBPTTState(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
rnnTimeStep(INDArray) - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer: Do one or more time steps using the previous time step state stored in stateMap.
Can be used to efficiently do forward pass one or n-steps at a time (instead of doing forward pass always from t=0)
If stateMap is empty, default initialization (usually zeros) is used
Implementations also update stateMap at the end of this method
rnnTimeStep(INDArray...) - Method in class org.deeplearning4j.nn.graph.ComputationGraph: If this ComputationGraph contains one or more RNN layers: conduct forward pass (prediction) but using previous stored state for any RNN layers.
rnnTimeStep(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
rnnTimeStep(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
rnnTimeStep(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork: If this MultiLayerNetwork contains one or more RNN layers: conduct forward pass (prediction) but using previous stored state for any RNN layers.
RnnToCnnPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: A preprocessor to allow RNN and CNN layers to be used together
For example, time series (video) input -> ConvolutionLayer, or conceivable GravesLSTM -> ConvolutionLayer
Functionally equivalent to combining RnnToFeedForwardPreProcessor + FeedForwardToCnnPreProcessor
Specifically, this does two things:
(a) Reshape 3d activations out of RNN layer, with shape [miniBatchSize, numChannels*inputHeight*inputWidth, timeSeriesLength]) into 4d (CNN) activations (with shape [numExamples*timeSeriesLength, numChannels, inputWidth, inputHeight])
(b) Reshapes 4d epsilons (weights.*deltas) out of CNN layer (with shape [numExamples*timeSeriesLength, numChannels, inputHeight, inputWidth]) into 3d epsilons with shape [miniBatchSize, numChannels*inputHeight*inputWidth, timeSeriesLength] suitable to feed into CNN layers.
RnnToCnnPreProcessor(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.RnnToCnnPreProcessor
RnnToFeedForwardPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor: A preprocessor to allow RNN and feed-forward network layers to be used together.
For example, GravesLSTM -> OutputLayer or GravesLSTM -> DenseLayer
This does two things:
(a) Reshapes activations out of RNN layer (which is 3D with shape [miniBatchSize,layerSize,timeSeriesLength]) into 2d activations (with shape [miniBatchSize*timeSeriesLength,layerSize]) suitable for use in feed-forward layers.
(b) Reshapes 2d epsilons (weights*deltas from feed forward layer, with shape [miniBatchSize*timeSeriesLength,layerSize]) into 3d epsilons (with shape [miniBatchSize,layerSize,timeSeriesLength]) for use in RNN layer
RnnToFeedForwardPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
rnnUpdateStateWithTBPTTState() - Method in class org.deeplearning4j.nn.graph.ComputationGraph: Update the internal state of RNN layers after a truncated BPTT fit call
ROC - Class in org.deeplearning4j.eval: ROC (Receiver Operating Characteristic) for binary classifiers, using the specified number of threshold steps.
ROC(int) - Constructor for class org.deeplearning4j.eval.ROC
ROC.CountsForThreshold - Class in org.deeplearning4j.eval
ROC.PrecisionRecallPoint - Class in org.deeplearning4j.eval
ROC.ROCValue - Class in org.deeplearning4j.eval
ROCBinary - Class in org.deeplearning4j.eval: ROC (Receiver Operating Characteristic) for multi-task binary classifiers, using the specified number of threshold steps.
ROCBinary(int) - Constructor for class org.deeplearning4j.eval.ROCBinary
ROCBinary.CountsForThreshold - Class in org.deeplearning4j.eval
ROCBinary.PrecisionRecallPoint - Class in org.deeplearning4j.eval
ROCBinary.ROCValue - Class in org.deeplearning4j.eval
ROCBinaryTest - Class in org.deeplearning4j.eval: Created by Alex on 21/03/2017.
ROCBinaryTest() - Constructor for class org.deeplearning4j.eval.ROCBinaryTest
rocChartToHtml(ROC) - Static method in class org.deeplearning4j.evaluation.EvaluationTools: Given a ROC instance, render the ROC chart and precision vs.
rocChartToHtml(ROCMultiClass) - Static method in class org.deeplearning4j.evaluation.EvaluationTools: Given a ROCMultiClass instance, render the ROC chart and precision vs.
rocChartToHtml(ROCMultiClass, List<String>) - Static method in class org.deeplearning4j.evaluation.EvaluationTools: Given a ROCMultiClass instance and (optionally) names for each class, render the ROC chart to a stand-alone HTML file (returned as a String)
RocEvalSanityCheck() - Method in class org.deeplearning4j.eval.ROCTest
ROCMultiClass - Class in org.deeplearning4j.eval: ROC (Receiver Operating Characteristic) for multi-class classifiers, using the specified number of threshold steps.
ROCMultiClass(int) - Constructor for class org.deeplearning4j.eval.ROCMultiClass
ROCTest - Class in org.deeplearning4j.eval: Created by Alex on 04/11/2016.
ROCTest() - Constructor for class org.deeplearning4j.eval.ROCTest
ROCValue() - Constructor for class org.deeplearning4j.eval.ROC.ROCValue
ROCValue() - Constructor for class org.deeplearning4j.eval.ROCBinary.ROCValue
root - Variable in class com.atilika.kuromoji.trie.PatriciaTrie: Root value is left -- right is unused
rootMeanSquaredError(int) - Method in class org.deeplearning4j.eval.RegressionEvaluation
rootMeansSquaredError(double[], double[]) - Static method in class org.deeplearning4j.util.MathUtils: This returns the root mean squared error of two data sets
round(double) - Static method in class org.deeplearning4j.util.MathUtils: Rounds a double to the next nearest integer value.
RoundCount - Class in org.deeplearning4j.models.glove.count: Simple circular counter, that circulates within 0...Limit, both inclusive
RoundCount(int) - Constructor for class org.deeplearning4j.models.glove.count.RoundCount: Creates new RoundCount instance.
RoundCount(int, int) - Constructor for class org.deeplearning4j.models.glove.count.RoundCount: Creates new RoundCount instance.
RoundCountTest - Class in org.deeplearning4j.models.glove.count: Created by fartovii on 23.12.15.
RoundCountTest() - Constructor for class org.deeplearning4j.models.glove.count.RoundCountTest
roundDouble(double, int) - Static method in class org.deeplearning4j.util.MathUtils: Rounds a double to the given number of decimal places.
roundFloat(float, int) - Static method in class org.deeplearning4j.util.MathUtils: Rounds a double to the given number of decimal places.
Route - Class in org.deeplearning4j.ui.api: A Route specifies an endpoint that can be queried in the UI - along with how it should be handled
Route(String, HttpMethod, FunctionType, Supplier<Result>) - Constructor for class org.deeplearning4j.ui.api.Route
Route(String, HttpMethod, FunctionType, Function<String, Result>) - Constructor for class org.deeplearning4j.ui.api.Route
Route(String, HttpMethod, FunctionType, BiFunction<String, String, Result>) - Constructor for class org.deeplearning4j.ui.api.Route
RoutingIterationListener - Interface in org.deeplearning4j.api.storage.listener: An extension of the IterationListener interface for those listeners that pass data off to a StatsStorageRouter instance.
rowSums - Variable in class org.deeplearning4j.spark.BaseSparkTest
run() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.AsyncSequencer
run() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.VocabRunnable
run() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
runCifar(boolean) - Method in class org.deeplearning4j.datasets.iterator.DataSetIteratorTest
runMain(String...) - Method in class org.deeplearning4j.parallelism.main.ParallelWrapperMain
runMain(String[]) - Method in class org.deeplearning4j.ui.play.PlayUIServer
running(AtomicInteger) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer.ParameterServerTrainerBuilder
running - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
runPairWise(List<V>, CounterMap.CountFunction<V>) - Static method in class org.deeplearning4j.berkeley.CounterMap: Build a counter map by iterating pairwise over the list.
runParallelWrapperMain() - Method in class org.deeplearning4j.parallelism.main.ParallelWrapperMainTest
runRemoteCommand(String) - Method in class org.deeplearning4j.aws.ec2.provision.HostProvisioner

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