| org.deeplearning4j.nn.multilayer.MultiLayerNetwork.activate(INDArray)
|
| org.deeplearning4j.nn.conf.layers.ActivationLayer.Builder.activation(String)
|
| org.deeplearning4j.arbiter.MultiLayerSpace.Builder.addLayer(LayerSpace<? extends Layer>, ParameterSpace<Integer>, boolean) |
| org.nd4j.linalg.api.buffer.BaseDataBuffer.addReferencing(String) |
| org.deeplearning4j.eval.RegressionEvaluation.averagecorrelationR2()
|
| org.nd4j.linalg.factory.BlasWrapper.axpy(double, INDArray, INDArray) |
| org.nd4j.linalg.factory.BlasWrapper.axpy(float, INDArray, INDArray) |
| org.nd4j.linalg.api.ndarray.BaseNDArray.cleanup() |
| org.tensorflow.framework.GraphDef.Builder.clearVersion() |
| org.nd4j.jita.handler.impl.CudaZeroHandler.copyback(AllocationPoint, AllocationShape) |
| org.nd4j.jita.handler.impl.CudaZeroHandler.copyforward(AllocationPoint, AllocationShape) |
| org.nd4j.linalg.api.shape.Shape.cOrFortranOrder(int[], int[], int) |
| org.deeplearning4j.eval.RegressionEvaluation.correlationR2(int)
|
| org.deeplearning4j.arbiter.optimize.api.TaskCreator.create(Candidate, DataProvider, ScoreFunction, List<StatusListener>, IOptimizationRunner) |
| org.nd4j.linalg.api.rng.distribution.Distribution.cumulativeProbability(double, double)
|
| org.nd4j.linalg.api.rng.distribution.impl.ConstantDistribution.cumulativeProbability(double, double)
|
| org.nd4j.linalg.api.rng.distribution.impl.LogNormalDistribution.cumulativeProbability(double, double)
|
| org.nd4j.linalg.api.rng.distribution.impl.TruncatedNormalDistribution.cumulativeProbability(double, double)
|
| org.nd4j.linalg.api.rng.distribution.impl.OrthogonalDistribution.cumulativeProbability(double, double)
|
| org.nd4j.linalg.api.rng.distribution.impl.NormalDistribution.cumulativeProbability(double, double)
|
| org.deeplearning4j.arbiter.optimize.config.OptimizationConfiguration.Builder.dataProvider(DataProvider)
|
| org.nd4j.linalg.dataset.api.DataSet.dataSetBatches(int)
|
| org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder.debugLongerIterations(long) |
| org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler.decodeUpdates(INDArray) |
| org.nd4j.linalg.jcublas.context.CudaContext.destroy() |
| org.nd4j.linalg.jcublas.context.CudaContext.destroy(CublasPointer, boolean) |
| org.nd4j.linalg.api.buffer.BaseDataBuffer.dirty() |
| org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.doIterationPDS(SparkDl4jMultiLayer, SparkComputationGraph, JavaRDD<PortableDataStream>, int, int) |
| org.nd4j.linalg.api.ndarray.INDArray.elementStride()
|
| org.deeplearning4j.parallelism.trainer.SymmetricTrainer.enqueueGradient(SharedGradient) |
| org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner.execute(Candidate, DataProvider, ScoreFunction) |
| org.deeplearning4j.arbiter.optimize.runner.BaseOptimizationRunner.execute(List<Candidate>, DataProvider, ScoreFunction) |
| org.nd4j.jita.handler.impl.CudaZeroHandler.fallback(AllocationPoint, AllocationShape) |
| org.deeplearning4j.nn.api.Model.fit() |
| org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.fit() |
| org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.fit() |
| org.deeplearning4j.plot.BarnesHutTsne.fit(INDArray, int)
|
| org.deeplearning4j.spark.impl.graph.SparkComputationGraph.fit(String, int)
|
| org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer.fit(String, int)
|
| org.deeplearning4j.spark.impl.graph.SparkComputationGraph.fitMultiDataSet(String, int)
|
| org.nd4j.linalg.io.ClassUtils.forName(String) |
| org.deeplearning4j.spark.util.MLLibUtil.fromContinuousLabeledPoint(JavaSparkContext, JavaRDD<LabeledPoint>)
|
| org.deeplearning4j.spark.util.MLLibUtil.fromDataSet(JavaSparkContext, JavaRDD<DataSet>)
|
| org.deeplearning4j.spark.util.MLLibUtil.fromLabeledPoint(JavaSparkContext, JavaRDD<LabeledPoint>, long)
|
| org.nd4j.linalg.factory.BlasWrapper.gemm(double, INDArray, INDArray, double, INDArray) |
| org.nd4j.linalg.factory.BlasWrapper.gemm(float, INDArray, INDArray, float, INDArray) |
| org.nd4j.linalg.factory.BlasWrapper.gemv(double, INDArray, INDArray, double, INDArray) |
| org.nd4j.linalg.factory.BlasWrapper.gemv(float, INDArray, INDArray, float, INDArray) |
| org.nd4j.linalg.factory.BlasWrapper.ger(double, INDArray, INDArray, INDArray) |
| org.tensorflow.framework.FunctionDefOrBuilder.getAttr() |
| org.tensorflow.framework.FunctionDef.getAttr() |
| org.tensorflow.framework.FunctionDef.Builder.getAttr() |
| org.tensorflow.framework.NameAttrList.getAttr() |
| org.tensorflow.framework.NameAttrList.Builder.getAttr() |
| org.tensorflow.framework.NodeDefOrBuilder.getAttr() |
| org.tensorflow.framework.NodeDef.getAttr() |
| org.tensorflow.framework.NodeDef.Builder.getAttr() |
| org.tensorflow.framework.NameAttrListOrBuilder.getAttr() |
| com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase.getBufferEntries() |
| org.nd4j.linalg.dataset.DataSet.getColumnNames() |
| org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional.getDepth() |
| com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase.getDictionaryEntries() |
| org.deeplearning4j.models.sequencevectors.sequence.SequenceElement.getGradient(int, double, double) |
| org.deeplearning4j.models.sequencevectors.sequence.SequenceElement.getHistoricalGradient() |
| org.nd4j.linalg.jcublas.buffer.JCudaBuffer.getHostBuffer() |
| org.nd4j.linalg.jcublas.buffer.JCudaBuffer.getHostPointer() |
| org.nd4j.linalg.jcublas.buffer.BaseCudaDataBuffer.getHostPointer(INDArray, int, long, int) |
| org.nd4j.linalg.jcublas.buffer.JCudaBuffer.getHostPointer(long) |
| org.deeplearning4j.text.documentiterator.LabelledDocument.getLabel() |
| org.nd4j.linalg.dataset.DataSet.getLabelNames() |
| org.nd4j.linalg.dataset.api.DataSet.getLabelNames() |
| org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.getLr() |
| org.tensorflow.framework.FunctionDef.Builder.getMutableAttr() |
| org.tensorflow.framework.NameAttrList.Builder.getMutableAttr() |
| org.tensorflow.framework.NodeDef.Builder.getMutableAttr() |
| org.tensorflow.framework.FunctionDef.Builder.getMutableRet() |
| org.nd4j.jita.allocator.impl.AtomicAllocator.getPointer(DataBuffer, AllocationShape, boolean, CudaContext) |
| org.nd4j.linalg.jcublas.ops.executioner.CudaGridExecutioner.getQueueLength(int) |
| org.tensorflow.framework.FunctionDefOrBuilder.getRet() |
| org.tensorflow.framework.FunctionDef.getRet() |
| org.tensorflow.framework.FunctionDef.Builder.getRet() |
| org.deeplearning4j.arbiter.scoring.util.ScoreUtil.getScoreFromRegressionEval(RegressionEvaluation, RegressionValue) |
| org.tensorflow.framework.GraphDefOrBuilder.getVersion() |
| org.tensorflow.framework.GraphDef.getVersion() |
| org.tensorflow.framework.GraphDef.Builder.getVersion() |
| com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase.getWordIdMap() |
| org.nd4j.util.StringUtils.humanReadableInt(long)
|
| org.nd4j.linalg.api.ndarray.BaseNDArray.index(long, long) |
| org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder.inferenceWorkspaceMode(WorkspaceMode)
|
| org.deeplearning4j.nn.weights.WeightInitUtil.initWeights(double, double, int[], WeightInit, Distribution, char, INDArray) |
| org.deeplearning4j.nn.weights.WeightInitUtil.initWeights(double, double, int[], WeightInit, Distribution, INDArray) |
| org.nd4j.linalg.api.ndarray.BaseNDArray.isCleanedUp() |
| org.nd4j.linalg.api.buffer.BaseDataBuffer.isPersist() |
| org.nd4j.linalg.io.ClassUtils.isPresent(String) |
| org.nd4j.linalg.api.rng.distribution.Distribution.isSupportLowerBoundInclusive()
|
| org.nd4j.linalg.api.rng.distribution.Distribution.isSupportUpperBoundInclusive()
|
| org.nd4j.linalg.api.ndarray.BaseNDArray.isValid() |
| org.nd4j.linalg.api.ndarray.BaseNDArray.isWrapAround() |
| org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.iterate(T, T) |
| org.deeplearning4j.models.embeddings.WeightLookupTable.iterate(T, T) |
| org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.iterateSample(T, T, AtomicLong, double) |
| org.deeplearning4j.models.embeddings.WeightLookupTable.iterateSample(T, T, AtomicLong, double) |
| org.nd4j.linalg.dataset.api.DataSet.iterateWithMiniBatches() |
| org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder.labels(List<String>) |
| org.nd4j.linalg.api.ndarray.BaseNDArray.lengthLong() |
| org.nd4j.util.StringUtils.limitDecimalTo2(double)
|
| org.nd4j.linalg.api.ndarray.BaseNDArray.linearIndex(long) |
| org.nd4j.linalg.api.ndarray.BaseNDArray.linearView()
|
| org.nd4j.linalg.api.ndarray.INDArray.linearView()
|
| org.nd4j.linalg.api.ndarray.BaseNDArray.linearViewColumnOrder() |
| org.nd4j.linalg.api.ndarray.INDArray.linearViewColumnOrder() |
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.loadFullModel(String)
|
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.loadTxtVectors(File) |
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.loadTxtVectors(InputStream, boolean)
|
| org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder.lr(double) |
| org.nd4j.linalg.api.ndarray.BaseNDArray.majorStride() |
| org.nd4j.linalg.dataset.api.DataSetUtil.mergePerOutputMasks2d(long[], INDArray[], INDArray[])
|
| org.deeplearning4j.zoo.InstantiableModel.metaData()
|
| org.deeplearning4j.models.glove.Glove.Builder.negativeSample(double) |
| org.nd4j.linalg.dataset.DataSet.normalizeZeroMeanZeroUnitVariance() |
| org.nd4j.linalg.dataset.api.DataSet.normalizeZeroMeanZeroUnitVariance()
|
| org.deeplearning4j.arbiter.layers.OCNNLayerSpace.Builder.numHidden(int) |
| org.deeplearning4j.arbiter.layers.OCNNLayerSpace.Builder.numHidden(ParameterSpace<Integer>) |
| org.nd4j.linalg.api.shape.Shape.offset(DataBuffer) |
| org.nd4j.linalg.api.shape.Shape.offset(int[]) |
| org.nd4j.linalg.api.shape.Shape.offset(IntBuffer) |
| org.nd4j.linalg.api.shape.Shape.offset(long[]) |
| org.nd4j.linalg.api.shape.Shape.offset(LongBuffer) |
| org.nd4j.linalg.convolution.Convolution.outSize(int, int, int, int, int, boolean) |
| org.nd4j.linalg.api.buffer.BaseDataBuffer.persist() |
| org.deeplearning4j.plot.BarnesHutTsne.plot(INDArray, int, List<String>, String)
|
| org.deeplearning4j.models.paragraphvectors.ParagraphVectors.predict(String) |
| org.nd4j.jita.memory.impl.CudaCachingZeroProvider.printCacheStats() |
| org.nd4j.linalg.profiler.OpProfiler.processBlasCall(String) |
| org.deeplearning4j.models.word2vec.wordstore.VocabCache.putVocabWord(String) |
| org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache.putVocabWord(String) |
| org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache.putVocabWord(String) |
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readParagraphVectorsFromText(File)
|
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readParagraphVectorsFromText(InputStream)
|
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readParagraphVectorsFromText(String)
|
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.readWord2Vec(File) |
| org.nd4j.linalg.api.buffer.BaseDataBuffer.references() |
| org.nd4j.linalg.api.buffer.BaseDataBuffer.removeReferencing(String) |
| org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder.repartitionData(Repartition)
|
| org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder.repartitionStrategy(RepartitionStrategy)
|
| org.nd4j.linalg.api.ndarray.INDArray.repeat(int, int...) |
| org.nd4j.linalg.api.ndarray.BaseNDArray.resetLinearView() |
| org.nd4j.linalg.api.ndarray.INDArray.resetLinearView() |
| org.deeplearning4j.models.glove.Glove.Builder.sampling(double) |
| org.nd4j.linalg.dataset.api.preprocessor.NormalizerMinMaxScaler.save(File...)
|
| org.nd4j.linalg.dataset.api.preprocessor.NormalizerStandardize.save(File...)
|
| org.nd4j.linalg.dataset.api.preprocessor.MultiNormalizerStandardize.save(List<File>, List<File>)
|
| org.nd4j.linalg.factory.BlasWrapper.saxpy(double, INDArray, INDArray) |
| org.nd4j.linalg.factory.BlasWrapper.saxpy(float, INDArray, INDArray) |
| org.nd4j.linalg.factory.BlasWrapper.scal(double, INDArray) |
| org.nd4j.linalg.factory.BlasWrapper.scal(float, INDArray) |
| org.nd4j.linalg.api.ndarray.BaseNDArray.secondaryStride() |
| org.nd4j.linalg.jcublas.buffer.BaseCudaDataBuffer.set(long, long, Pointer) |
| org.nd4j.linalg.jcublas.buffer.BaseCudaDataBuffer.set(long, long, Pointer, long) |
| org.nd4j.linalg.jcublas.buffer.BaseCudaDataBuffer.set(long, Pointer) |
| org.nd4j.linalg.jcublas.buffer.BaseCudaDataBuffer.set(Pointer) |
| org.nd4j.linalg.dataset.DataSet.setColumnNames(List<String>) |
| org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional.setDepth(long) |
| com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase.setDictionaryEntries(List<GenericDictionaryEntry>) |
| org.nd4j.jita.conf.Configuration.setExecutionModel(Configuration.ExecutionModel)
|
| org.deeplearning4j.models.sequencevectors.sequence.SequenceElement.setHistoricalGradient(INDArray) |
| org.datavec.api.transform.join.Join.Builder.setKeyColumns(String...)
|
| org.datavec.api.transform.join.Join.Builder.setKeyColumnsLeft(String...)
|
| org.datavec.api.transform.join.Join.Builder.setKeyColumnsRight(String...)
|
| org.deeplearning4j.text.documentiterator.LabelledDocument.setLabel(String) |
| org.nd4j.linalg.api.shape.Shape.setOrder(IntBuffer, char) |
| org.nd4j.linalg.api.ndarray.INDArray.setShape(long...) |
| org.nd4j.linalg.api.ndarray.INDArray.setStride(long...) |
| org.tensorflow.framework.GraphDef.Builder.setVersion(int) |
| org.nd4j.linalg.api.ndarray.BaseNDArray.setWrapAround(boolean) |
| org.deeplearning4j.models.paragraphvectors.ParagraphVectors.similarityToLabel(String, String) |
| org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder.stepFunction(StepFunction) |
| org.nd4j.linalg.factory.BlasWrapper.syevr(char, char, char, INDArray, double, double, int, int, double, INDArray, INDArray, int[]) |
| org.nd4j.linalg.factory.BlasWrapper.syevr(char, char, char, INDArray, float, float, int, int, float, INDArray, INDArray, int[]) |
| org.nd4j.linalg.dataset.api.DataSetUtil.tailor3d2d(DataSet, boolean) |
| org.datavec.api.util.ndarray.RecordConverter.toArray(Collection<Writable>, int) |
| org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder.trainingWorkspaceMode(WorkspaceMode)
|
| org.deeplearning4j.models.glove.Glove.Builder.trainSequencesRepresentation(boolean) |
| org.nd4j.linalg.api.buffer.BaseDataBuffer.unPersist() |
| org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder.updater(Updater)
|
| org.deeplearning4j.nn.conf.layers.BaseLayer.Builder.updater(Updater) |
| org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder.updater(Updater)
|
| org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder.useAdaGrad(boolean) |
| org.tensorflow.framework.GraphTransferInfo.Destination.valueOf(int)
|
| org.tensorflow.framework.RemoteFusedGraphExecuteInfo.NodeType.valueOf(int)
|
| org.tensorflow.framework.ApiDef.Visibility.valueOf(int)
|
| org.tensorflow.framework.Summary.Value.ValueCase.valueOf(int)
|
| org.tensorflow.framework.AttrValue.ValueCase.valueOf(int)
|
| org.tensorflow.framework.TensorSliceProto.Extent.HasLengthCase.valueOf(int)
|
| onnx.OnnxOperatorsProto3.OperatorProto.OperatorStatus.valueOf(int)
|
| onnx.OnnxProto3.Version.valueOf(int)
|
| onnx.OnnxProto3.AttributeProto.AttributeType.valueOf(int)
|
| onnx.OnnxProto3.TensorProto.DataType.valueOf(int)
|
| onnx.OnnxProto3.TensorShapeProto.Dimension.ValueCase.valueOf(int)
|
| onnx.OnnxProto3.TypeProto.ValueCase.valueOf(int)
|
| onnx.OnnxMlProto3.Version.valueOf(int)
|
| onnx.OnnxMlProto3.AttributeProto.AttributeType.valueOf(int)
|
| onnx.OnnxMlProto3.TensorProto.DataType.valueOf(int)
|
| onnx.OnnxMlProto3.TensorShapeProto.Dimension.ValueCase.valueOf(int)
|
| onnx.OnnxMlProto3.TypeProto.ValueCase.valueOf(int)
|
| org.tensorflow.framework.DataType.valueOf(int)
|
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.writeFullModel(Word2Vec, String)
|
| org.nd4j.linalg.factory.Nd4j.writeTxt(INDArray, String, int)
|
| org.nd4j.linalg.factory.Nd4j.writeTxt(INDArray, String, String)
|
| org.nd4j.linalg.factory.Nd4j.writeTxt(INDArray, String, String, int)
|
| org.nd4j.linalg.factory.Nd4j.writeTxtString(INDArray, OutputStream, int)
|
| org.nd4j.linalg.factory.Nd4j.writeTxtString(INDArray, OutputStream, String)
|
| org.nd4j.linalg.factory.Nd4j.writeTxtString(INDArray, OutputStream, String, int)
|
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.writeWordVectors(InMemoryLookupTable, InMemoryLookupCache, String)
|
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.writeWordVectors(ParagraphVectors, File) |
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.writeWordVectors(ParagraphVectors, OutputStream) |
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.writeWordVectors(ParagraphVectors, String) |
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.writeWordVectors(Word2Vec, BufferedWriter) |
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.writeWordVectors(Word2Vec, File) |
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.writeWordVectors(Word2Vec, OutputStream) |
| org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.writeWordVectors(Word2Vec, String) |