All Classes Interface Summary Class Summary Enum Summary Exception Summary
| Class |
Description |
| AbstractLayer<LayerConfT extends Layer> |
A layer with input and output, no parameters or gradients
|
| AbstractLSTM |
|
| AbstractLSTM.Builder<T extends AbstractLSTM.Builder<T>> |
|
| AbstractSameDiffLayer |
|
| AbstractSameDiffLayer.Builder<T extends AbstractSameDiffLayer.Builder<T>> |
|
| ActivationLayer |
|
| ActivationLayer |
|
| ActivationLayer.Builder |
|
| AdaptiveThresholdAlgorithm |
|
| AlphaDropout |
|
| ArgmaxAdapter |
|
| ArrayEmbeddingInitializer |
|
| ArrayType |
|
| AttentionVertex |
|
| AttentionVertex.Builder |
|
| AutoEncoder |
|
| AutoEncoder |
|
| AutoEncoder.Builder |
|
| AutoencoderScoreCalculator |
|
| BackpropType |
|
| BackTrackLineSearch |
|
| BaseConstraint |
|
| BaseEarlyStoppingTrainer<T extends Model> |
|
| BaseEvaluation<T extends BaseEvaluation> |
Deprecated. |
| BaseGraphVertex |
|
| BaseIEvaluationScoreCalculator<T extends Model,U extends IEvaluation> |
|
| BaseInputPreProcessor |
|
| BaseLayer |
A neural network layer.
|
| BaseLayer<LayerConfT extends BaseLayer> |
A layer with parameters
|
| BaseLayer.Builder<T extends BaseLayer.Builder<T>> |
|
| BaseMKLDNNHelper |
|
| BaseMLNScoreCalculator |
|
| BaseMultiLayerUpdater<T extends Model> |
|
| BaseNetConfigDeserializer<T> |
|
| BaseOptimizer |
Base optimizer
|
| BaseOutputLayer |
|
| BaseOutputLayer<LayerConfT extends BaseOutputLayer> |
|
| BaseOutputLayer.Builder<T extends BaseOutputLayer.Builder<T>> |
|
| BasePretrainNetwork |
|
| BasePretrainNetwork<LayerConfT extends BasePretrainNetwork> |
|
| BasePretrainNetwork.Builder<T extends BasePretrainNetwork.Builder<T>> |
|
| BaseRecurrentLayer |
|
| BaseRecurrentLayer<LayerConfT extends BaseRecurrentLayer> |
|
| BaseRecurrentLayer.Builder<T extends BaseRecurrentLayer.Builder<T>> |
|
| BaseScoreCalculator<T extends Model> |
|
| BaseTrainingListener |
|
| BaseUpsamplingLayer |
Upsampling base layer
|
| BaseUpsamplingLayer.UpsamplingBuilder<T extends BaseUpsamplingLayer.UpsamplingBuilder<T>> |
|
| BaseWrapperLayer |
|
| BaseWrapperLayer |
|
| BaseWrapperVertex |
|
| BasicGradientsAccumulator |
|
| BatchNormalization |
|
| BatchNormalization |
|
| BatchNormalization.Builder |
|
| BatchNormalizationHelper |
|
| BatchNormalizationParamInitializer |
|
| BernoulliReconstructionDistribution |
|
| BestScoreEpochTerminationCondition |
|
| Bidirectional |
|
| Bidirectional.Builder |
|
| Bidirectional.Mode |
This Mode enumeration defines how the activations for the forward and backward networks should be combined.
ADD: out = forward + backward (elementwise addition)
MUL: out = forward * backward (elementwise
multiplication)
AVERAGE: out = 0.5 * (forward + backward)
CONCAT: Concatenate the activations.
Where
'forward' is the activations for the forward RNN, and 'backward' is the activations for the backward RNN.
|
| BidirectionalLayer |
|
| BidirectionalParamInitializer |
|
| BinomialDistribution |
|
| BoundingBoxesDeserializer |
|
| CacheMode |
|
| CapsuleLayer |
|
| CapsuleLayer.Builder |
|
| CapsuleStrengthLayer |
|
| CapsuleStrengthLayer.Builder |
|
| CapsuleUtils |
|
| CenterLossOutputLayer |
|
| CenterLossOutputLayer |
|
| CenterLossOutputLayer.Builder |
|
| CenterLossParamInitializer |
|
| Checkpoint |
|
| CheckpointListener |
|
| CheckpointListener.Builder |
|
| ClassificationScoreCalculator |
|
| Classifier |
|
| CNN2DFormat |
|
| Cnn3DLossLayer |
|
| Cnn3DLossLayer |
|
| Cnn3DLossLayer.Builder |
|
| Cnn3DToFeedForwardPreProcessor |
|
| CnnLossLayer |
|
| CnnLossLayer |
|
| CnnLossLayer.Builder |
|
| CnnToFeedForwardPreProcessor |
|
| CnnToRnnPreProcessor |
|
| CollectScoresIterationListener |
|
| CollectScoresIterationListener.ScoreStat |
|
| CollectScoresListener |
|
| ComposableInputPreProcessor |
|
| ComposableIterationListener |
Deprecated. |
| CompositeReconstructionDistribution |
|
| CompositeReconstructionDistribution.Builder |
|
| ComputationGraph |
|
| ComputationGraphConfiguration |
|
| ComputationGraphConfiguration.GraphBuilder |
|
| ComputationGraphConfigurationDeserializer |
|
| ComputationGraphUpdater |
|
| ComputationGraphUtil |
|
| ConfusionMatrix<T extends Comparable<? super T>> |
Deprecated. |
| ConjugateGradient |
|
| ConstantDistribution |
|
| ConvexOptimizer |
|
| Convolution1D |
|
| Convolution1DLayer |
|
| Convolution1DLayer |
|
| Convolution1DLayer.Builder |
|
| Convolution1DUtils |
|
| Convolution2D |
|
| Convolution3D |
|
| Convolution3D.Builder |
|
| Convolution3D.DataFormat |
An optional dataFormat: "NDHWC" or "NCDHW".
|
| Convolution3DLayer |
|
| Convolution3DParamInitializer |
|
| Convolution3DUtils |
|
| ConvolutionHelper |
|
| ConvolutionLayer |
|
| ConvolutionLayer |
|
| ConvolutionLayer.AlgoMode |
|
| ConvolutionLayer.BaseConvBuilder<T extends ConvolutionLayer.BaseConvBuilder<T>> |
|
| ConvolutionLayer.Builder |
|
| ConvolutionLayer.BwdDataAlgo |
|
| ConvolutionLayer.BwdFilterAlgo |
|
| ConvolutionLayer.FwdAlgo |
|
| ConvolutionMode |
|
| ConvolutionParamInitializer |
|
| ConvolutionUtils |
|
| CrashReportingUtil |
|
| Cropping1D |
|
| Cropping1D.Builder |
|
| Cropping1DLayer |
|
| Cropping2D |
|
| Cropping2D.Builder |
|
| Cropping2DLayer |
|
| Cropping3D |
|
| Cropping3D.Builder |
|
| Cropping3DLayer |
|
| DataFormat |
|
| DataFormatDeserializer |
|
| DataFormatSerializer |
|
| DataSetLossCalculator |
|
| DataSetLossCalculatorCG |
Deprecated. |
| Deconvolution2D |
|
| Deconvolution2D.Builder |
|
| Deconvolution2DLayer |
|
| Deconvolution3D |
|
| Deconvolution3D.Builder |
|
| Deconvolution3DLayer |
|
| Deconvolution3DParamInitializer |
|
| DeconvolutionParamInitializer |
|
| DeepLearningException |
|
| DefaultGradient |
|
| DefaultParamInitializer |
|
| DefaultStepFunction |
|
| DefaultStepFunction |
|
| DenseLayer |
|
| DenseLayer |
|
| DenseLayer.Builder |
|
| DepthwiseConvolution2D |
|
| DepthwiseConvolution2D.Builder |
|
| DepthwiseConvolution2DLayer |
|
| DepthwiseConvolutionParamInitializer |
|
| DetectedObject |
|
| Distribution |
|
| Distributions |
|
| DL4JException |
|
| DL4JInvalidConfigException |
|
| DL4JInvalidInputException |
|
| DL4JModelValidator |
|
| DL4JSameDiffMemoryMgr |
|
| DropConnect |
|
| Dropout |
|
| DropoutHelper |
|
| DropoutLayer |
|
| DropoutLayer |
|
| DropoutLayer.Builder |
|
| DummyConfig |
|
| DuplicateToTimeSeriesVertex |
|
| DuplicateToTimeSeriesVertex |
|
| EarlyStoppingConfiguration<T extends Model> |
|
| EarlyStoppingConfiguration.Builder<T extends Model> |
|
| EarlyStoppingGraphTrainer |
|
| EarlyStoppingListener<T extends Model> |
|
| EarlyStoppingModelSaver<T extends Model> |
|
| EarlyStoppingResult<T extends Model> |
|
| EarlyStoppingResult.TerminationReason |
|
| EarlyStoppingTrainer |
|
| ElementWiseMultiplicationLayer |
|
| ElementWiseMultiplicationLayer |
|
| ElementWiseMultiplicationLayer.Builder |
|
| ElementWiseParamInitializer |
|
| ElementWiseVertex |
|
| ElementWiseVertex |
|
| ElementWiseVertex.Op |
|
| ElementWiseVertex.Op |
|
| EmbeddingInitializer |
|
| EmbeddingLayer |
|
| EmbeddingLayer |
|
| EmbeddingLayer.Builder |
|
| EmbeddingLayerParamInitializer |
|
| EmbeddingSequenceLayer |
|
| EmbeddingSequenceLayer |
|
| EmbeddingSequenceLayer.Builder |
|
| EmptyParamInitializer |
|
| EncodedGradientsAccumulator |
|
| EncodedGradientsAccumulator.Builder |
|
| EncodingHandler |
|
| EpochTerminationCondition |
|
| Evaluation |
Deprecated. |
| Evaluation.Metric |
Deprecated. |
| EvaluationAveraging |
Deprecated. |
| EvaluationBinary |
Deprecated. |
| EvaluationCalibration |
Deprecated. |
| EvaluationCallback |
|
| EvaluationUtils |
Deprecated. |
| EvaluativeListener |
|
| ExponentialReconstructionDistribution |
|
| FailureTestingListener |
|
| FailureTestingListener.And |
|
| FailureTestingListener.CallType |
|
| FailureTestingListener.FailureMode |
|
| FailureTestingListener.FailureTrigger |
|
| FailureTestingListener.HostNameTrigger |
|
| FailureTestingListener.IterationEpochTrigger |
|
| FailureTestingListener.Or |
|
| FailureTestingListener.RandomProb |
|
| FailureTestingListener.TimeSinceInitializedTrigger |
|
| FailureTestingListener.UserNameTrigger |
|
| FancyBlockingQueue<E> |
|
| FeedForwardLayer |
|
| FeedForwardLayer.Builder<T extends FeedForwardLayer.Builder<T>> |
|
| FeedForwardToCnn3DPreProcessor |
|
| FeedForwardToCnnPreProcessor |
|
| FeedForwardToRnnPreProcessor |
|
| FineTuneConfiguration |
|
| FineTuneConfiguration.Builder |
|
| FixedThresholdAlgorithm |
|
| FixedThresholdAlgorithm.FixedAlgorithmThresholdReducer |
|
| FrozenLayer |
|
| FrozenLayer |
|
| FrozenLayer.Builder |
|
| FrozenLayerParamInitializer |
|
| FrozenLayerWithBackprop |
Frozen layer freezes parameters of the layer it wraps, but allows the backpropagation to continue.
|
| FrozenLayerWithBackprop |
Frozen layer freezes parameters of the layer it wraps, but allows the backpropagation to continue.
|
| FrozenLayerWithBackpropParamInitializer |
|
| FrozenVertex |
|
| FrozenVertex |
|
| FwdPassReturn |
|
| FwdPassType |
|
| GaussianDistribution |
Deprecated. |
| GaussianDropout |
|
| GaussianNoise |
|
| GaussianReconstructionDistribution |
|
| GlobalPoolingLayer |
|
| GlobalPoolingLayer |
|
| GlobalPoolingLayer.Builder |
|
| Gradient |
|
| GradientCheckUtil |
|
| GradientCheckUtil.GraphConfig |
|
| GradientCheckUtil.MLNConfig |
|
| GradientCheckUtil.PrintMode |
|
| GradientNormalization |
|
| GradientsAccumulator |
|
| GradientStepFunction |
|
| GradientStepFunction |
|
| GraphBuilderModule |
|
| GraphIndices |
|
| GraphVertex |
|
| GraphVertex |
|
| GravesBidirectionalLSTM |
Deprecated. |
| GravesBidirectionalLSTM |
|
| GravesBidirectionalLSTM.Builder |
|
| GravesBidirectionalLSTMParamInitializer |
|
| GravesLSTM |
Deprecated. |
| GravesLSTM |
Deprecated. |
| GravesLSTM.Builder |
|
| GravesLSTMParamInitializer |
|
| HelperUtils |
Simple meta helper util class for instantiating
platform specific layer helpers that handle interaction with
lower level libraries like cudnn and onednn.
|
| Histogram |
Deprecated. |
| IdentityLayer |
|
| IDropout |
|
| IEarlyStoppingTrainer<T extends Model> |
|
| IEvaluation<T extends IEvaluation> |
Deprecated. |
| IndexedTail |
|
| InMemoryModelSaver<T extends Model> |
|
| InputPreProcessor |
|
| InputType |
|
| InputType.InputTypeConvolutional |
|
| InputType.InputTypeConvolutional3D |
|
| InputType.InputTypeConvolutionalFlat |
|
| InputType.InputTypeFeedForward |
|
| InputType.InputTypeRecurrent |
|
| InputType.Type |
The type of activations in/out of a given GraphVertex
FF: Standard feed-foward (2d minibatch, 1d per example) data
RNN: Recurrent neural network (3d minibatch) time series data
CNN: 2D Convolutional neural network (4d minibatch, [miniBatchSize, channels, height, width])
CNNFlat: Flattened 2D conv net data (2d minibatch, [miniBatchSize, height * width * channels])
CNN3D: 3D convolutional neural network (5d minibatch, [miniBatchSize, channels, height, width, channels])
|
| InputTypeUtil |
|
| InputVertex |
|
| InvalidInputTypeException |
|
| InvalidScoreIterationTerminationCondition |
|
| InvalidStepException |
|
| InvocationType |
|
| IOutputLayer |
|
| IterationListener |
Deprecated. |
| IterationTerminationCondition |
|
| IWeightInit |
|
| IWeightNoise |
|
| JsonMappers |
|
| KerasFlattenRnnPreprocessor |
|
| L2NormalizeVertex |
|
| L2NormalizeVertex |
|
| L2Vertex |
|
| L2Vertex |
|
| LastTimeStep |
|
| LastTimeStepLayer |
|
| LastTimeStepVertex |
|
| LastTimeStepVertex |
|
| Layer |
|
| Layer |
A neural network layer.
|
| Layer.Builder<T extends Layer.Builder<T>> |
|
| Layer.TrainingMode |
|
| Layer.Type |
|
| LayerConstraint |
|
| LayerHelper |
|
| LayerMemoryReport |
|
| LayerMemoryReport.Builder |
|
| LayerUpdater |
|
| LayerValidation |
|
| LayerVertex |
|
| LayerVertex |
|
| LayerWorkspaceMgr |
|
| LayerWorkspaceMgr.Builder |
|
| LBFGS |
LBFGS
|
| LearnedSelfAttentionLayer |
|
| LearnedSelfAttentionLayer.Builder |
|
| LegacyDistributionDeserializer |
|
| LegacyDistributionHelper |
|
| LegacyIntArrayDeserializer |
|
| LegacyJsonFormat |
|
| LegacyJsonFormat.GraphVertexMixin |
|
| LegacyJsonFormat.IActivationMixin |
|
| LegacyJsonFormat.ILossFunctionMixin |
|
| LegacyJsonFormat.InputPreProcessorMixin |
|
| LegacyJsonFormat.LayerMixin |
|
| LegacyJsonFormat.ReconstructionDistributionMixin |
|
| LineGradientDescent |
|
| LineOptimizer |
|
| LocalFileGraphSaver |
|
| LocalFileModelSaver |
|
| LocalHandler |
|
| LocallyConnected1D |
|
| LocallyConnected1D.Builder |
|
| LocallyConnected2D |
|
| LocallyConnected2D.Builder |
|
| LocalResponseNormalization |
|
| LocalResponseNormalization |
|
| LocalResponseNormalization.Builder |
|
| LocalResponseNormalizationHelper |
|
| LogNormalDistribution |
A log-normal distribution, with two parameters: mean and standard deviation.
|
| LossFunctionWrapper |
|
| LossLayer |
|
| LossLayer |
|
| LossLayer.Builder |
|
| LSTM |
|
| LSTM |
|
| LSTM.Builder |
|
| LSTMHelper |
|
| LSTMHelpers |
|
| LSTMParamInitializer |
|
| MaskedReductionUtil |
|
| MaskLayer |
|
| MaskLayer |
|
| MaskState |
|
| MaskZeroLayer |
|
| MaskZeroLayer |
|
| MaskZeroLayer.Builder |
|
| MaxEpochsTerminationCondition |
|
| MaxNormConstraint |
|
| MaxScoreIterationTerminationCondition |
|
| MaxTimeIterationTerminationCondition |
Terminate training based on max time.
|
| MemoryReport |
|
| MemoryType |
|
| MemoryUseMode |
|
| MergeVertex |
|
| MergeVertex |
|
| MessageHandler |
|
| MinMaxNormConstraint |
|
| MKLDNNBatchNormHelper |
|
| MKLDNNConvHelper |
|
| MKLDNNLocalResponseNormalizationHelper |
|
| MKLDNNSubsamplingHelper |
|
| Model |
|
| ModelAdapter<T> |
|
| ModelSavingCallback |
|
| ModelSerializer |
|
| MultiLayerConfiguration |
|
| MultiLayerConfiguration.Builder |
|
| MultiLayerConfigurationDeserializer |
|
| MultiLayerNetwork |
|
| MultiLayerUpdater |
|
| NegativeDefaultStepFunction |
|
| NegativeDefaultStepFunction |
|
| NegativeGradientStepFunction |
|
| NegativeGradientStepFunction |
|
| NetworkMemoryReport |
|
| NetworkUtils |
|
| NeuralNetConfiguration |
|
| NeuralNetConfiguration.Builder |
NeuralNetConfiguration builder, used as a starting point for creating a MultiLayerConfiguration or
ComputationGraphConfiguration.
Note that values set here on the layer will be applied to all relevant layers - unless the value is overridden
on a layer's configuration
|
| NeuralNetConfiguration.ListBuilder |
Fluent interface for building a list of configurations
|
| NeuralNetwork |
|
| NonNegativeConstraint |
|
| NoOpResidualPostProcessor |
|
| NoParamLayer |
|
| NormalDistribution |
A normal (Gaussian) distribution, with two parameters: mean and standard deviation
|
| OCNNOutputLayer |
|
| OCNNOutputLayer |
|
| OCNNOutputLayer.Builder |
|
| OCNNParamInitializer |
|
| OptimizationAlgorithm |
Optimization algorithm to use
|
| OrthogonalDistribution |
|
| OutputLayer |
|
| OutputLayer |
|
| OutputLayer.Builder |
|
| OutputLayerUtil |
|
| ParamInitializer |
Param initializer for a layer
|
| PerformanceListener |
|
| PerformanceListener.Builder |
|
| PermutePreprocessor |
|
| PoolHelperVertex |
|
| PoolHelperVertex |
|
| Pooling1D |
1D Pooling (subsampling) layer.
|
| Pooling2D |
2D Pooling (subsampling) layer.
|
| PoolingType |
Pooling type:
MAX: Max pooling - output is the maximum value of the input values
AVG: Average pooling - output is the average value of the input values
SUM: Sum pooling - output is the sum of the input values
PNORM: P-norm pooling
|
| PrecisionRecallCurve |
Deprecated. |
| PrecisionRecallCurve.Confusion |
|
| PrecisionRecallCurve.Point |
|
| Prediction |
|
| PReLU |
|
| PReLULayer |
|
| PReLULayer.Builder |
|
| PReLUParamInitializer |
|
| PreprocessorVertex |
|
| PreprocessorVertex |
|
| PretrainParamInitializer |
Pretrain weight initializer.
|
| PrimaryCapsules |
|
| PrimaryCapsules.Builder |
|
| ReconstructionDistribution |
|
| RecurrentAttentionLayer |
|
| RecurrentAttentionLayer.Builder |
|
| RecurrentLayer |
|
| Registerable |
|
| Regression2dAdapter |
|
| RegressionEvaluation |
Deprecated. |
| RegressionEvaluation.Metric |
Deprecated.
|
| RegressionScoreCalculator |
|
| ReliabilityDiagram |
Deprecated. |
| RepeatVector |
|
| RepeatVector |
|
| RepeatVector.Builder<T extends RepeatVector.Builder<T>> |
|
| ReshapePreprocessor |
|
| ReshapeVertex |
|
| ReshapeVertex |
|
| ResidualClippingPostProcessor |
|
| ResidualPostProcessor |
|
| ReverseTimeSeriesVertex |
|
| ReverseTimeSeriesVertex |
|
| RNNFormat |
|
| RnnLossLayer |
|
| RnnLossLayer |
|
| RnnLossLayer.Builder |
|
| RnnOutputLayer |
|
| RnnOutputLayer |
|
| RnnOutputLayer.Builder |
|
| RnnToCnnPreProcessor |
|
| RnnToFeedForwardPreProcessor |
|
| ROC |
Deprecated. |
| ROC.CountsForThreshold |
Deprecated.
|
| ROCBinary |
Deprecated. |
| RocCurve |
Deprecated. |
| ROCMultiClass |
Deprecated. |
| ROCScoreCalculator |
|
| ROCScoreCalculator.Metric |
|
| ROCScoreCalculator.ROCType |
|
| SameDiffGraphVertex |
|
| SameDiffLambdaLayer |
|
| SameDiffLambdaVertex |
|
| SameDiffLayer |
|
| SameDiffLayer |
|
| SameDiffLayer.Builder<T extends SameDiffLayer.Builder<T>> |
|
| SameDiffLayerUtils |
|
| SameDiffOutputLayer |
|
| SameDiffOutputLayer |
|
| SameDiffParamInitializer |
|
| SameDiffVertex |
|
| ScaleVertex |
|
| ScaleVertex |
|
| ScoreCalculator<T extends Model> |
|
| ScoreImprovementEpochTerminationCondition |
|
| ScoreIterationListener |
|
| SDLayerParams |
|
| SDVertexParams |
|
| SelfAttentionLayer |
|
| SelfAttentionLayer.Builder |
|
| SeparableConvolution2D |
|
| SeparableConvolution2D.Builder |
|
| SeparableConvolution2DLayer |
|
| SeparableConvolutionParamInitializer |
|
| SharedGradient |
|
| ShiftVertex |
|
| ShiftVertex |
|
| SimpleRnn |
|
| SimpleRnn |
|
| SimpleRnn.Builder |
|
| SimpleRnnParamInitializer |
|
| SleepyTrainingListener |
|
| SleepyTrainingListener.SleepMode |
|
| SleepyTrainingListener.TimeMode |
|
| Solver |
|
| Solver.Builder |
|
| SpaceToBatch |
|
| SpaceToBatchLayer |
|
| SpaceToBatchLayer.Builder<T extends SpaceToBatchLayer.Builder<T>> |
|
| SpaceToDepth |
|
| SpaceToDepthLayer |
|
| SpaceToDepthLayer.Builder<T extends SpaceToDepthLayer.Builder<T>> |
|
| SpaceToDepthLayer.DataFormat |
Deprecated.
|
| SpatialDropout |
|
| StackVertex |
|
| StackVertex |
|
| StepFunction |
|
| StepFunction |
|
| StepFunctions |
|
| StochasticGradientDescent |
|
| Subsampling1DLayer |
|
| Subsampling1DLayer |
|
| Subsampling1DLayer.Builder |
|
| Subsampling3DLayer |
|
| Subsampling3DLayer |
|
| Subsampling3DLayer.BaseSubsamplingBuilder<T extends Subsampling3DLayer.BaseSubsamplingBuilder<T>> |
|
| Subsampling3DLayer.Builder |
|
| Subsampling3DLayer.PoolingType |
|
| SubsamplingHelper |
Helper for the subsampling layer.
|
| SubsamplingLayer |
|
| SubsamplingLayer |
|
| SubsamplingLayer.BaseSubsamplingBuilder<T extends SubsamplingLayer.BaseSubsamplingBuilder<T>> |
|
| SubsamplingLayer.Builder |
|
| SubsamplingLayer.PoolingType |
|
| SubsetVertex |
|
| SubsetVertex |
|
| TargetSparsityThresholdAlgorithm |
|
| ThresholdAlgorithm |
|
| ThresholdAlgorithmReducer |
|
| TimeDistributed |
|
| TimeDistributedLayer |
|
| TimeIterationListener |
|
| TimeSeriesUtils |
|
| Trainable |
|
| TrainingConfig |
|
| TrainingListener |
|
| TransferLearning |
|
| TransferLearning.Builder |
|
| TransferLearning.GraphBuilder |
|
| TransferLearningHelper |
|
| Tree |
|
| TruncatedNormalDistribution |
|
| UniformDistribution |
A uniform distribution, with two parameters: lower and upper - i.e., U(lower,upper)
|
| UnitNormConstraint |
|
| UnstackVertex |
|
| UnstackVertex |
|
| Updater |
Update the model
|
| Updater |
All the possible different updaters
|
| UpdaterBlock |
|
| UpdaterBlock.ParamState |
|
| UpdaterCreator |
|
| UpdaterUtils |
|
| Upsampling1D |
|
| Upsampling1D |
|
| Upsampling1D.Builder |
|
| Upsampling2D |
|
| Upsampling2D |
|
| Upsampling2D.Builder |
|
| Upsampling3D |
|
| Upsampling3D |
|
| Upsampling3D.Builder |
|
| VAEReconErrorScoreCalculator |
|
| VAEReconProbScoreCalculator |
|
| ValidationUtils |
Validation methods for array sizes/shapes and value non-negativeness
|
| VariationalAutoencoder |
|
| VariationalAutoencoder |
|
| VariationalAutoencoder.Builder |
|
| VariationalAutoencoderParamInitializer |
|
| VertexIndices |
|
| WeightInit |
|
| WeightInitConstant |
|
| WeightInitDistribution |
|
| WeightInitEmbedding |
|
| WeightInitIdentity |
|
| WeightInitLecunUniform |
Uniform U[-a,a] with a=3/sqrt(fanIn).
|
| WeightInitNormal |
Normal/Gaussian distribution, with mean 0 and standard deviation 1/sqrt(fanIn).
|
| WeightInitRelu |
|
| WeightInitReluUniform |
|
| WeightInitSigmoidUniform |
|
| WeightInitUniform |
|
| WeightInitUtil |
Weight initialization utility
|
| WeightInitVarScalingNormalFanAvg |
|
| WeightInitVarScalingNormalFanIn |
|
| WeightInitVarScalingNormalFanOut |
|
| WeightInitVarScalingUniformFanAvg |
Uniform U[-a,a] with a=3.0/((fanIn + fanOut)/2)
|
| WeightInitVarScalingUniformFanIn |
|
| WeightInitVarScalingUniformFanOut |
|
| WeightInitXavier |
|
| WeightInitXavierLegacy |
Xavier weight init in DL4J up to 0.6.0.
|
| WeightInitXavierUniform |
As per Glorot and Bengio 2010: Uniform distribution U(-s,s) with s = sqrt(6/(fanIn + fanOut))
|
| WeightNoise |
|
| WorkspaceMode |
|
| WrapperLayerParamInitializer |
|
| Yolo2OutputLayer |
|
| Yolo2OutputLayer |
|
| Yolo2OutputLayer.Builder |
|
| YoloModelAdapter |
|
| YoloUtils |
|
| ZeroPadding1DLayer |
|
| ZeroPadding1DLayer |
|
| ZeroPadding1DLayer.Builder |
|
| ZeroPadding3DLayer |
|
| ZeroPadding3DLayer |
|
| ZeroPadding3DLayer.Builder |
|
| ZeroPaddingLayer |
|
| ZeroPaddingLayer |
|
| ZeroPaddingLayer.Builder |
|