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
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AbstractLSTM |
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AbstractLSTM.Builder<T extends AbstractLSTM.Builder<T>> |
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AbstractSameDiffLayer |
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AbstractSameDiffLayer.Builder<T extends AbstractSameDiffLayer.Builder<T>> |
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ActivationLayer |
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ActivationLayer |
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ActivationLayer.Builder |
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AdaptiveThresholdAlgorithm |
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AlphaDropout |
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ArgmaxAdapter |
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ArrayEmbeddingInitializer |
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ArrayType |
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AttentionVertex |
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AttentionVertex.Builder |
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AutoEncoder |
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AutoEncoder |
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AutoEncoder.Builder |
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AutoencoderScoreCalculator |
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BackpropType |
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BackTrackLineSearch |
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BaseConstraint |
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BaseEarlyStoppingTrainer<T extends Model> |
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BaseEvaluation<T extends BaseEvaluation> |
Deprecated. |
BaseGraphVertex |
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BaseIEvaluationScoreCalculator<T extends Model,U extends IEvaluation> |
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BaseInputPreProcessor |
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BaseLayer |
A neural network layer.
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BaseLayer<LayerConfT extends BaseLayer> |
A layer with parameters
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BaseLayer.Builder<T extends BaseLayer.Builder<T>> |
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BaseMKLDNNHelper |
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BaseMLNScoreCalculator |
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BaseMultiLayerUpdater<T extends Model> |
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BaseNetConfigDeserializer<T> |
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BaseOptimizer |
Base optimizer
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BaseOutputLayer |
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BaseOutputLayer<LayerConfT extends BaseOutputLayer> |
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BaseOutputLayer.Builder<T extends BaseOutputLayer.Builder<T>> |
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BasePretrainNetwork |
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BasePretrainNetwork<LayerConfT extends BasePretrainNetwork> |
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BasePretrainNetwork.Builder<T extends BasePretrainNetwork.Builder<T>> |
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BaseRecurrentLayer |
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BaseRecurrentLayer<LayerConfT extends BaseRecurrentLayer> |
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BaseRecurrentLayer.Builder<T extends BaseRecurrentLayer.Builder<T>> |
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BaseScoreCalculator<T extends Model> |
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BaseTrainingListener |
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BaseUpsamplingLayer |
Upsampling base layer
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BaseUpsamplingLayer.UpsamplingBuilder<T extends BaseUpsamplingLayer.UpsamplingBuilder<T>> |
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BaseWrapperLayer |
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BaseWrapperLayer |
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BaseWrapperVertex |
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BasicGradientsAccumulator |
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BatchNormalization |
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BatchNormalization |
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BatchNormalization.Builder |
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BatchNormalizationHelper |
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BatchNormalizationParamInitializer |
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BernoulliReconstructionDistribution |
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BestScoreEpochTerminationCondition |
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Bidirectional |
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Bidirectional.Builder |
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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.
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BidirectionalLayer |
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BidirectionalParamInitializer |
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BinomialDistribution |
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BoundingBoxesDeserializer |
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CacheMode |
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CapsuleLayer |
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CapsuleLayer.Builder |
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CapsuleStrengthLayer |
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CapsuleStrengthLayer.Builder |
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CapsuleUtils |
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CenterLossOutputLayer |
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CenterLossOutputLayer |
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CenterLossOutputLayer.Builder |
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CenterLossParamInitializer |
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Checkpoint |
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CheckpointListener |
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CheckpointListener.Builder |
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ClassificationScoreCalculator |
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Classifier |
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CNN2DFormat |
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Cnn3DLossLayer |
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Cnn3DLossLayer |
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Cnn3DLossLayer.Builder |
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Cnn3DToFeedForwardPreProcessor |
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CnnLossLayer |
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CnnLossLayer |
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CnnLossLayer.Builder |
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CnnToFeedForwardPreProcessor |
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CnnToRnnPreProcessor |
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CollectScoresIterationListener |
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CollectScoresIterationListener.ScoreStat |
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CollectScoresListener |
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ComposableInputPreProcessor |
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ComposableIterationListener |
Deprecated. |
CompositeReconstructionDistribution |
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CompositeReconstructionDistribution.Builder |
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ComputationGraph |
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ComputationGraphConfiguration |
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ComputationGraphConfiguration.GraphBuilder |
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ComputationGraphConfigurationDeserializer |
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ComputationGraphUpdater |
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ComputationGraphUtil |
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ConfusionMatrix<T extends Comparable<? super T>> |
Deprecated. |
ConjugateGradient |
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ConstantDistribution |
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ConvexOptimizer |
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Convolution1D |
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Convolution1DLayer |
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Convolution1DLayer |
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Convolution1DLayer.Builder |
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Convolution1DUtils |
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Convolution2D |
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Convolution3D |
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Convolution3D.Builder |
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Convolution3D.DataFormat |
An optional dataFormat: "NDHWC" or "NCDHW".
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Convolution3DLayer |
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Convolution3DParamInitializer |
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Convolution3DUtils |
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ConvolutionHelper |
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ConvolutionLayer |
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ConvolutionLayer |
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ConvolutionLayer.AlgoMode |
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ConvolutionLayer.BaseConvBuilder<T extends ConvolutionLayer.BaseConvBuilder<T>> |
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ConvolutionLayer.Builder |
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ConvolutionLayer.BwdDataAlgo |
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ConvolutionLayer.BwdFilterAlgo |
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ConvolutionLayer.FwdAlgo |
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ConvolutionMode |
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ConvolutionParamInitializer |
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ConvolutionUtils |
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CrashReportingUtil |
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Cropping1D |
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Cropping1D.Builder |
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Cropping1DLayer |
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Cropping2D |
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Cropping2D.Builder |
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Cropping2DLayer |
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Cropping3D |
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Cropping3D.Builder |
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Cropping3DLayer |
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DataFormat |
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DataFormatDeserializer |
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DataFormatSerializer |
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DataSetLossCalculator |
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DataSetLossCalculatorCG |
Deprecated. |
Deconvolution2D |
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Deconvolution2D.Builder |
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Deconvolution2DLayer |
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Deconvolution3D |
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Deconvolution3D.Builder |
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Deconvolution3DLayer |
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Deconvolution3DParamInitializer |
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DeconvolutionParamInitializer |
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DeepLearningException |
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DefaultGradient |
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DefaultParamInitializer |
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DefaultStepFunction |
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DefaultStepFunction |
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DenseLayer |
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DenseLayer |
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DenseLayer.Builder |
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DepthwiseConvolution2D |
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DepthwiseConvolution2D.Builder |
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DepthwiseConvolution2DLayer |
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DepthwiseConvolutionParamInitializer |
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DetectedObject |
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Distribution |
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Distributions |
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DL4JException |
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DL4JInvalidConfigException |
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DL4JInvalidInputException |
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DL4JModelValidator |
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DL4JSameDiffMemoryMgr |
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DropConnect |
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Dropout |
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DropoutHelper |
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DropoutLayer |
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DropoutLayer |
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DropoutLayer.Builder |
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DummyConfig |
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DuplicateToTimeSeriesVertex |
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DuplicateToTimeSeriesVertex |
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EarlyStoppingConfiguration<T extends Model> |
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EarlyStoppingConfiguration.Builder<T extends Model> |
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EarlyStoppingGraphTrainer |
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EarlyStoppingListener<T extends Model> |
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EarlyStoppingModelSaver<T extends Model> |
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EarlyStoppingResult<T extends Model> |
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EarlyStoppingResult.TerminationReason |
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EarlyStoppingTrainer |
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ElementWiseMultiplicationLayer |
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ElementWiseMultiplicationLayer |
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ElementWiseMultiplicationLayer.Builder |
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ElementWiseParamInitializer |
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ElementWiseVertex |
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ElementWiseVertex |
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ElementWiseVertex.Op |
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ElementWiseVertex.Op |
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EmbeddingInitializer |
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EmbeddingLayer |
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EmbeddingLayer |
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EmbeddingLayer.Builder |
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EmbeddingLayerParamInitializer |
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EmbeddingSequenceLayer |
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EmbeddingSequenceLayer |
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EmbeddingSequenceLayer.Builder |
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EmptyParamInitializer |
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EncodedGradientsAccumulator |
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EncodedGradientsAccumulator.Builder |
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EncodingHandler |
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EpochTerminationCondition |
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Evaluation |
Deprecated. |
Evaluation.Metric |
Deprecated. |
EvaluationAveraging |
Deprecated. |
EvaluationBinary |
Deprecated. |
EvaluationCalibration |
Deprecated. |
EvaluationCallback |
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EvaluationUtils |
Deprecated. |
EvaluativeListener |
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ExponentialReconstructionDistribution |
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FailureTestingListener |
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FailureTestingListener.And |
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FailureTestingListener.CallType |
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FailureTestingListener.FailureMode |
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FailureTestingListener.FailureTrigger |
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FailureTestingListener.HostNameTrigger |
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FailureTestingListener.IterationEpochTrigger |
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FailureTestingListener.Or |
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FailureTestingListener.RandomProb |
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FailureTestingListener.TimeSinceInitializedTrigger |
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FailureTestingListener.UserNameTrigger |
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FancyBlockingQueue<E> |
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FeedForwardLayer |
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FeedForwardLayer.Builder<T extends FeedForwardLayer.Builder<T>> |
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FeedForwardToCnn3DPreProcessor |
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FeedForwardToCnnPreProcessor |
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FeedForwardToRnnPreProcessor |
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FineTuneConfiguration |
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FineTuneConfiguration.Builder |
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FixedThresholdAlgorithm |
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FixedThresholdAlgorithm.FixedAlgorithmThresholdReducer |
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FrozenLayer |
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FrozenLayer |
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FrozenLayer.Builder |
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FrozenLayerParamInitializer |
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FrozenLayerWithBackprop |
Frozen layer freezes parameters of the layer it wraps, but allows the backpropagation to continue.
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FrozenLayerWithBackprop |
Frozen layer freezes parameters of the layer it wraps, but allows the backpropagation to continue.
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FrozenLayerWithBackpropParamInitializer |
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FrozenVertex |
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FrozenVertex |
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FwdPassReturn |
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FwdPassType |
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GaussianDistribution |
Deprecated. |
GaussianDropout |
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GaussianNoise |
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GaussianReconstructionDistribution |
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GlobalPoolingLayer |
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GlobalPoolingLayer |
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GlobalPoolingLayer.Builder |
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Gradient |
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GradientCheckUtil |
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GradientCheckUtil.GraphConfig |
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GradientCheckUtil.MLNConfig |
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GradientCheckUtil.PrintMode |
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GradientNormalization |
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GradientsAccumulator |
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GradientStepFunction |
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GradientStepFunction |
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GraphBuilderModule |
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GraphIndices |
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GraphVertex |
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GraphVertex |
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GravesBidirectionalLSTM |
Deprecated. |
GravesBidirectionalLSTM |
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GravesBidirectionalLSTM.Builder |
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GravesBidirectionalLSTMParamInitializer |
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GravesLSTM |
Deprecated. |
GravesLSTM |
Deprecated. |
GravesLSTM.Builder |
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GravesLSTMParamInitializer |
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HelperUtils |
Simple meta helper util class for instantiating
platform specific layer helpers that handle interaction with
lower level libraries like cudnn and onednn.
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Histogram |
Deprecated. |
IdentityLayer |
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IDropout |
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IEarlyStoppingTrainer<T extends Model> |
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IEvaluation<T extends IEvaluation> |
Deprecated. |
IndexedTail |
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InMemoryModelSaver<T extends Model> |
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InputPreProcessor |
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InputType |
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InputType.InputTypeConvolutional |
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InputType.InputTypeConvolutional3D |
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InputType.InputTypeConvolutionalFlat |
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InputType.InputTypeFeedForward |
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InputType.InputTypeRecurrent |
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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])
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InputTypeUtil |
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InputVertex |
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InvalidInputTypeException |
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InvalidScoreIterationTerminationCondition |
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InvalidStepException |
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InvocationType |
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IOutputLayer |
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IterationListener |
Deprecated. |
IterationTerminationCondition |
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IWeightInit |
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IWeightNoise |
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JsonMappers |
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KerasFlattenRnnPreprocessor |
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L2NormalizeVertex |
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L2NormalizeVertex |
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L2Vertex |
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L2Vertex |
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LastTimeStep |
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LastTimeStepLayer |
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LastTimeStepVertex |
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LastTimeStepVertex |
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Layer |
|
Layer |
A neural network layer.
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Layer.Builder<T extends Layer.Builder<T>> |
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Layer.TrainingMode |
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Layer.Type |
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LayerConstraint |
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LayerHelper |
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LayerMemoryReport |
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LayerMemoryReport.Builder |
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LayerUpdater |
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LayerValidation |
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LayerVertex |
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LayerVertex |
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LayerWorkspaceMgr |
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LayerWorkspaceMgr.Builder |
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LBFGS |
LBFGS
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LearnedSelfAttentionLayer |
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LearnedSelfAttentionLayer.Builder |
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LegacyDistributionDeserializer |
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LegacyDistributionHelper |
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LegacyIntArrayDeserializer |
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LegacyJsonFormat |
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LegacyJsonFormat.GraphVertexMixin |
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LegacyJsonFormat.IActivationMixin |
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LegacyJsonFormat.ILossFunctionMixin |
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LegacyJsonFormat.InputPreProcessorMixin |
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LegacyJsonFormat.LayerMixin |
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LegacyJsonFormat.ReconstructionDistributionMixin |
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LineGradientDescent |
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LineOptimizer |
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LocalFileGraphSaver |
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LocalFileModelSaver |
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LocalHandler |
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LocallyConnected1D |
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LocallyConnected1D.Builder |
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LocallyConnected2D |
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LocallyConnected2D.Builder |
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LocalResponseNormalization |
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LocalResponseNormalization |
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LocalResponseNormalization.Builder |
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LocalResponseNormalizationHelper |
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LogNormalDistribution |
A log-normal distribution, with two parameters: mean and standard deviation.
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LossFunctionWrapper |
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LossLayer |
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LossLayer |
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LossLayer.Builder |
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LSTM |
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LSTM |
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LSTM.Builder |
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LSTMHelper |
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LSTMHelpers |
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LSTMParamInitializer |
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MaskedReductionUtil |
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MaskLayer |
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MaskLayer |
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MaskState |
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MaskZeroLayer |
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MaskZeroLayer |
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MaskZeroLayer.Builder |
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MaxEpochsTerminationCondition |
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MaxNormConstraint |
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MaxScoreIterationTerminationCondition |
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MaxTimeIterationTerminationCondition |
Terminate training based on max time.
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MemoryReport |
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MemoryType |
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MemoryUseMode |
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MergeVertex |
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MergeVertex |
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MessageHandler |
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MinMaxNormConstraint |
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MKLDNNBatchNormHelper |
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MKLDNNConvHelper |
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MKLDNNLocalResponseNormalizationHelper |
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MKLDNNSubsamplingHelper |
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Model |
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ModelAdapter<T> |
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ModelSavingCallback |
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ModelSerializer |
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MultiLayerConfiguration |
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MultiLayerConfiguration.Builder |
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MultiLayerConfigurationDeserializer |
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MultiLayerNetwork |
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MultiLayerUpdater |
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NegativeDefaultStepFunction |
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NegativeDefaultStepFunction |
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NegativeGradientStepFunction |
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NegativeGradientStepFunction |
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NetworkMemoryReport |
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NetworkUtils |
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NeuralNetConfiguration |
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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
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NeuralNetConfiguration.ListBuilder |
Fluent interface for building a list of configurations
|
NeuralNetwork |
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NonNegativeConstraint |
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NoOpResidualPostProcessor |
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NoParamLayer |
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NormalDistribution |
A normal (Gaussian) distribution, with two parameters: mean and standard deviation
|
OCNNOutputLayer |
|
OCNNOutputLayer |
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OCNNOutputLayer.Builder |
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OCNNParamInitializer |
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OptimizationAlgorithm |
Optimization algorithm to use
|
OrthogonalDistribution |
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OutputLayer |
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OutputLayer |
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OutputLayer.Builder |
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OutputLayerUtil |
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ParamInitializer |
Param initializer for a layer
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PerformanceListener |
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PerformanceListener.Builder |
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PermutePreprocessor |
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PoolHelperVertex |
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PoolHelperVertex |
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Pooling1D |
1D Pooling (subsampling) layer.
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Pooling2D |
2D Pooling (subsampling) layer.
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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
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PrecisionRecallCurve |
Deprecated. |
PrecisionRecallCurve.Confusion |
|
PrecisionRecallCurve.Point |
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Prediction |
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PReLU |
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PReLULayer |
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PReLULayer.Builder |
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PReLUParamInitializer |
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PreprocessorVertex |
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PreprocessorVertex |
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PretrainParamInitializer |
Pretrain weight initializer.
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PrimaryCapsules |
|
PrimaryCapsules.Builder |
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ReconstructionDistribution |
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RecurrentAttentionLayer |
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RecurrentAttentionLayer.Builder |
|
RecurrentLayer |
|
Registerable |
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Regression2dAdapter |
|
RegressionEvaluation |
Deprecated. |
RegressionEvaluation.Metric |
Deprecated.
|
RegressionScoreCalculator |
|
ReliabilityDiagram |
Deprecated. |
RepeatVector |
|
RepeatVector |
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RepeatVector.Builder<T extends RepeatVector.Builder<T>> |
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ReshapePreprocessor |
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ReshapeVertex |
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ReshapeVertex |
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ResidualClippingPostProcessor |
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ResidualPostProcessor |
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ReverseTimeSeriesVertex |
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ReverseTimeSeriesVertex |
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RNNFormat |
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RnnLossLayer |
|
RnnLossLayer |
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RnnLossLayer.Builder |
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RnnOutputLayer |
|
RnnOutputLayer |
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RnnOutputLayer.Builder |
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RnnToCnnPreProcessor |
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RnnToFeedForwardPreProcessor |
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ROC |
Deprecated. |
ROC.CountsForThreshold |
Deprecated.
|
ROCBinary |
Deprecated. |
RocCurve |
Deprecated. |
ROCMultiClass |
Deprecated. |
ROCScoreCalculator |
|
ROCScoreCalculator.Metric |
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ROCScoreCalculator.ROCType |
|
SameDiffGraphVertex |
|
SameDiffLambdaLayer |
|
SameDiffLambdaVertex |
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SameDiffLayer |
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SameDiffLayer |
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SameDiffLayer.Builder<T extends SameDiffLayer.Builder<T>> |
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SameDiffLayerUtils |
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SameDiffOutputLayer |
|
SameDiffOutputLayer |
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SameDiffParamInitializer |
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SameDiffVertex |
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ScaleVertex |
|
ScaleVertex |
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ScoreCalculator<T extends Model> |
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ScoreImprovementEpochTerminationCondition |
|
ScoreIterationListener |
|
SDLayerParams |
|
SDVertexParams |
|
SelfAttentionLayer |
|
SelfAttentionLayer.Builder |
|
SeparableConvolution2D |
|
SeparableConvolution2D.Builder |
|
SeparableConvolution2DLayer |
|
SeparableConvolutionParamInitializer |
|
SharedGradient |
|
ShiftVertex |
|
ShiftVertex |
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SimpleRnn |
|
SimpleRnn |
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SimpleRnn.Builder |
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SimpleRnnParamInitializer |
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SleepyTrainingListener |
|
SleepyTrainingListener.SleepMode |
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SleepyTrainingListener.TimeMode |
|
Solver |
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Solver.Builder |
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SpaceToBatch |
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SpaceToBatchLayer |
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SpaceToBatchLayer.Builder<T extends SpaceToBatchLayer.Builder<T>> |
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SpaceToDepth |
|
SpaceToDepthLayer |
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SpaceToDepthLayer.Builder<T extends SpaceToDepthLayer.Builder<T>> |
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SpaceToDepthLayer.DataFormat |
Deprecated.
|
SpatialDropout |
|
StackVertex |
|
StackVertex |
|
StepFunction |
|
StepFunction |
|
StepFunctions |
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StochasticGradientDescent |
|
Subsampling1DLayer |
|
Subsampling1DLayer |
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Subsampling1DLayer.Builder |
|
Subsampling3DLayer |
|
Subsampling3DLayer |
|
Subsampling3DLayer.BaseSubsamplingBuilder<T extends Subsampling3DLayer.BaseSubsamplingBuilder<T>> |
|
Subsampling3DLayer.Builder |
|
Subsampling3DLayer.PoolingType |
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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 |
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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 |
|