Uses of Class
org.deeplearning4j.nn.multilayer.MultiLayerNetwork
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Uses of MultiLayerNetwork in org.deeplearning4j.earlystopping.saver
Methods in org.deeplearning4j.earlystopping.saver that return MultiLayerNetwork Modifier and Type Method Description MultiLayerNetworkLocalFileModelSaver. getBestModel()MultiLayerNetworkLocalFileModelSaver. getLatestModel()Methods in org.deeplearning4j.earlystopping.saver with parameters of type MultiLayerNetwork Modifier and Type Method Description voidLocalFileModelSaver. saveBestModel(MultiLayerNetwork net, double score)voidLocalFileModelSaver. saveLatestModel(MultiLayerNetwork net, double score) -
Uses of MultiLayerNetwork in org.deeplearning4j.earlystopping.scorecalc.base
Methods in org.deeplearning4j.earlystopping.scorecalc.base with parameters of type MultiLayerNetwork Modifier and Type Method Description protected INDArray[]BaseMLNScoreCalculator. output(MultiLayerNetwork network, INDArray[] input, INDArray[] fMask, INDArray[] lMask)protected INDArrayBaseMLNScoreCalculator. output(MultiLayerNetwork network, INDArray input, INDArray fMask, INDArray lMask)protected doubleBaseMLNScoreCalculator. scoreMinibatch(MultiLayerNetwork network, INDArray[] features, INDArray[] labels, INDArray[] fMask, INDArray[] lMask, INDArray[] output) -
Uses of MultiLayerNetwork in org.deeplearning4j.earlystopping.trainer
Constructors in org.deeplearning4j.earlystopping.trainer with parameters of type MultiLayerNetwork Constructor Description EarlyStoppingTrainer(EarlyStoppingConfiguration<MultiLayerNetwork> esConfig, MultiLayerNetwork net, DataSetIterator train)EarlyStoppingTrainer(EarlyStoppingConfiguration<MultiLayerNetwork> esConfig, MultiLayerNetwork net, DataSetIterator train, EarlyStoppingListener<MultiLayerNetwork> listener)Constructor parameters in org.deeplearning4j.earlystopping.trainer with type arguments of type MultiLayerNetwork Constructor Description EarlyStoppingTrainer(EarlyStoppingConfiguration<MultiLayerNetwork> earlyStoppingConfiguration, MultiLayerConfiguration configuration, DataSetIterator train)EarlyStoppingTrainer(EarlyStoppingConfiguration<MultiLayerNetwork> esConfig, MultiLayerNetwork net, DataSetIterator train)EarlyStoppingTrainer(EarlyStoppingConfiguration<MultiLayerNetwork> esConfig, MultiLayerNetwork net, DataSetIterator train, EarlyStoppingListener<MultiLayerNetwork> listener)EarlyStoppingTrainer(EarlyStoppingConfiguration<MultiLayerNetwork> esConfig, MultiLayerNetwork net, DataSetIterator train, EarlyStoppingListener<MultiLayerNetwork> listener) -
Uses of MultiLayerNetwork in org.deeplearning4j.gradientcheck
Methods in org.deeplearning4j.gradientcheck with parameters of type MultiLayerNetwork Modifier and Type Method Description static booleanGradientCheckUtil. checkGradients(MultiLayerNetwork mln, double epsilon, double maxRelError, double minAbsoluteError, boolean print, boolean exitOnFirstError, INDArray input, INDArray labels)Deprecated.static booleanGradientCheckUtil. checkGradients(MultiLayerNetwork mln, double epsilon, double maxRelError, double minAbsoluteError, boolean print, boolean exitOnFirstError, INDArray input, INDArray labels, INDArray inputMask, INDArray labelMask, boolean subset, int maxPerParam, Set<String> excludeParams, Integer rngSeedResetEachIter)Deprecated. -
Uses of MultiLayerNetwork in org.deeplearning4j.nn.multilayer
Methods in org.deeplearning4j.nn.multilayer that return MultiLayerNetwork Modifier and Type Method Description MultiLayerNetworkMultiLayerNetwork. clone()Clone the MultiLayerNetworkMultiLayerNetworkMultiLayerNetwork. convertDataType(@NonNull DataType dataType)Return a copy of the network with the parameters and activations set to use the specified (floating point) data type.static MultiLayerNetworkMultiLayerNetwork. load(File f, boolean loadUpdater)Restore a MultiLayerNetwork to a file, saved usingsave(File)orModelSerializer -
Uses of MultiLayerNetwork in org.deeplearning4j.nn.transferlearning
Methods in org.deeplearning4j.nn.transferlearning that return MultiLayerNetwork Modifier and Type Method Description MultiLayerNetworkTransferLearning.Builder. build()Returns a model with the fine tune configuration and specified architecture changes.MultiLayerNetworkTransferLearningHelper. unfrozenMLN()Returns the unfrozen layers of the MultiLayerNetwork as a multilayernetwork Note that with each call to featurizedFit the parameters to the original MLN are also updatedConstructors in org.deeplearning4j.nn.transferlearning with parameters of type MultiLayerNetwork Constructor Description Builder(MultiLayerNetwork origModel)Multilayer Network to tweak for transfer learningTransferLearningHelper(MultiLayerNetwork orig)Expects a MLN where some layers are frozenTransferLearningHelper(MultiLayerNetwork orig, int frozenTill)Will modify the given MLN (in place!) to freeze layers (hold params constant during training) specified and below -
Uses of MultiLayerNetwork in org.deeplearning4j.nn.updater
Constructors in org.deeplearning4j.nn.updater with parameters of type MultiLayerNetwork Constructor Description MultiLayerUpdater(MultiLayerNetwork network)MultiLayerUpdater(MultiLayerNetwork network, INDArray updaterState) -
Uses of MultiLayerNetwork in org.deeplearning4j.optimize.listeners
Methods in org.deeplearning4j.optimize.listeners that return MultiLayerNetwork Modifier and Type Method Description MultiLayerNetworkCheckpointListener. loadCheckpointMLN(int checkpointNum)Load a MultiLayerNetwork for the given checkpoint numberstatic MultiLayerNetworkCheckpointListener. loadCheckpointMLN(File rootDir, int checkpointNum)Load a MultiLayerNetwork for the given checkpoint numberstatic MultiLayerNetworkCheckpointListener. loadCheckpointMLN(File rootDir, Checkpoint checkpoint)Load a MultiLayerNetwork for the given checkpoint that resides in the specified root directoryMultiLayerNetworkCheckpointListener. loadCheckpointMLN(Checkpoint checkpoint)Load a MultiLayerNetwork for the given checkpointstatic MultiLayerNetworkCheckpointListener. loadLastCheckpointMLN(File rootDir)Load the last (most recent) checkpoint from the specified root directory -
Uses of MultiLayerNetwork in org.deeplearning4j.util
Methods in org.deeplearning4j.util that return MultiLayerNetwork Modifier and Type Method Description static MultiLayerNetworkModelSerializer. restoreMultiLayerNetwork(@NonNull File file)Load a multi layer network from a filestatic MultiLayerNetworkModelSerializer. restoreMultiLayerNetwork(@NonNull File file, boolean loadUpdater)Load a multi layer network from a filestatic MultiLayerNetworkModelSerializer. restoreMultiLayerNetwork(@NonNull InputStream is)Restore a multi layer network from an input stream
* Note: the input stream is read fully and closed by this method.static MultiLayerNetworkModelSerializer. restoreMultiLayerNetwork(@NonNull InputStream is, boolean loadUpdater)Load a MultiLayerNetwork from InputStream from an input stream
Note: the input stream is read fully and closed by this method.static MultiLayerNetworkModelSerializer. restoreMultiLayerNetwork(@NonNull String path)Load a MultilayerNetwork model from a filestatic MultiLayerNetworkModelSerializer. restoreMultiLayerNetwork(@NonNull String path, boolean loadUpdater)Load a MultilayerNetwork model from a fileMethods in org.deeplearning4j.util that return types with arguments of type MultiLayerNetwork Modifier and Type Method Description static Pair<MultiLayerNetwork,Normalizer>ModelSerializer. restoreMultiLayerNetworkAndNormalizer(@NonNull File file, boolean loadUpdater)Restore a MultiLayerNetwork and Normalizer (if present - null if not) from a Filestatic Pair<MultiLayerNetwork,Normalizer>ModelSerializer. restoreMultiLayerNetworkAndNormalizer(@NonNull InputStream is, boolean loadUpdater)Restore a MultiLayerNetwork and Normalizer (if present - null if not) from the InputStream.Methods in org.deeplearning4j.util with parameters of type MultiLayerNetwork Modifier and Type Method Description static DoubleNetworkUtils. getLearningRate(MultiLayerNetwork net, int layerNumber)Get the current learning rate, for the specified layer, fromthe network.static voidNetworkUtils. setLearningRate(MultiLayerNetwork net, double newLr)Set the learning rate for all layers in the network to the specified value.static voidNetworkUtils. setLearningRate(MultiLayerNetwork net, int layerNumber, double newLr)Set the learning rate for a single layer in the network to the specified value.static voidNetworkUtils. setLearningRate(MultiLayerNetwork net, int layerNumber, ISchedule lrSchedule)Set the learning rate schedule for a single layer in the network to the specified value.
Note also thatNetworkUtils.setLearningRate(MultiLayerNetwork, ISchedule)should also be used in preference, when all layers need to be set to a new LR schedule.
This schedule will replace any/all existing schedules, and also any fixed learning rate values.
Note also that the iteration/epoch counts will not be reset.static voidNetworkUtils. setLearningRate(MultiLayerNetwork net, ISchedule newLrSchedule)Set the learning rate schedule for all layers in the network to the specified schedule.static ComputationGraphNetworkUtils. toComputationGraph(MultiLayerNetwork net)Convert a MultiLayerNetwork to a ComputationGraph
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