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 MultiLayerNetwork
LocalFileModelSaver. getBestModel()
MultiLayerNetwork
LocalFileModelSaver. getLatestModel()
Methods in org.deeplearning4j.earlystopping.saver with parameters of type MultiLayerNetwork Modifier and Type Method Description void
LocalFileModelSaver. saveBestModel(MultiLayerNetwork net, double score)
void
LocalFileModelSaver. saveLatestModel(MultiLayerNetwork net, double score)
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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 INDArray
BaseMLNScoreCalculator. output(MultiLayerNetwork network, INDArray input, INDArray fMask, INDArray lMask)
protected double
BaseMLNScoreCalculator. scoreMinibatch(MultiLayerNetwork network, INDArray[] features, INDArray[] labels, INDArray[] fMask, INDArray[] lMask, INDArray[] output)
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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)
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Uses of MultiLayerNetwork in org.deeplearning4j.gradientcheck
Methods in org.deeplearning4j.gradientcheck with parameters of type MultiLayerNetwork Modifier and Type Method Description static boolean
GradientCheckUtil. checkGradients(MultiLayerNetwork mln, double epsilon, double maxRelError, double minAbsoluteError, boolean print, boolean exitOnFirstError, INDArray input, INDArray labels)
Deprecated.static boolean
GradientCheckUtil. 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)
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Uses of MultiLayerNetwork in org.deeplearning4j.nn.multilayer
Methods in org.deeplearning4j.nn.multilayer that return MultiLayerNetwork Modifier and Type Method Description MultiLayerNetwork
MultiLayerNetwork. clone()
Clone the MultiLayerNetworkMultiLayerNetwork
MultiLayerNetwork. 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 MultiLayerNetwork
MultiLayerNetwork. load(File f, boolean loadUpdater)
Restore a MultiLayerNetwork to a file, saved usingsave(File)
orModelSerializer
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Uses of MultiLayerNetwork in org.deeplearning4j.nn.transferlearning
Methods in org.deeplearning4j.nn.transferlearning that return MultiLayerNetwork Modifier and Type Method Description MultiLayerNetwork
TransferLearning.Builder. build()
Returns a model with the fine tune configuration and specified architecture changes.MultiLayerNetwork
TransferLearningHelper. 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)
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Uses of MultiLayerNetwork in org.deeplearning4j.optimize.listeners
Methods in org.deeplearning4j.optimize.listeners that return MultiLayerNetwork Modifier and Type Method Description MultiLayerNetwork
CheckpointListener. loadCheckpointMLN(int checkpointNum)
Load a MultiLayerNetwork for the given checkpoint numberstatic MultiLayerNetwork
CheckpointListener. loadCheckpointMLN(File rootDir, int checkpointNum)
Load a MultiLayerNetwork for the given checkpoint numberstatic MultiLayerNetwork
CheckpointListener. loadCheckpointMLN(File rootDir, Checkpoint checkpoint)
Load a MultiLayerNetwork for the given checkpoint that resides in the specified root directoryMultiLayerNetwork
CheckpointListener. loadCheckpointMLN(Checkpoint checkpoint)
Load a MultiLayerNetwork for the given checkpointstatic MultiLayerNetwork
CheckpointListener. 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 MultiLayerNetwork
ModelSerializer. restoreMultiLayerNetwork(@NonNull File file)
Load a multi layer network from a filestatic MultiLayerNetwork
ModelSerializer. restoreMultiLayerNetwork(@NonNull File file, boolean loadUpdater)
Load a multi layer network from a filestatic MultiLayerNetwork
ModelSerializer. 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 MultiLayerNetwork
ModelSerializer. 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 MultiLayerNetwork
ModelSerializer. restoreMultiLayerNetwork(@NonNull String path)
Load a MultilayerNetwork model from a filestatic MultiLayerNetwork
ModelSerializer. 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 Double
NetworkUtils. getLearningRate(MultiLayerNetwork net, int layerNumber)
Get the current learning rate, for the specified layer, fromthe network.static void
NetworkUtils. setLearningRate(MultiLayerNetwork net, double newLr)
Set the learning rate for all layers in the network to the specified value.static void
NetworkUtils. setLearningRate(MultiLayerNetwork net, int layerNumber, double newLr)
Set the learning rate for a single layer in the network to the specified value.static void
NetworkUtils. 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 void
NetworkUtils. setLearningRate(MultiLayerNetwork net, ISchedule newLrSchedule)
Set the learning rate schedule for all layers in the network to the specified schedule.static ComputationGraph
NetworkUtils. toComputationGraph(MultiLayerNetwork net)
Convert a MultiLayerNetwork to a ComputationGraph
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