| Modifier and Type | Method and Description |
|---|---|
MultiLayerNetwork |
LocalFileModelSaver.getBestModel() |
MultiLayerNetwork |
LocalFileModelSaver.getLatestModel() |
| Modifier and Type | Method and Description |
|---|---|
void |
LocalFileModelSaver.saveBestModel(MultiLayerNetwork net,
double score) |
void |
LocalFileModelSaver.saveLatestModel(MultiLayerNetwork net,
double score) |
| Modifier and Type | Method and 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) |
| Constructor and Description |
|---|
EarlyStoppingTrainer(EarlyStoppingConfiguration<MultiLayerNetwork> esConfig,
MultiLayerNetwork net,
DataSetIterator train) |
EarlyStoppingTrainer(EarlyStoppingConfiguration<MultiLayerNetwork> esConfig,
MultiLayerNetwork net,
DataSetIterator train,
EarlyStoppingListener<MultiLayerNetwork> listener) |
| Constructor and 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) |
| Modifier and Type | Method and Description |
|---|---|
static boolean |
GradientCheckUtil.checkGradients(MultiLayerNetwork mln,
double epsilon,
double maxRelError,
double minAbsoluteError,
boolean print,
boolean exitOnFirstError,
INDArray input,
INDArray labels)
Check backprop gradients for a MultiLayerNetwork.
|
static boolean |
GradientCheckUtil.checkGradients(MultiLayerNetwork mln,
double epsilon,
double maxRelError,
double minAbsoluteError,
boolean print,
boolean exitOnFirstError,
INDArray input,
INDArray labels,
INDArray inputMask,
INDArray labelMask) |
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) |
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) |
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,
Consumer<MultiLayerNetwork> callEachIter) |
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) |
static boolean |
GradientCheckUtil.checkGradients(MultiLayerNetwork mln,
double epsilon,
double maxRelError,
double minAbsoluteError,
boolean print,
boolean exitOnFirstError,
INDArray input,
INDArray labels,
Set<String> excludeParams) |
| Modifier and Type | Method and Description |
|---|---|
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,
Consumer<MultiLayerNetwork> callEachIter) |
| Modifier and Type | Method and Description |
|---|---|
MultiLayerNetwork |
MultiLayerNetwork.clone()
Clone the MultiLayerNetwork
|
MultiLayerNetwork |
MultiLayerNetwork.convertDataType(org.nd4j.linalg.api.buffer.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 using
save(File) or ModelSerializer |
| Modifier and Type | Method and 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 updated
|
| Constructor and Description |
|---|
Builder(MultiLayerNetwork origModel)
Multilayer Network to tweak for transfer learning
|
TransferLearningHelper(MultiLayerNetwork orig)
Expects a MLN where some layers are frozen
|
TransferLearningHelper(MultiLayerNetwork orig,
int frozenTill)
Will modify the given MLN (in place!) to freeze layers (hold params constant during training) specified and below
|
| Constructor and Description |
|---|
MultiLayerUpdater(MultiLayerNetwork network) |
MultiLayerUpdater(MultiLayerNetwork network,
INDArray updaterState) |
| Modifier and Type | Method and Description |
|---|---|
MultiLayerNetwork |
CheckpointListener.loadCheckpointMLN(Checkpoint checkpoint)
Load a MultiLayerNetwork for the given checkpoint
|
static MultiLayerNetwork |
CheckpointListener.loadCheckpointMLN(File rootDir,
Checkpoint checkpoint)
Load a MultiLayerNetwork for the given checkpoint that resides in the specified root directory
|
static MultiLayerNetwork |
CheckpointListener.loadCheckpointMLN(File rootDir,
int checkpointNum)
Load a MultiLayerNetwork for the given checkpoint number
|
MultiLayerNetwork |
CheckpointListener.loadCheckpointMLN(int checkpointNum)
Load a MultiLayerNetwork for the given checkpoint number
|
static MultiLayerNetwork |
CheckpointListener.loadLastCheckpointMLN(File rootDir)
Load the last (most recent) checkpoint from the specified root directory
|
| Modifier and Type | Method and Description |
|---|---|
static MultiLayerNetwork |
ModelSerializer.restoreMultiLayerNetwork(File file)
Load a multi layer network from a file
|
static MultiLayerNetwork |
ModelSerializer.restoreMultiLayerNetwork(File file,
boolean loadUpdater)
Load a multi layer network from a file
|
static MultiLayerNetwork |
ModelSerializer.restoreMultiLayerNetwork(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(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(String path)
Load a MultilayerNetwork model from a file
|
static MultiLayerNetwork |
ModelSerializer.restoreMultiLayerNetwork(String path,
boolean loadUpdater)
Load a MultilayerNetwork model from a file
|
| Modifier and Type | Method and Description |
|---|---|
static Pair<MultiLayerNetwork,Normalizer> |
ModelSerializer.restoreMultiLayerNetworkAndNormalizer(File file,
boolean loadUpdater)
Restore a MultiLayerNetwork and Normalizer (if present - null if not) from a File
|
static Pair<MultiLayerNetwork,Normalizer> |
ModelSerializer.restoreMultiLayerNetworkAndNormalizer(InputStream is,
boolean loadUpdater)
Restore a MultiLayerNetwork and Normalizer (if present - null if not) from the InputStream.
|
| Modifier and Type | Method and 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 that NetworkUtils.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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