Uses of Class
org.deeplearning4j.nn.conf.CacheMode

Packages that use CacheMode

Package	Description
org.deeplearning4j.nn.api
org.deeplearning4j.nn.conf
org.deeplearning4j.nn.conf.memory
org.deeplearning4j.nn.graph
org.deeplearning4j.nn.layers
org.deeplearning4j.nn.layers.recurrent
org.deeplearning4j.nn.layers.variational
org.deeplearning4j.nn.layers.wrapper
org.deeplearning4j.nn.multilayer

Uses of CacheMode in org.deeplearning4j.nn.api

Methods in org.deeplearning4j.nn.api with parameters of type CacheMode

Modifier and Type	Method	Description
void	Layer.setCacheMode(CacheMode mode)	This method sets given CacheMode for current layer

Uses of CacheMode in org.deeplearning4j.nn.conf

Fields in org.deeplearning4j.nn.conf declared as CacheMode

Modifier and Type	Field	Description
protected CacheMode	ComputationGraphConfiguration.cacheMode
protected CacheMode	MultiLayerConfiguration.Builder.cacheMode
protected CacheMode	MultiLayerConfiguration.cacheMode
protected CacheMode	NeuralNetConfiguration.Builder.cacheMode
protected CacheMode	NeuralNetConfiguration.cacheMode

Methods in org.deeplearning4j.nn.conf that return CacheMode

Modifier and Type	Method	Description
static CacheMode	CacheMode.valueOf(String name)	Returns the enum constant of this type with the specified name.
static CacheMode[]	CacheMode.values()	Returns an array containing the constants of this enum type, in the order they are declared.

Methods in org.deeplearning4j.nn.conf with parameters of type CacheMode

Modifier and Type	Method	Description
MultiLayerConfiguration.Builder	MultiLayerConfiguration.Builder.cacheMode(@NonNull CacheMode cacheMode)	This method defines how/if preOutput cache is handled: NONE: cache disabled (default value) HOST: Host memory will be used DEVICE: GPU memory will be used (on CPU backends effect will be the same as for HOST)
NeuralNetConfiguration.Builder	NeuralNetConfiguration.Builder.cacheMode(@NonNull CacheMode cacheMode)	This method defines how/if preOutput cache is handled: NONE: cache disabled (default value) HOST: Host memory will be used DEVICE: GPU memory will be used (on CPU backends effect will be the same as for HOST)
NeuralNetConfiguration.ListBuilder	NeuralNetConfiguration.ListBuilder.cacheMode(@NonNull CacheMode cacheMode)

Uses of CacheMode in org.deeplearning4j.nn.conf.memory

Fields in org.deeplearning4j.nn.conf.memory with type parameters of type CacheMode

Modifier and Type	Field	Description
static Map<CacheMode,Long>	MemoryReport.CACHE_MODE_ALL_ZEROS	A simple Map containing all zeros for each CacheMode key

Methods in org.deeplearning4j.nn.conf.memory that return types with arguments of type CacheMode

Modifier and Type	Method	Description
static Map<CacheMode,Long>	MemoryReport.cacheModeMapFor(long value)	Get a map of CacheMode with all keys associated with the specified value

Methods in org.deeplearning4j.nn.conf.memory with parameters of type CacheMode

Modifier and Type	Method	Description
long	LayerMemoryReport.getMemoryBytes(MemoryType memoryType, int minibatchSize, MemoryUseMode memoryUseMode, CacheMode cacheMode, DataType dataType)
long	MemoryReport.getMemoryBytes(MemoryType memoryType, int minibatchSize, MemoryUseMode memoryUseMode, CacheMode cacheMode)	Get the memory estimate (in bytes) for the specified type of memory, using the current ND4J data type
abstract long	MemoryReport.getMemoryBytes(MemoryType memoryType, int minibatchSize, MemoryUseMode memoryUseMode, CacheMode cacheMode, DataType dataType)	Get the memory estimate (in bytes) for the specified type of memory
long	NetworkMemoryReport.getMemoryBytes(MemoryType memoryType, int minibatchSize, MemoryUseMode memoryUseMode, CacheMode cacheMode, DataType dataType)
long	LayerMemoryReport.getTotalMemoryBytes(int minibatchSize, @NonNull MemoryUseMode memoryUseMode, @NonNull CacheMode cacheMode, @NonNull DataType dataType)
long	MemoryReport.getTotalMemoryBytes(int minibatchSize, @NonNull MemoryUseMode memoryUseMode, @NonNull CacheMode cacheMode)	Get the total memory use in bytes for the given configuration (using the current ND4J data type)
abstract long	MemoryReport.getTotalMemoryBytes(int minibatchSize, @NonNull MemoryUseMode memoryUseMode, @NonNull CacheMode cacheMode, @NonNull DataType dataType)	Get the total memory use in bytes for the given configuration
long	NetworkMemoryReport.getTotalMemoryBytes(int minibatchSize, @NonNull MemoryUseMode memoryUseMode, @NonNull CacheMode cacheMode, @NonNull DataType dataType)

Method parameters in org.deeplearning4j.nn.conf.memory with type arguments of type CacheMode

Modifier and Type	Method	Description
LayerMemoryReport.Builder	LayerMemoryReport.Builder.cacheMemory(Map<CacheMode,Long> cacheModeMemoryFixed, Map<CacheMode,Long> cacheModeMemoryVariablePerEx)	Reports the cached/cacheable memory requirements.
LayerMemoryReport.Builder	LayerMemoryReport.Builder.workingMemory(long fixedInference, long variableInferencePerEx, Map<CacheMode,Long> fixedTrain, Map<CacheMode,Long> variableTrainPerEx)	Report the working memory requirements, for both inference and training.

Uses of CacheMode in org.deeplearning4j.nn.graph

Methods in org.deeplearning4j.nn.graph with parameters of type CacheMode

Modifier and Type	Method	Description
void	ComputationGraph.setCacheMode(CacheMode mode)	This method sets specified CacheMode for all layers within network

Uses of CacheMode in org.deeplearning4j.nn.layers

Fields in org.deeplearning4j.nn.layers declared as CacheMode

Modifier and Type	Field	Description
protected CacheMode	AbstractLayer.cacheMode

Methods in org.deeplearning4j.nn.layers with parameters of type CacheMode

Modifier and Type	Method	Description
void	AbstractLayer.setCacheMode(CacheMode mode)
void	FrozenLayer.setCacheMode(CacheMode mode)

Uses of CacheMode in org.deeplearning4j.nn.layers.recurrent

Methods in org.deeplearning4j.nn.layers.recurrent with parameters of type CacheMode

Modifier and Type	Method	Description
static FwdPassReturn	LSTMHelpers.activateHelper(BaseRecurrentLayer layer, NeuralNetConfiguration conf, IActivation gateActivationFn, INDArray input, INDArray recurrentWeights, INDArray originalInputWeights, INDArray biases, boolean training, INDArray originalPrevOutputActivations, INDArray originalPrevMemCellState, boolean forBackprop, boolean forwards, String inputWeightKey, INDArray maskArray, boolean hasPeepholeConnections, LSTMHelper helper, CacheMode cacheMode, LayerWorkspaceMgr workspaceMgr, boolean isHelperAllowFallback)	Returns FwdPassReturn object with activations/INDArrays.
void	BidirectionalLayer.setCacheMode(CacheMode mode)

Uses of CacheMode in org.deeplearning4j.nn.layers.variational

Fields in org.deeplearning4j.nn.layers.variational declared as CacheMode

Modifier and Type	Field	Description
protected CacheMode	VariationalAutoencoder.cacheMode

Methods in org.deeplearning4j.nn.layers.variational with parameters of type CacheMode

Modifier and Type	Method	Description
void	VariationalAutoencoder.setCacheMode(CacheMode mode)

Uses of CacheMode in org.deeplearning4j.nn.layers.wrapper

Methods in org.deeplearning4j.nn.layers.wrapper with parameters of type CacheMode

Modifier and Type	Method	Description
void	BaseWrapperLayer.setCacheMode(CacheMode mode)

Uses of CacheMode in org.deeplearning4j.nn.multilayer

Methods in org.deeplearning4j.nn.multilayer with parameters of type CacheMode

Modifier and Type	Method	Description
void	MultiLayerNetwork.setCacheMode(CacheMode mode)	This method sets specified CacheMode for all layers within network