Package org.ojalgo.ann
Class WrappedANN
- java.lang.Object
-
- org.ojalgo.ann.WrappedANN
-
- All Implemented Interfaces:
java.util.function.Supplier<ArtificialNeuralNetwork>
- Direct Known Subclasses:
NetworkInvoker
,NetworkTrainer
abstract class WrappedANN extends java.lang.Object implements java.util.function.Supplier<ArtificialNeuralNetwork>
-
-
Field Summary
Fields Modifier and Type Field Description private int
myBatchSize
private PhysicalStore<java.lang.Double>
myInput
private ArtificialNeuralNetwork
myNetwork
private PhysicalStore<java.lang.Double>[]
myOutputs
-
Constructor Summary
Constructors Constructor Description WrappedANN(ArtificialNeuralNetwork network, int batchSize)
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description (package private) void
adjust(int layer, PhysicalStore<java.lang.Double> input, PhysicalStore<java.lang.Double> output, PhysicalStore<java.lang.Double> upstreamGradient, PhysicalStore<java.lang.Double> downstreamGradient)
(package private) int
depth()
boolean
equals(java.lang.Object obj)
ArtificialNeuralNetwork
get()
(package private) ArtificialNeuralNetwork.Activator
getActivator(int layer)
(package private) int
getBatchSize()
(package private) double
getBias(int layer, int output)
(package private) PhysicalStore<java.lang.Double>
getInput()
(package private) PhysicalStore<java.lang.Double>
getInput(int layer)
(package private) PhysicalStore<java.lang.Double>
getOutput()
(package private) PhysicalStore<java.lang.Double>
getOutput(int layer)
(package private) ArtificialNeuralNetwork.Activator
getOutputActivator()
(package private) double
getWeight(int layer, int input, int output)
(package private) java.util.List<MatrixStore<java.lang.Double>>
getWeights()
int
hashCode()
(package private) MatrixStore<java.lang.Double>
invoke(Access1D<java.lang.Double> input, TrainingConfiguration configuration)
DataBatch
newInputBatch()
When usingNetworkTrainer
orNetworkInvoker
with a batch size larger than 1 this utility may help with creating the batches.(package private) DataBatch
newOutputBatch()
(package private) void
randomise()
(package private) void
setActivator(int layer, ArtificialNeuralNetwork.Activator activator)
(package private) void
setBias(int layer, int output, double bias)
private void
setInput(Access1D<java.lang.Double> input)
(package private) void
setWeight(int layer, int input, int output, double weight)
(package private) Structure2D[]
structure()
-
-
-
Field Detail
-
myBatchSize
private final int myBatchSize
-
myInput
private PhysicalStore<java.lang.Double> myInput
-
myNetwork
private final ArtificialNeuralNetwork myNetwork
-
myOutputs
private final PhysicalStore<java.lang.Double>[] myOutputs
-
-
Constructor Detail
-
WrappedANN
WrappedANN(ArtificialNeuralNetwork network, int batchSize)
-
-
Method Detail
-
equals
public boolean equals(java.lang.Object obj)
- Overrides:
equals
in classjava.lang.Object
-
get
public ArtificialNeuralNetwork get()
- Specified by:
get
in interfacejava.util.function.Supplier<ArtificialNeuralNetwork>
-
hashCode
public int hashCode()
- Overrides:
hashCode
in classjava.lang.Object
-
newInputBatch
public DataBatch newInputBatch()
When usingNetworkTrainer
orNetworkInvoker
with a batch size larger than 1 this utility may help with creating the batches.
-
setInput
private void setInput(Access1D<java.lang.Double> input)
-
adjust
void adjust(int layer, PhysicalStore<java.lang.Double> input, PhysicalStore<java.lang.Double> output, PhysicalStore<java.lang.Double> upstreamGradient, PhysicalStore<java.lang.Double> downstreamGradient)
-
depth
int depth()
-
getActivator
ArtificialNeuralNetwork.Activator getActivator(int layer)
-
getBatchSize
int getBatchSize()
-
getBias
double getBias(int layer, int output)
-
getInput
PhysicalStore<java.lang.Double> getInput()
-
getInput
PhysicalStore<java.lang.Double> getInput(int layer)
-
getOutput
PhysicalStore<java.lang.Double> getOutput()
-
getOutput
PhysicalStore<java.lang.Double> getOutput(int layer)
-
getOutputActivator
ArtificialNeuralNetwork.Activator getOutputActivator()
-
getWeight
double getWeight(int layer, int input, int output)
-
getWeights
java.util.List<MatrixStore<java.lang.Double>> getWeights()
-
invoke
MatrixStore<java.lang.Double> invoke(Access1D<java.lang.Double> input, TrainingConfiguration configuration)
-
newOutputBatch
DataBatch newOutputBatch()
-
randomise
void randomise()
-
setActivator
void setActivator(int layer, ArtificialNeuralNetwork.Activator activator)
-
setBias
void setBias(int layer, int output, double bias)
-
setWeight
void setWeight(int layer, int input, int output, double weight)
-
structure
Structure2D[] structure()
-
-