org.encog.engine.opencl.kernels
Class KernelNetworkCalc

java.lang.Object
  org.encog.engine.opencl.kernels.EncogKernel
      org.encog.engine.opencl.kernels.KernelNetworkCalc

public class KernelNetworkCalc
extends EncogKernel

An OpenCL kernel that is designed to calculate the output of a neural network.

Field Summary

static int	PARRAY_INPUT_COUNT The input count.
static int	PARRAY_ITEMS_PER Items to train per call.
static int	PARRAY_ITERATIONS Items to train per call.
static int	PARRAY_LAYER_COUNT The layer count.
static int	PARRAY_LEARN Are we learning? 0=no, 1 =yes.
static int	PARRAY_OUTPUT_COUNT The output count.
static int	PARRAY_START What is the starting index to train at.

Constructor Summary

KernelNetworkCalc(EncogCLDevice device)
Construct a kernel to train the network.

Method Summary

void	calculate(int start, int size) Calculate one iteration over the specified range.
void	compile(FlatNetwork network) Compile the kernel.
double	getError()
float[]	getErrors()
FlatNetwork	getFlat()
EngineIndexableSet	getTraining()
void	release() Release the kernel and all buffers.
void	setFlat(FlatNetwork flat)
void	setTraining(EngineIndexableSet training)

Methods inherited from class org.encog.engine.opencl.kernels.EncogKernel

compile, compile, createArrayReadOnly, createArrayReadOnly, createFloatArrayWriteOnly, getCLSource, getContext, getDevice, getGlobalWork, getKernel, getLocalWork, getMaxWorkGroupSize, getProgram, getSourceName, getWorkGroupLong, prepareKernel, releaseBuffer, setArg, setCLSource, setGlobalWork, setLocalWork

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

PARRAY_INPUT_COUNT

public static final int PARRAY_INPUT_COUNT

The input count.

See Also:

Constant Field Values

PARRAY_OUTPUT_COUNT

public static final int PARRAY_OUTPUT_COUNT

The output count.

See Also:

Constant Field Values

PARRAY_LAYER_COUNT

public static final int PARRAY_LAYER_COUNT

The layer count.

See Also:

Constant Field Values

PARRAY_LEARN

public static final int PARRAY_LEARN

Are we learning? 0=no, 1 =yes.

See Also:

Constant Field Values

PARRAY_START

public static final int PARRAY_START

What is the starting index to train at.

See Also:

Constant Field Values

PARRAY_ITEMS_PER

public static final int PARRAY_ITEMS_PER

Items to train per call.

See Also:

Constant Field Values

PARRAY_ITERATIONS

public static final int PARRAY_ITERATIONS

Items to train per call.

See Also:

Constant Field Values

Constructor Detail

KernelNetworkCalc

public KernelNetworkCalc(EncogCLDevice device)

Construct a kernel to train the network.

Parameters:

device - The OpenCL device to use.

flat - The network to train.

training - The training data.

tempDataSize - How much temp data.

Method Detail

calculate

public void calculate(int start,
                      int size)

Calculate one iteration over the specified range.

Parameters:

start - The starting position to calculate for.

size - The ending position to calculate for.

iterations - The number of iterations to execute.

learn - True, if we should learn.

compile

public void compile(FlatNetwork network)

Compile the kernel.

Parameters:

options - The options.

profile - The OpenCL training profile.

network - The network to compile for.

getErrors

public float[] getErrors()

Returns:

the errors

release

public void release()

Release the kernel and all buffers.

Overrides:

release in class EncogKernel

getFlat

public FlatNetwork getFlat()

setFlat

public void setFlat(FlatNetwork flat)

getTraining

public EngineIndexableSet getTraining()

setTraining

public void setTraining(EngineIndexableSet training)

getError

public double getError()

Returns:

The error from the last evaluation.