org.deeplearning4j.nn.params

Class GravesLSTMParamInitializer

java.lang.Object

org.deeplearning4j.nn.params.GravesLSTMParamInitializer

All Implemented Interfaces:

ParamInitializer

public class GravesLSTMParamInitializer
extends Object
implements ParamInitializer

LSTM Parameter initializer, for LSTM based on Graves: Supervised Sequence Labelling with Recurrent Neural Networks http://www.cs.toronto.edu/~graves/phd.pdf

Field Summary

Fields

Modifier and Type	Field and Description
static String	BIAS_KEY
static String	INPUT_WEIGHT_KEY
static String	RECURRENT_WEIGHT_KEY Weights for previous time step -> current time step connections

Constructor Summary

Constructors

Constructor and Description
GravesLSTMParamInitializer()

Method Summary

Modifier and Type	Method and Description
List<String>	biasKeys(Layer layer) Bias parameter keys given the layer configuration
Map<String,INDArray>	getGradientsFromFlattened(NeuralNetConfiguration conf, INDArray gradientView) Return a map of gradients (in their standard non-flattened representation), taken from the flattened (row vector) gradientView array.
static GravesLSTMParamInitializer	getInstance()
Map<String,INDArray>	init(NeuralNetConfiguration conf, INDArray paramsView, boolean initializeParams) Initialize the parameters
boolean	isBiasParam(Layer layer, String key) Is the specified parameter a bias?
boolean	isWeightParam(Layer layer, String key) Is the specified parameter a weight?
long	numParams(Layer l)
long	numParams(NeuralNetConfiguration conf)
List<String>	paramKeys(Layer layer) Get a list of all parameter keys given the layer configuration
List<String>	weightKeys(Layer layer) Weight parameter keys given the layer configuration

Methods inherited from class java.lang.Object

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

Field Detail

RECURRENT_WEIGHT_KEY

public static final String RECURRENT_WEIGHT_KEY

Weights for previous time step -> current time step connections

See Also:

Constant Field Values

BIAS_KEY

public static final String BIAS_KEY

See Also:

Constant Field Values

INPUT_WEIGHT_KEY

public static final String INPUT_WEIGHT_KEY

See Also:

Constant Field Values

Constructor Detail

GravesLSTMParamInitializer

public GravesLSTMParamInitializer()

Method Detail

getInstance

public static GravesLSTMParamInitializer getInstance()

numParams

public long numParams(NeuralNetConfiguration conf)

Specified by:

numParams in interface ParamInitializer

numParams

public long numParams(Layer l)

Specified by:

numParams in interface ParamInitializer

paramKeys

public List<String> paramKeys(Layer layer)

Description copied from interface: ParamInitializer

Get a list of all parameter keys given the layer configuration

Specified by:

paramKeys in interface ParamInitializer

Parameters:

layer - Layer

Returns:

All parameter keys

weightKeys

public List<String> weightKeys(Layer layer)

Description copied from interface: ParamInitializer

Weight parameter keys given the layer configuration

Specified by:

weightKeys in interface ParamInitializer

Parameters:

layer - Layer

Returns:

Weight parameter keys

biasKeys

public List<String> biasKeys(Layer layer)

Description copied from interface: ParamInitializer

Bias parameter keys given the layer configuration

Specified by:

biasKeys in interface ParamInitializer

Parameters:

layer - Layer

Returns:

Bias parameter keys

isWeightParam

public boolean isWeightParam(Layer layer,
                             String key)

Description copied from interface: ParamInitializer

Is the specified parameter a weight?

Specified by:

isWeightParam in interface ParamInitializer

Parameters:

layer - Layer

key - Key to check

Returns:

True if parameter is a weight

isBiasParam

public boolean isBiasParam(Layer layer,
                           String key)

Description copied from interface: ParamInitializer

Is the specified parameter a bias?

Specified by:

isBiasParam in interface ParamInitializer

Parameters:

layer - Layer

key - Key to check

Returns:

True if parameter is a bias

init

public Map<String,INDArray> init(NeuralNetConfiguration conf,
                                 INDArray paramsView,
                                 boolean initializeParams)

Description copied from interface: ParamInitializer

Initialize the parameters

Specified by:

init in interface ParamInitializer

Parameters:

conf - the configuration

paramsView - a view of the full network (backprop) parameters

initializeParams - if true: initialize the parameters according to the configuration. If false: don't modify the values in the paramsView array (but do select out the appropriate subset, reshape etc as required)

Returns:

Map of parameters keyed by type (view of the 'paramsView' array)

getGradientsFromFlattened

public Map<String,INDArray> getGradientsFromFlattened(NeuralNetConfiguration conf,
                                                      INDArray gradientView)

Description copied from interface: ParamInitializer

Return a map of gradients (in their standard non-flattened representation), taken from the flattened (row vector) gradientView array. The idea is that operates in exactly the same way as the paramsView does in #init(Map, NeuralNetConfiguration, INDArray); thus the position in the view (and, the array orders) must match those of the parameters

Specified by:

getGradientsFromFlattened in interface ParamInitializer

Parameters:

conf - Configuration

gradientView - The flattened gradients array, as a view of the larger array

Returns:

A map containing an array by parameter type, that is a view of the full network gradients array