org.apache.spark.ml.ann

Interface Layer

All Superinterfaces:

java.io.Serializable

public interface Layer
extends scala.Serializable

Trait that holds Layer properties, that are needed to instantiate it. Implements Layer instantiation.

Method Summary

Modifier and Type	Method and Description
LayerModel	createModel(breeze.linalg.DenseVector<Object> initialWeights) Returns the instance of the layer based on weights provided.
int	getOutputSize(int inputSize) Returns the output size given the input size (not counting the stack size).
LayerModel	initModel(breeze.linalg.DenseVector<Object> weights, java.util.Random random) Returns the instance of the layer with random generated weights.
boolean	inPlace() If true, the memory is not allocated for the output of this layer.
int	weightSize() Number of weights that is used to allocate memory for the weights vector

Method Detail

createModel

LayerModel createModel(breeze.linalg.DenseVector<Object> initialWeights)

Returns the instance of the layer based on weights provided. Size of weights must be equal to weightSize

Parameters:

initialWeights - vector with layer weights

Returns:

the layer model

getOutputSize

int getOutputSize(int inputSize)

Returns the output size given the input size (not counting the stack size). Output size is used to allocate memory for the output.

Parameters:

inputSize - input size

Returns:

output size

inPlace

boolean inPlace()

If true, the memory is not allocated for the output of this layer. The memory allocated to the previous layer is used to write the output of this layer. Developer can set this to true if computing delta of a previous layer does not involve its output, so the current layer can write there. This also mean that both layers have the same number of outputs.

Returns:

(undocumented)

initModel

LayerModel initModel(breeze.linalg.DenseVector<Object> weights,
                     java.util.Random random)

Returns the instance of the layer with random generated weights.

Parameters:

weights - vector for weights initialization, must be equal to weightSize

random - random number generator

Returns:

the layer model

weightSize

int weightSize()

Number of weights that is used to allocate memory for the weights vector

Returns:

(undocumented)