Package org.deeplearning4j.nn.graph.vertex.impl

Class Summary

Class	Description
ElementWiseVertex	An ElementWiseVertex is used to combine the activations of two or more layer in an element-wise manner For example, the activations may be combined by addition, subtraction or multiplication.
InputVertex	An InputVertex simply defines the location (and connection structure) of inputs to the ComputationGraph.
LayerVertex	LayerVertex is a GraphVertex with a neural network Layer (and, optionally an InputPreProcessor) in it
MergeVertex	A MergeVertex is used to combine the activations of two or more layers/GraphVertex by means of concatenation/merging. Exactly how this is done depends on the type of input. For 2d (feed forward layer) inputs: MergeVertex([numExamples,layerSize1],[numExamples,layerSize2]) -> [numExamples,layerSize1 + layerSize2] For 3d (time series) inputs: MergeVertex([numExamples,layerSize1,timeSeriesLength],[numExamples,layerSize2,timeSeriesLength]) -> [numExamples,layerSize1 + layerSize2,timeSeriesLength] For 4d (convolutional) inputs: MergeVertex([numExamples,depth1,width,height],[numExamples,depth2,width,height]) -> [numExamples,depth1 + depth2,width,height]
PreprocessorVertex	PreprocessorVertex is a simple adaptor class that allows a InputPreProcessor to be used in a ComputationGraph GraphVertex, without it being associated with a layer.
SubsetVertex	SubsetVertex is used to select a subset of the activations out of another GraphVertex. For example, a subset of the activations out of a layer. Note that this subset is specifying by means of an interval of the original activations.

Enum Summary

Enum	Description
ElementWiseVertex.Op