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 or by selecting the maximum.
FrozenVertex is used for the purposes of transfer learning A frozen layers wraps another DL4J GraphVertex within it.
A GraphVertex is a vertex in the computation graph.
L2NormalizeVertex performs L2 normalization on a single input.
L2Vertex calculates the L2 least squares error of two inputs.
LayerVertex is a GraphVertex with a neural network Layer (and, optionally an
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]
Removes the first column and row from an input.
PreprocessorVertex is a simple adaptor class that allows a
Adds the ability to reshape and flatten the tensor in the computation graph.
NOTE: This class should only be used if you know exactly what you are doing with reshaping activations.
A ScaleVertex is used to scale the size of activations of a single layer
For example, ResNet activations can be scaled in repeating blocks to keep variance under control.
A ShiftVertex is used to shift the activations of a single layer
One could use it to add a bias or as part of some other calculation.
StackVertex allows for stacking of inputs so that they may be forwarded through a network.
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.
UnstackVertex allows for unstacking of inputs so that they may be forwarded through a network.