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.
An InputVertex simply defines the location (and connection structure) of inputs to the ComputationGraph.
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.
A custom layer for removing 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.
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.
UnstackVertex allows for unstacking of inputs so that they may be forwarded through a network.
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