NetArrayLayer

represents a layer that has no input and produces as output a constant array.

includes options for the initial value of the array or output size.

Details and Options

NetArrayLayer is typically used in a NetGraph and allows a learned array to be used as an ordinary input to other layers. Without NetArrayLayer, all layer inputs must ultimately be derived from inputs to the entire net.
The array stored by NetArrayLayer will be learned during training.
The constant array stored in NetArrayLayer has the same dimensions as the output of NetArrayLayer.
NetArrayLayer["Array"->array] can be used to give an explicit value of the constant array.
When the constant array is not explicitly specified or is given as Automatic, it is added automatically when NetInitialize or NetTrain is used.
NetArrayLayer["Output"->{d₁,d₂,…}] can be used to fix the output size of the layer, which also fixes the size of the constant array.
The following training parameter can also be included:
LearningRateMultipliers Automatic learning rate multipliers for the array
NetArrayLayer[…][] returns the constant array.
The constant array can also be obtained from an initialized NetArrayLayer using NetExtract[layer,"Array"].
Options[NetArrayLayer] gives the list of default options to construct the layer. Options[NetArrayLayer[…]] gives the list of default options to evaluate the layer on some data.
Information[NetArrayLayer[…]] gives a report about the layer.
Information[NetArrayLayer[…],prop] gives the value of the property prop of NetArrayLayer[…]. Possible properties are the same as for NetGraph.
Neural Networks in the Wolfram Language

Create an initialized NetArrayLayer with output dimensions specified:

Extract the initialized array:

Create a NetArrayLayer with a specific initial value for the array:

Embed the layer in a graph that raises the input to a power of the array elementwise:

NetArrayLayer cannot accept symbolic arrays:

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