NetNestOperator

represents a net in which net is applied n times to the input.

Details and Options

[net,n] accepts a single input array s₀ and produces an output array s_n, computed by applying net repeatedly to s_i-1 to compute s_i.
In NetNestOperator[net,n], net should take exactly one input and produce exactly one output. The input and output must be of the same dimensions.
NetNestOperator exposes the following ports for use in NetGraph etc.:
"Input" the initial state s₀

"Output" the final state s_n
If net contains trainable parameters, the same parameters are used for every application of net to the input.
If net has no trainable parameters, NetNestOperator[net,n] is equivalent to a NetChain containing n copies of net.
The following training parameter can be included:
LearningRateMultipliers Automatic learning rate multipliers for trainable arrays in the net
NetExtract allows access to the forward and reverse nets via "Net".
Options[NetNestOperator] gives the list of default options to construct the operator. Options[NetNestOperator[…]] gives the list of default options to evaluate the operator on some data.
Information[NetNestOperator[…]] gives a report about the operator.
Information[NetNestOperator[…],prop] gives the value of the property prop of NetNestOperator[…]. Possible properties are the same as for NetGraph.

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Create a net that applies a LinearLayer 10 times:

Randomly initialize the net and apply it to an input:

Distort an image by nesting convolutions and poolings. First, create a chain that applies a convolution, pooling and a nonlinearity:

Create a net the applies the chain 30 times:

Randomly initialize the net and apply it to a test image:

Create a gallery of the results from different random initializations:

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	"Input"	the initial state s₀
	"Output"	the final state s_n