AggregationLayer

AggregationLayer[f]

represents a layer that aggregates a tensor of arbitrary rank into a vector, using the function f.

Details and Options

  • AggregationLayer[f] operates on a tensor of size d1×…×dn to produce a vector of size d1, effectively applying the function f to the elements of each subtensor of size d2×…×dn.
  • Possible values for f are Mean, Min, Max and Total.
  • AggregationLayer[…][input] explicitly computes the output from applying the layer.
  • AggregationLayer[…][{input1,input2,…}] explicitly computes outputs for each of the inputi.
  • AggregationLayer is typically used inside NetChain, NetGraph, etc. as the final stage in a chain of convolutions, poolings, etc. to convert a tensor with spatial dimensions into a fixed-size vector representation.
  • AggregationLayer exposes the following ports for use in NetGraph etc.:
  • "Input"a tensor of rank 2 or greater
    "Output"a vector
  • When it cannot be inferred from other layers in a larger net, the option "Input"{d1,…,dn} can be used to fix the input of AggregationLayer to be a tensor of dimensions d1×…×dn.

Examples

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Basic Examples  (2)

Create an AggregationLayer using Max as the aggregation function:

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Create an AggregationLayer using Total as the aggregation function:

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Apply the layer to a matrix:

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Scope  (2)

Possible Issues  (1)

See Also

TotalLayer  PoolingLayer  SummationLayer  NetChain  NetGraph  NetTrain

Introduced in 2017
(11.1)