Static Neural Network Parameters

We can also allocate neural network parameters using StaticArrays. Therefore we simply need to set the keyword static to true in the NeuralNetwork constructor.

using AbstractNeuralNetworks
import Random
Random.seed!(123)

backend = AbstractNeuralNetworks.CPUStatic()
input_dim = 2
n_hidden_layers = 100
c = Chain(Dense(input_dim, 10, tanh), Tuple(Dense(10, 10, tanh) for _ in 1:n_hidden_layers)..., Dense(10, 1, tanh))
nn = NeuralNetwork(c, backend)
typeof(params(nn).L1.W)

MMatrix{10, 2, Float64, 20} (alias for StaticArraysCore.MArray{Tuple{10, 2}, Float64, 2, 20})

We can compare different evaluation times:

nn_cpu = changebackend(CPU(), nn)
second_dim = 200
x = rand(input_dim, second_dim)
@time nn(x);

  0.002678 seconds (714 allocations: 3.109 MiB)

@time nn_cpu(x);

  0.002113 seconds (714 allocations: 3.109 MiB)

If we also make the input static, we get:

using StaticArrays
x = @SMatrix rand(input_dim, second_dim)
nn(x);
@time nn(x);

  0.003259 seconds (207 allocations: 1.559 MiB)

@time nn_cpu(x);

  0.002212 seconds (715 allocations: 3.112 MiB)