Update – using latest Flux. I’d like to optimize a function of the singular values of a matrix. The Flux training loop barfs. Here’s my code using Flux, ForwardDiff, LinearAlgebra, GenericLinearAlgebra m = 20 X = randn(m,m) model = Dense(m,m) loss(X) = sum(GenericLinearAlgebra.svdvals(model(X))) …

Here’s how you can get the gradient working: using Flux, Zygote, ForwardDiff using GenericLinearAlgebra: svdvals svdvals2(X) = Zygote.forwarddiff(svdvals, X) m = 20 X = randn(m,m) model = Dense(m,m) loss(X) = sum(svdvals2(X)) ## nuclear norm loss(X) gradient(loss, X) This plugs in forwarddiff …

Using Flux to optimize a function of the Singular Values

Specific Domains Optimization (Mathematical)

baggepinnen May 18, 2020, 10:57am 2

Welcome to this forum! See this post

to make the code more readable

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Using Flux to optimize a function of the Singular Values

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