Why am I getting a "Mutating arrays is not supported" error here?

Question

Here's a minimal working example.

using Flux

myvector = []
for i in 1:3
    push!(myvector, 0.1 * i) #Produces a vector [0.1, 0.2, 0.3]
end

Q = Chain(Dense(3, 64, relu), Dense(64, 32, relu), Dense(32, 16, relu), 
    Dense(16, 1, identity)) #Creates a neural network. Exact parameters aren't important.
θ, re = Flux.destructure(Q)

f(x) = -re(θ)(x)[1]

gs = gradient(f, myvector)[1] #Takes the gradient of f at the point u. 

The code creates a vector myvector and a neural network Q. It then feeds the neural network myvector and tries to take the gradient. There is a mutating arrays error:

Mutating arrays is not supported -- called setindex!(Vector{Any}, ...) This error occurs when you ask Zygote to differentiate operations that change the elements of arrays in place (e.g. setting values with x .= ...)

Why is there such an error? Nothing seems to be changing the elements of the array. How can I fix this error?

If instead of using !push to define the vector I had simply defined myvector = [0.1, 0.2, 0.3], then there is no error. However, I don't see why - the !push doesn't modify the elements, it just increases the length of myvector. For my use case as well, the elements of the vector are complicated and need to be calculated individually, so I can't just define myvector as in this MWE.

There is also no error if I define myvector = AbstractFloat[]. However, this seems to cause issues elsewhere in my use case (which I will ask about separately if making myvector an AbstractFloat is the best solution).

Answer 1

Your issue is related to your variable, myvector. You made a Vector{Any}, which is not supported by Zygote. You could make a Vector{Float64} like this: myvector=[0.1 * i for i in 1:3]. In most cases, Float32 is needed for machine learning, myvector=[0.1 * i for i in 1:3].|>Float32

If you really want to use push!(), I would suggest using myvector = Float64[] instead of myvector = AbstractFloat[].