# Debugging Zygote: ERROR: Mutating arrays is not supported

**URL:** <https://discourse.julialang.org/t/debugging-zygote-error-mutating-arrays-is-not-supported/85064>\
**Category:** New to Julia\
**Tags:** flux, zygote\
**Created:** [July 31, 2022, 3:12pm UTC](https://discourse.julialang.org/t/debugging-zygote-error-mutating-arrays-is-not-supported/85064 "2022-07-31T15:12:08Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![mauerflitzer](https://avatars.discourse-cdn.com/v4/letter/m/ba9def/32.png) [@mauerflitzer](https://discourse.julialang.org/u/mauerflitzer)\
**Post date:** [July 31, 2022, 3:12pm UTC](https://discourse.julialang.org/t/debugging-zygote-error-mutating-arrays-is-not-supported/85064/1 "2022-07-31T15:12:08Z")

</div>

Hi,

I’m fairly new to Julia and not really experienced with Zygote so far, thats why I have a hard time debugging it. I try to implement the following loss function, where I pass a 2 dimensional grid (t and x) and calculate the derrivates of the model for both x and t.  
This is my training call:

```julia
train!(loss, parameters, [(xtrain, x_grid, t_grid, ytrain)], opt, cb=evalcb)

```

And here is the definition of my loss function

```julia
function loss(xtrain, x_sensor, t_sensor, ytrain)
    f = model(xtrain, vcat(x_sensor, t_sensor))
    f_x = jacobian(x_grid -> model(xtrain, vcat(x_grid, t_sensor)), x_sensor)[1]
    f_t = jacobian(t_grid -> model(xtrain, vcat(x_sensor, t_grid)), t_sensor)[1]

    loss_residual = f_t + f .* f_x
   return sum(loss_residual)

```

I gett the following error message all the time and I cant figure out what is wrong:

```julia
ERROR: Mutating arrays is not supported -- called copyto!(::SubArray{Float64, 1, Matrix{Float64}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}}, true}, _...)
Stacktrace:
  [1] error(s::String)
    @ Base .\error.jl:33
  [2] (::Zygote.var"#441#442"{SubArray{Float64, 1, Matrix{Float64}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}}, true}})(#unused#::Nothing)
    @ Zygote C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\lib\array.jl:74
  [3] (::Zygote.var"#2347#back#443"{Zygote.var"#441#442"{SubArray{Float64, 1, Matrix{Float64}, Tuple{Int64, Base.Slice{Base.OneTo{Int64}}}, true}}})(Δ::Nothing)
    @ Zygote C:\Users\Tobi\.julia\packages\ZygoteRules\AIbCs\src\adjoint.jl:67
  [4] Pullback
    @ C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\lib\grad.jl:183 [inlined]
  [5] (::typeof(∂(_gradcopy!)))(Δ::Nothing)
    @ Zygote C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\compiler\interface2.jl:0
  [6] Pullback
    @ C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\lib\grad.jl:165 [inlined]
  [7] (::typeof(∂(withjacobian)))(Δ::Nothing)
    @ Zygote C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\compiler\interface2.jl:0
  [8] (::Zygote.var"#208#209"{Tuple{Tuple{Nothing}, Tuple{Nothing}}, typeof(∂(withjacobian))})(Δ::Nothing)
    @ Zygote C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\lib\lib.jl:207
  [9] #1750#back
    @ C:\Users\Tobi\.julia\packages\ZygoteRules\AIbCs\src\adjoint.jl:67 [inlined]
 [10] Pullback
    @ C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\lib\grad.jl:140 [inlined]
 [11] (::typeof(∂(jacobian)))(Δ::Nothing)
    @ Zygote C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\compiler\interface2.jl:0
 [12] Pullback
    @ .\REPL[414]:7 [inlined]
 [13] (::typeof(∂(loss_refactored)))(Δ::Int64)
    @ Zygote C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\compiler\interface2.jl:0
 [14] #208
    @ C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\lib\lib.jl:207 [inlined]
 [15] #1750#back
    @ C:\Users\Tobi\.julia\packages\ZygoteRules\AIbCs\src\adjoint.jl:67 [inlined]
 [16] Pullback
    @ C:\Users\Tobi\.julia\packages\Flux\js6mP\src\optimise\train.jl:120 [inlined]
 [17] (::typeof(∂(λ)))(Δ::Int64)
    @ Zygote C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\compiler\interface2.jl:0
 [18] (::Zygote.var"#89#90"{Params{Zygote.Buffer{Any, Vector{Any}}}, typeof(∂(λ)), Zygote.Context})(Δ::Int64)
    @ Zygote C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\compiler\interface.jl:357
 [19] gradient(f::Function, args::Params{Zygote.Buffer{Any, Vector{Any}}})
    @ Zygote C:\Users\Tobi\.julia\packages\Zygote\DkIUK\src\compiler\interface.jl:76
 [20] macro expansion
    @ C:\Users\Tobi\.julia\packages\Flux\js6mP\src\optimise\train.jl:119 [inlined]
 [21] macro expansion
    @ C:\Users\Tobi\.julia\packages\ProgressLogging\6KXlp\src\ProgressLogging.jl:328 [inlined]
 [22] train!(loss::Function, ps::Params{Zygote.Buffer{Any, Vector{Any}}}, data::Vector{Tuple{Vector{Float64}, Adjoint{Float64, Vector{Float64}}, Matrix{Float64}, Adjoint{Float64, Vector{Float64}}}}, opt::ADAM; cb::typeof(evalcb))
    @ Flux.Optimise C:\Users\Tobi\.julia\packages\Flux\js6mP\src\optimise\train.jl:117
 [23] top-level scope
    @ REPL[415]:1
 [24] top-level scope
    @ C:\Users\Tobi\.julia\packages\CUDA\qAl31\src\initialization.jl:52De

```

---

<div class="post-metadata">

**Author:** ![cortner](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/cortner/32/204_2.png) [@cortner](https://discourse.julialang.org/u/cortner)\
**Post date:** [July 31, 2022, 11:20pm UTC](https://discourse.julialang.org/t/debugging-zygote-error-mutating-arrays-is-not-supported/85064/2 "2022-07-31T23:20:18Z")

</div>

Have you implemented model and Jacobean yourself? You are likely mutating some arrays in those implementations. Use o my non-mutating arrays, or Buffers or judiciously annotate with @ignore\_derivatives or A combination of those.

Note that generic and even typical Julia code is more often than not INCOMPATIBLE with Zygote (or other AD packages) and it can be nontrivial to rewrite it in a way so that it becomes ADable… at least that’s my personal experience.

---

<div class="post-metadata">

**Author:** ![ToucheSir](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/touchesir/32/14411_2.png) [@ToucheSir](https://discourse.julialang.org/u/ToucheSir)\
**Post date:** [July 31, 2022, 11:42pm UTC](https://discourse.julialang.org/t/debugging-zygote-error-mutating-arrays-is-not-supported/85064/3 "2022-07-31T23:42:21Z")

</div>

`Zygote.jacobian` happens to be one of those incompatible functions: [Jacobian in loss function · Issue #953 · FluxML/Zygote.jl · GitHub](https://github.com/FluxML/Zygote.jl/issues/953)