# Weird error in Flux model

**URL:** <https://discourse.julialang.org/t/weird-error-in-flux-model/108650>\
**Category:** New to Julia\
**Tags:** question, flux, zygote\
**Created:** [January 10, 2024, 11:40pm UTC](https://discourse.julialang.org/t/weird-error-in-flux-model/108650 "2024-01-10T23:40:19Z")\
**Posts on this page:** 5\
**Page:** 1

<div class="post-metadata">

**Author:** ![artp96](https://avatars.discourse-cdn.com/v4/letter/a/858c86/32.png) [@artp96](https://discourse.julialang.org/u/artp96)\
**Post date:** [January 10, 2024, 11:40pm UTC](https://discourse.julialang.org/t/weird-error-in-flux-model/108650/1 "2024-01-10T23:40:19Z")

</div>

I hate to blindly dump but I’m getting a weird error with this code. I’ve tried looking for something similar, and I’ve spent some time trying to debug it and even asked GPT-4 but I’m stumped.

```julia
using cuDNN, Flux, CUDA
h = Chain(
    Dense(32 => 64, relu), # activation function inside layer
    Dense(64 => 32, relu), # activation function inside layer
    Dense(32 => 32, relu), # activation function inside layer
    Dense(32 => 64, relu), # activation function inside layer
identity)

opt = Flux.setup(Adam(0.001), h)

x = Flux.dataloader((x=𝒟, y=𝒯); batchsize=128, shuffle=true)
ε = [] # loss
@showprogress for t in 1:1000
    for (x, y) in X
        εₜ, ∇ = Flux.withgradient(h) do m
            # Evaluate model and loss inside gradient context:
            yₜ = m(x)
            Flux.mae(yₜ, y)
        end
        Flux.update!(h, opt, ∇)
        push!(ε, εₜ) # logging, outside gradient context
    end
end

```

where x and y are matrices of size n\*32. The error is as follows:

```julia
┌ Error: Exception while generating log record in module Main at /home/art/Work/NMR/Neural Networks in/NN_2/CPP_ver/WithLogging.jl:7
│ exception =
│ LoadError: MethodError: no method matching (::var"#31#32")(::Chain{NTuple{4, Dense{typeof(relu), Matrix{Float32}, Vector{Float32}}}}, ::@NamedTuple{data::Matrix{Float32}, label::Matrix{Float32}})
│    
│ Closest candidates are:
│ (::var"#31#32")(::Any, ::Any, !Matched::Any)
│ @ Main ~/Work/NMR/Neural Networks in/NN_2/CPP_ver/testrun.jl:45
│    
│ Stacktrace:
│ [1] macro expansion
│ @ ~/.julia/packages/Zygote/WOy6z/src/compiler/interface2.jl:0 [inlined]
│ [2] _pullback(::Zygote.Context{false}, ::var"#31#32", ::Chain{NTuple{4, Dense{typeof(relu), Matrix{Float32}, Vector{Float32}}}}, ::@NamedTuple{data::Matrix{Float32}, label::Matrix{Float32}})
│ @ Zygote ~/.julia/packages/Zygote/WOy6z/src/compiler/interface2.jl:81
│ [3] _apply(::Function, ::Vararg{Any})
│ @ Core ./boot.jl:838
│ [4] adjoint
│ @ ~/.julia/packages/Zygote/WOy6z/src/lib/lib.jl:203 [inlined]
│ [5] _pullback
│ @ ~/.julia/packages/ZygoteRules/4nXuu/src/adjoint.jl:66 [inlined]
│ [6] #4
│ @ ~/.julia/packages/Flux/UsEXa/src/train.jl:107 [inlined]
│ [7] _pullback(ctx::Zygote.Context{false}, f::Flux.Train.var"#4#5"{var"#31#32", Tuple{@NamedTuple{data::Matrix{Float32}, label::Matrix{Float32}}}}, args::Chain{NTuple{4, Dense{typeof(relu), Matrix{Float32}, Vector{Float32}}}})
│ @ Zygote ~/.julia/packages/Zygote/WOy6z/src/compiler/interface2.jl:0
│ [8] pullback(f::Function, cx::Zygote.Context{false}, args::Chain{NTuple{4, Dense{typeof(relu), Matrix{Float32}, Vector{Float32}}}})
│ @ Zygote ~/.julia/packages/Zygote/WOy6z/src/compiler/interface.jl:44
│ [9] pullback(f::Function, cx::Zygote.Context{false}, args::Chain{NTuple{4, Dense{typeof(relu), Matrix{Float32}, Vector{Float32}}}})
│ @ Zygote ~/.julia/packages/Zygote/WOy6z/src/compiler/interface.jl:42 [inlined]
│ [10] withgradient(f::Function, args::Chain{NTuple{4, Dense{typeof(relu), Matrix{Float32}, Vector{Float32}}}})
│ @ Zygote ~/.julia/packages/Zygote/WOy6z/src/compiler/interface.jl:154
│ [11] macro expansion
│ @ ~/.julia/packages/Flux/UsEXa/src/train.jl:107 [inlined]
│ [12] macro expansion
│ @ ~/.julia/packages/ProgressLogging/6KXlp/src/ProgressLogging.jl:328 [inlined]
│ [13] train!(loss::Function, model::Chain{NTuple{4, Dense{typeof(relu), Matrix{Float32}, Vector{Float32}}}}, data::MLUtils.DataLoader{@NamedTuple{data::Matrix{Float32}, label::Matrix{Float32}}, Random._GLOBAL_RNG, Val{nothing}}, opt::@NamedTuple{layers::NTuple{4, @NamedTuple{weight::Optimisers.Leaf{Optimisers.Adam, Tuple{Matrix{Float32}, Matrix{Float32}, Tuple{Float32, Float32}}}, bias::Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}, σ::Tuple{}}}}; cb::Nothing)
│ @ Flux.Train ~/.julia/packages/Flux/UsEXa/src/train.jl:105
│ [14] train!(loss::Function, model::Chain{NTuple{4, Dense{typeof(relu), Matrix{Float32}, Vector{Float32}}}}, data::MLUtils.DataLoader{@NamedTuple{data::Matrix{Float32}, label::Matrix{Float32}}, Random._GLOBAL_RNG, Val{nothing}}, opt::@NamedTuple{layers::NTuple{4, @NamedTuple{weight::Optimisers.Leaf{Optimisers.Adam, Tuple{Matrix{Float32}, Matrix{Float32}, Tuple{Float32, Float32}}}, bias::Optimisers.Leaf{Optimisers.Adam, Tuple{Vector{Float32}, Vector{Float32}, Tuple{Float32, Float32}}}, σ::Tuple{}}}})
│ @ Flux.Train ~/.julia/packages/Flux/UsEXa/src/train.jl:102
│ [15] top-level scope

```

I don’t get why this is throwing a method error of this type.  
Should I be using a different training function for non-classification problems? Everything on the documentation seems to be image classification of some kind.

thankyou in advance!

---

<div class="post-metadata">

**Author:** ![artp96](https://avatars.discourse-cdn.com/v4/letter/a/858c86/32.png) [@artp96](https://discourse.julialang.org/u/artp96)\
**Post date:** [January 10, 2024, 11:41pm UTC](https://discourse.julialang.org/t/weird-error-in-flux-model/108650/2 "2024-01-10T23:41:21Z")

</div>

all packages up to date at time of posting

---

<div class="post-metadata">

**Author:** ![CarloLucibello](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/carlolucibello/32/3278_2.png) [@CarloLucibello](https://discourse.julialang.org/u/CarloLucibello)\
**Post date:** [January 11, 2024, 8:46am UTC](https://discourse.julialang.org/t/weird-error-in-flux-model/108650/3 "2024-01-11T08:46:46Z")

</div>

Can you paste a reproducible example?

---

<div class="post-metadata">

**Author:** ![artp96](https://avatars.discourse-cdn.com/v4/letter/a/858c86/32.png) [@artp96](https://discourse.julialang.org/u/artp96)\
**Post date:** [January 11, 2024, 11:04am UTC](https://discourse.julialang.org/t/weird-error-in-flux-model/108650/4 "2024-01-11T11:04:15Z")

</div>

full MWE

```julia
using CUDA, cuDNN, Flux, ProgressMeter

x = randn(Float32,(32,1000))
y = randn(Float32,(64,1000))

h = Chain(
    Dense(32 => 64, relu), # activation function inside layer
    Dense(64 => 32, relu), # activation function inside layer
    Dense(32 => 32, relu), # activation function inside layer
    Dense(32 => 64), # activation function inside layer
identity)

opt = Flux.setup(Adam(0.001), h)
h = gpu(h)

X = Flux.DataLoader((x=x, y=y); batchsize=128, shuffle=true)
ε = [] # loss
@showprogress for t in 1:1000
    for (x, y) in X
      x_gpu = gpu(x)
      y_gpu = gpu(y)
        εₜ, ∇ = Flux.withgradient(h) do m
            # Evaluate model and loss inside gradient context:
            yₜ = m(x)
            Flux.mae(yₜ, y)
        end
        Flux.update!(h, opt, ∇)
        push!(ε, εₜ) # logging, outside gradient context
    end
end

```

---

<div class="post-metadata">

**Author:** ![artp96](https://avatars.discourse-cdn.com/v4/letter/a/858c86/32.png) [@artp96](https://discourse.julialang.org/u/artp96)\
**Post date:** [January 11, 2024, 11:15am UTC](https://discourse.julialang.org/t/weird-error-in-flux-model/108650/5 "2024-01-11T11:15:29Z")

</div>

Solved, basic syntax error in ` Flux.update!`, should have passed `(opt, h, del[1])`

Very weird error format for this mistake though