# CuArray error when running NeuralPDE.jl on JuliaHub

**URL:** <https://discourse.julialang.org/t/cuarray-error-when-running-neuralpde-jl-on-juliahub/101798>\
**Category:** GPU\
**Tags:** sciml, neural-network\
**Created:** [July 19, 2023, 6:49pm UTC](https://discourse.julialang.org/t/cuarray-error-when-running-neuralpde-jl-on-juliahub/101798 "2023-07-19T18:49:52Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![PeX](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/pex/32/49986_2.png) [@PeX](https://discourse.julialang.org/u/PeX)\
**Post date:** [July 19, 2023, 6:49pm UTC](https://discourse.julialang.org/t/cuarray-error-when-running-neuralpde-jl-on-juliahub/101798/1 "2023-07-19T18:49:52Z")

</div>

Hi everyone!  
I was trying to test the GPU ability of NeuralPDE.jl on the JuliaHub, my network is defined like this:

```julia
# Neural network
inner = 25
chain = Chain(Dense(3,inner,Lux.σ),
              Dense(inner,inner,Lux.σ),
              Dense(inner,inner,Lux.σ),
              Dense(inner,inner,Lux.σ),
              Dense(inner,6)) 

strategy = GridTraining(0.05)
ps = Lux.setup(Random.default_rng(), chain)[1]
ps = ps |> ComponentArray |> gpu .|> Float64
discretization = PhysicsInformedNN(chain,
                                   strategy,
                                   init_params = ps)

@named pdesystem = PDESystem(eqs, ic_bc, domains, [t,x,z], [u(t,x,z), w(t,x,z), P(t,x,z),
T(t,x,z), τ₁(t,x,z), τ₃(t,x,z) ])

prob = discretize(pdesystem,discretization)

```

But when I execute the last line I get:

```julia
ERROR: CuArray only supports element types that are allocated inline.
Real is not allocated inline

```

I was looking to see if this issue was mentioned somewhere and I found [this](https://github.com/SciML/NeuralPDE.jl/issues/594)

But I didn’t understand if this was solved yet.

This is my first time trying to use a GPU, so any hints would be highly appreciated!