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29d90b2
is marks continuous callback usage broken because of scalar indexing in https://github.com/JuliaDiffEq/DiffEqBase.jl/blob/master/src/init.jl#L150 . @maleadt I thought this was fixed on CuArrays.jl?
The text was updated successfully, but these errors were encountered:
Yes, findall is in CuArrays 1.4.0 JuliaGPU/CuArrays.jl#446 Using old package? Working with an array wrapper?
findall
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Interesting....
using DiffEqGPU, CuArrays, OrdinaryDiffEq, Test function lorenz(du,u,p,t) @inbounds begin du[1] = p[1]*(u[2]-u[1]) du[2] = u[1]*(p[2]-u[3]) - u[2] du[3] = u[1]*u[2] - p[3]*u[3] end nothing end CuArrays.allowscalar(false) u0 = Float32[1.0;0.0;0.0] tspan = (0.0f0,100.0f0) p = (10.0f0,28.0f0,8/3f0) prob = ODEProblem(lorenz,u0,tspan,p) const pre_p = [rand(Float32,3) for i in 1:10] prob_func = (prob,i,repeat) -> remake(prob,p=pre_p[i].*p) c_condition = function (u,t,integrator) @inbounds u[1] - 3 end c_affect! = function (integrator) @inbounds integrator.u[1] += 20 end callback_prob = ODEProblem(lorenz,u0,tspan,p,callback=ContinuousCallback(c_condition,c_affect!,save_positions=(false,false))) callback_monteprob = EnsembleProblem(callback_prob, prob_func = prob_func) solve(callback_monteprob,Tsit5(),EnsembleGPUArray(),trajectories=2,saveat=1.0f0)
The MWE works on my laptop but not my desktop
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29d90b2
is marks continuous callback usage broken because of scalar indexing in https://github.com/JuliaDiffEq/DiffEqBase.jl/blob/master/src/init.jl#L150 . @maleadt I thought this was fixed on CuArrays.jl?
The text was updated successfully, but these errors were encountered: