# LIBSVM call on remote workers requires waiting

**URL:** <https://discourse.julialang.org/t/libsvm-call-on-remote-workers-requires-waiting/127796>\
**Category:** Performance\
**Tags:** precompilation, distributed, machine-learning\
**Created:** [April 7, 2025, 1:05pm UTC](https://discourse.julialang.org/t/libsvm-call-on-remote-workers-requires-waiting/127796 "2025-04-07T13:05:15Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![alequa](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/alequa/32/12338_2.png) [@alequa](https://discourse.julialang.org/u/alequa)\
**Post date:** [April 7, 2025, 1:05pm UTC](https://discourse.julialang.org/t/libsvm-call-on-remote-workers-requires-waiting/127796/1 "2025-04-07T13:05:15Z")

</div>

Hello,

I have been getting a bit crazy on this (now solved) problem.

I am running a SVM classification on a remote worker, the LIBSVM is imported under the hood  
of another module, let’s call it ClassifierModule, so that it can preprocess my raw data.

The code looks something like this:

```julia
using Distributed
addprocs(2)
@everywhere module MyClassifier 
    using Distributed
    using MLJ
    using LIBSVM
    # Define a function to run on the remote node
    function run_svm()
        # Your LIBSVM code here
        SVMClassifier = MLJ.@load SVC pkg=LIBSVM verbosity=0
        svm = SVMClassifier(kernel=LIBSVM.Kernel.Linear)
        return svm
    end
    export run_svm
end

# Add remote processes

# Ensure that the code is executed on all nodes
# Run the function on a remote node
future = @spawnat 2 MyClassifier.run_svm()
model = fetch(future) # ! Here it gets the error

```

Running this code gives me this error:

```julia
ERROR: MethodError: no method matching MLJLIBSVMInterface.SVC(; kernel::LIBSVM.Kernel.KERNEL)
The type `MLJLIBSVMInterface.SVC` exists, but no method is defined for this combination of argument types when trying to construct it.

Closest candidates are:
  MLJLIBSVMInterface.SVC(::Any, ::Float64, ::Float64, ::Float64, ::Int32, ::Float64, ::Float64, ::Bool) got unsupported keyword argument "kernel" (method too new to be called from this world context.)
   @ MLJLIBSVMInterface ~/.julia/packages/MLJLIBSVMInterface/zUY3E/src/MLJLIBSVMInterface.jl:56
  MLJLIBSVMInterface.SVC(::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any) got unsupported keyword argument "kernel" (method too new to be called from this world context.)
   @ MLJLIBSVMInterface ~/.julia/packages/MLJLIBSVMInterface/zUY3E/src/MLJLIBSVMInterface.jl:56
  MLJLIBSVMInterface.SVC(; kernel, gamma, cost, cachesize, degree, coef0, tolerance, shrinking) (method too new to be called from this world context.)
   @ MLJLIBSVMInterface ~/.julia/packages/MLJLIBSVMInterface/zUY3E/src/MLJLIBSVMInterface.jl:66

```

however, if I wait enough, let’s say, 10seconds, and rerun the code, it works. Thus, I believe it is some sort of problem of precompilation, for which I am calling the function while an independent process is still compiling it.

My simple solution was to do this:

```julia

ready = false
while !ready
    test_workers = []
    @sync for p in workers()
        k = @spawnat p begin
            try
                MyClassifier.run_svm()
                @info "SVMLIB loaded on worker $(getpid())"
                return true
            catch e
                return false
            end
        end
        push!(test_workers, k)
    end
    ready = all([fetch(k) for k in test_workers])
    if !ready
        @info "Workers not ready yet"
        sleep(5)
    end
end

```

But it s not very elegant and it is annoying to rewrite it every time I want to run a SVM classification on some data. How could I do to solve this problem in few lines? possibly from within the `MyClassifier` module?

---

<div class="post-metadata">

**Author:** ![alequa](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/alequa/32/12338_2.png) [@alequa](https://discourse.julialang.org/u/alequa)\
**Post date:** [April 7, 2025, 1:13pm UTC](https://discourse.julialang.org/t/libsvm-call-on-remote-workers-requires-waiting/127796/2 "2025-04-07T13:13:46Z")

</div>

I can also do this:

```julia

function run_svm()
    svm = nothing
    while !machine_loaded 
        machine_loaded = begin
            try
                SVMClassifier = MLJ.@load SVC pkg=LIBSVM verbosity=0
                svm = SVMClassifier(kernel=LIBSVM.Kernel.Linear)
                true
            catch e
                @warn "SVMLIB not loaded (yet) on worker $(getpid())"
                sleep(5)
                false
            end
        end
    return svm
    end
end

```

But still, not the most elegant solution. I would really prefer that this problem is solved (and the interpreter wait for it) at the `using MyClassifier` point