# Running Machine Learning Experiments with Flux

**URL:** <https://discourse.julialang.org/t/running-machine-learning-experiments-with-flux/102661>\
**Category:** Machine Learning\
**Tags:** machine-learning\
**Created:** [August 10, 2023, 8:03am UTC](https://discourse.julialang.org/t/running-machine-learning-experiments-with-flux/102661 "2023-08-10T08:03:28Z")\
**Posts on this page:** 6\
**Page:** 1

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**Author:** ![josemanuel22](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/josemanuel22/32/20668_2.png) [@josemanuel22](https://discourse.julialang.org/u/josemanuel22)\
**Post date:** [August 10, 2023, 8:03am UTC](https://discourse.julialang.org/t/running-machine-learning-experiments-with-flux/102661/1 "2023-08-10T08:03:29Z")

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I’m running some ML experiments to draw certain conclusions about whether my new method works as expected. I would like, so to speak, to run multiple experiments in the same file, as it would otherwise be cumbersome. The idea is to use a syntax similar to what Test offers; however, I don’t want to create a test, I just want to run an experiment and extract statistics from it. Is there any framework for this that I’m unaware of?

The idea would be to have something similar to this but I’m curious if there’s a dedicated package that offers specific functionalities for this purpose.

```julia
@testset "vanilla_gan" begin

    @testset "Origin N(0,1)" begin

        noise_model = Normal(0.0f0, 1.0f0)
        n_samples = 10000

        @testset "N(0,1) to N(23,1)" begin
            gen = Chain(Dense(1, 7), elu, Dense(7, 13), elu, Dense(13, 7), elu, Dense(7, 1))
            dscr = Chain(
                Dense(1, 11), elu, Dense(11, 29), elu, Dense(29, 11), elu, Dense(11, 1, σ)
            )
            target_model = Normal(23.0f0, 1.0f0)
            hparams = HyperParamsVanillaGan(;
                data_size=100,
                batch_size=1,
                epochs=1000,
                lr_dscr=1e-4,
                lr_gen=1e-4,
                dscr_steps=5,
                gen_steps=1,
                noise_model=noise_model,
                target_model=target_model,
            )

            train_vanilla_gan(dscr, gen, hparams)
           ksd = KSD(noise_model, target_model, n_samples, 20:0.1:25)
            mae = MAE(noise_model, x -> x .+ 23, n_samples)
            mse = MSE(noise_model, x -> x .+ 23, n_sample)
    end
...

```

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<div class="post-metadata">

**Author:** ![Maucejo](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maucejo/32/39090_2.png) [@Maucejo](https://discourse.julialang.org/u/Maucejo)\
**Post date:** [August 10, 2023, 9:17am UTC](https://discourse.julialang.org/t/running-machine-learning-experiments-with-flux/102661/3 "2023-08-10T09:17:37Z")

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I think that `DrWatson.jl` can help you to run several experiments by varying the parameters.  
Look at the doc of the package to see if it suits your needs.

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**Author:** ![kir0ul](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/kir0ul/32/31826_2.png) [@kir0ul](https://discourse.julialang.org/u/kir0ul)\
**Post date:** [August 10, 2023, 2:34pm UTC](https://discourse.julialang.org/t/running-machine-learning-experiments-with-flux/102661/4 "2023-08-10T14:34:16Z")

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Also `MLFlowClient.jl` could probably help for that use case: [Tutorial · MLFlowClient.jl](https://juliaai.github.io/MLFlowClient.jl/dev/tutorial/)

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**Author:** ![ablaom](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ablaom/32/4889_2.png) [@ablaom](https://discourse.julialang.org/u/ablaom)\
**Post date:** [August 13, 2023, 8:33pm UTC](https://discourse.julialang.org/t/running-machine-learning-experiments-with-flux/102661/5 "2023-08-13T20:33:28Z")

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A GSoC project in progress provides integration between mlflow (using MLFlowClient.jl) and [MLJ](https://alan-turing-institute.github.io/MLJ.jl/dev/), a general ML framework which provides some Flux models (see [MLJFlux](https://github.com/FluxML/MLJFlux.jl)). I expect a basic release within a month.

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<div class="post-metadata">

**Author:** ![ablaom](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ablaom/32/4889_2.png) [@ablaom](https://discourse.julialang.org/u/ablaom)\
**Post date:** [August 13, 2023, 8:34pm UTC](https://discourse.julialang.org/t/running-machine-learning-experiments-with-flux/102661/6 "2023-08-13T20:34:28Z")

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As part of this project MLFlowClient.jl has been brought up-to-date with the latest mlflow API.

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<div class="post-metadata">

**Author:** ![xgdgsc](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/xgdgsc/32/608_2.png) [@xgdgsc](https://discourse.julialang.org/u/xgdgsc)\
**Post date:** [August 24, 2023, 9:55am UTC](https://discourse.julialang.org/t/running-machine-learning-experiments-with-flux/102661/7 "2023-08-24T09:55:11Z")

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I’ ve just started using mlflow and found it’ s authentication pretty experimental like [[BUG] Security Vulnerability anyone can use /signup · Issue #9448 · mlflow/mlflow · GitHub](https://github.com/mlflow/mlflow/issues/9448) . Do you know something that does better in authentication/group permission management?