Flux.jl

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Hi,

I tried the tutorial on this repo that is mentioned in the title. I am using Julia v. 1.8.5, and

[052768ef] CUDA v4.0.1 [587475ba] Flux v0.13.12 [eb30cadb] MLDatasets v0.7.9

ERROR: LoadError: Scalar indexing is disallowed. Invocation of getindex resulted in scalar indexing of a GPU array. This is typically caused by calling an iterating implementation of a method. Such implementations do not execute on the GPU, but very slowly on the CPU

According to the line numbers (in my file script), the issue seems to come from:

for i in 1:10 preds = m(test[i][1]) lab = test[i][2] for j = 1:1000 pred_class = findmax(preds[:, j])[2] actual_class = findmax(lab[:, j])[2] if pred_class == actual_class class_correct[pred_class] += 1 end class_total[actual_class] += 1
end
end

Besides this, I saw the warning: ┌ Warning: CIFAR10.testdata() is deprecated, use CIFAR10(split=:test)[:] instead.

/Pedro

I presume you mean http://fluxml.ai/tutorialposts/2020-09-15-deep-learning-flux/ . Unfortunately tutorials there have been allowed to rot, and ought to be deleted.

Some have more recently updated cousins here: https://github.com/FluxML/model-zoo#examples-in-the-model-zoo . Those should all have project/manifest files, so that julia --project loads a known-good set of versions. The version of Flux is noted for each; the ones which say v0.13 will work on latest Flux as above (i.e. without using their own manifest). Ideally they would all be so updated, of course...

I read about the license of Flux but I wanted to double check with you if it is fine if I take the example you wrote and copy/paste into some material I am developing for a course which will be publicly available?