Faster image pipelines · FluxML/FastAI.jl

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enhancementhelp wanted

Metriche repository

Some low-hanging fruit that FastAI.jl can pick to become faster here:

builtin presizing support
- prototype at https://github.com/lorenzoh/DataBlockStorage.jl/
- using JpegTurbo.jl's downsized loading so no storing to disk is needed (https://github.com/JuliaIO/JpegTurbo.jl/issues/15#issuecomment-1031548344)
use inplace operations
- DataAugmentation.jl already supports inplace operations, FastAI.jl just needs to add a buffered encode! interface and use those paths
- JpegTurbo.jl image loading could also be done inplace (https://github.com/JuliaIO/JpegTurbo.jl/issues/23)
- the whole pipeline could become non-allocating
use MLUtils.jl (#196)
- new DataLoader seems more stable and possibly a little faster
run projective transformations on GPU (https://github.com/lorenzoh/DataAugmentation.jl/issues/48)

Direzione di ricerca: Concentrati sull'implementazione del supporto per il presizing utilizzando il caricamento ridotto di JpegTurbo.jl, seguendo il prototipo in DataBlockStorage.jl. Testa l'integrazione e confronta i miglioramenti di velocità.
Tech stack: julia
Dominio: machine learning
Tipo issue: Performance
Difficoltà: 2
Tempo stimato: Mezza giornata
Stato attività: Nuova
Chiarezza: Chiara
Prerequisiti: JuliaGitFastAI.jl
Adatta ai principianti: 70