FluxML/FastAI.jl

Benchmark image pipelines against ffcv

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#236 建立於 2022年6月10日

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 (0 留言) (1 反應) (0 負責人)Julia (592 star) (49 fork)batch import
help wantedperformance

描述

[https://github.com/libffcv/ffcv] seems to be the state-of-the-art when it comes to fast image pipelines for training deep learning models on computer vision. Would be interesting to benchmark against this and see how we compare.

Results could motivate work on #235.

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無
領域
machine learningperformance
議題類型
performance
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
3
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1-2 days
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stale
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needs investigation
前置要求
Julia programmingFlux.jl familiarityBenchmarking concepts
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
30
研究方向
The issue proposes benchmarking FastAI.jl image pipelines against ffcv. First, understand the current image pipeline implementation in FastAI.jl (likely in src/). Then, replicate ffcv's optimized pipeline in Julia or compare using similar datasets. The results could inform improvements mentioned in issue #235. Look at ffcv's documentation and performance benchmarks to design a fair comparison.