FluxML/Flux.jl

Allow BatchNorm training on CUDA with `track_stats=false`

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#1,606 创建于 2021年5月31日

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 (4 评论) (0 反应) (0 负责人)Julia (4,725 star) (619 fork)batch import
good first issuehelp wanted

描述

Gathered from https://discourse.julialang.org/t/batchnorm-only-track-stats-true-supported-on-gpu/62091.

This would most likely require changes in NNlibCUDA as well. I'm not sure how interchangeable the various cudnnBatchNormalizationForward* functions are, so putting a pin in this until someone more knowledgeable can comment.

贡献者指南

技术栈
无
领域
machine learning
议题类型
feature
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
4
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
over 1 week
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
stale
清晰度议题是否清楚说明期望改动、验收标准和下一步。
mostly clear
前置要求
JuliaFlux.jlCUDACuDNN
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
15
研究方向
Review the discourse thread linked for context on the request. Investigate the CuDNN API to determine if there is a way to perform batch normalization training without updating running statistics (i.e., track stats=false). Then identify the necessary changes in NNlibCUDA and Flux.jl to expose this option. Check for any existing work or discussions in the linked repository forks or related issues.
Allow BatchNorm training on CUDA with `track_stats=false` · FluxML/Flux.jl#1606 | Good First Issue