DLSpec:一个深度学习任务交换规范
DLSpec: A Deep Learning Task Exchange Specification
University of Illinois Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校);IBM T. J. Watson Research Center(IBM托马斯·J·沃森研究中心)
摘要:
深度学习(DL)创新正在快速推出。然而,目前缺乏DL任务的标准规范使得共享、运行、复制和比较这些创新变得困难。为了解决这个问题,我们提出了DLSpec,一个模型,数据集,软件和硬件无关的DL规范,捕获DL任务的不同方面。DLSpec已经通过指定和运行数百个DL任务进行了测试。
英文摘要:
Deep Learning (DL) innovations are being introduced at a rapid pace. However, the current lack of standard specification of DL tasks makes sharing, running, reproducing, and comparing these innovations difficult. To address this problem, we propose DLSpec, a model-, dataset-, software-, and hardware-agnostic DL specification that captures the different aspects of DL tasks. DLSpec has been tested by specifying and running hundreds of DL tasks.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。