DLSpec: A Deep Learning Task Exchange Specification
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 26 Feb 2020.
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1 paper.
- 2021MLHarness: A Scalable Benchmarking System for MLCommonscited by 1
- 2021MLHarness: A Scalable Benchmarking System for MLCommons9 Nov 2021