Open ajschumacher opened 3 years ago
Problems and Opportunities in Training Deep Learning Software Systems: An Analysis of Variance https://www.cs.purdue.edu/homes/lintan/publications/variance-ase20.pdf https://dl.acm.org/doi/10.1145/3324884.3416545 December 2020
A Workaround for Non-Determinism in TensorFlow https://www.twosigma.com/articles/a-workaround-for-non-determinism-in-tensorflow/
Determinism in Deep Learning (S9911) Duncan Riach, GTC 2019 https://developer.download.nvidia.com/video/gputechconf/gtc/2019/presentation/s9911-determinism-in-deep-learning.pdf
The funny thing still is that even if you make your runs deterministic, you haven't eliminated randomness, you've just frozen a particular random example.
Underspecification Presents Challenges for Credibility in Modern Machine Learning https://arxiv.org/abs/2011.03395
TF_CUDNN_DETERMINISTIC, TF_CUDNN_USE_AUTOTUNE
Problems and Opportunities in Training Deep Learning Software Systems: An Analysis of Variance https://www.cs.purdue.edu/homes/lintan/publications/variance-ase20.pdf https://dl.acm.org/doi/10.1145/3324884.3416545 December 2020
A Workaround for Non-Determinism in TensorFlow https://www.twosigma.com/articles/a-workaround-for-non-determinism-in-tensorflow/
Determinism in Deep Learning (S9911) Duncan Riach, GTC 2019 https://developer.download.nvidia.com/video/gputechconf/gtc/2019/presentation/s9911-determinism-in-deep-learning.pdf
The funny thing still is that even if you make your runs deterministic, you haven't eliminated randomness, you've just frozen a particular random example.
Underspecification Presents Challenges for Credibility in Modern Machine Learning https://arxiv.org/abs/2011.03395