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I use NVidia-Docker extensively in my Open Source project Deep Video Analytics [1] when combined with TensorFlow (which allows explicit GPU memory allocation) i
by aub3bhat 9y ago
I use NVidia-Docker extensively in my Open Source project Deep Video Analytics [1] when combined with TensorFlow (which allows explicit GPU memory allocation) its unbeatable in running multiple inference models on a single GPU in a reliable manner. Combining this setup with docker volumes on AWS EFS allows simple multi machine deployments.
[1] https://github.com/AKSHAYUBHAT/DeepVideoAnalytics https://github.com/AKSHAYUBHAT/DeepVideoAnalytics
- sandGorgon 9y agothis is pretty cool! why do you use multiple packages like torch and tensorflow ?
- aub3bhat 9y agoCertain algorithms/models are implemented in PyTorch or Caffe and typically it's huge amount of work to convert them to TensorFlow while ensuring correctness / Parity. Also I personally like design of PyTorch.
- sandGorgon 9y agocoming from the facebook/reactjs weaponized patent grant problem.. caffe also has the same revocable patent grant. Tensorflow is apache licensed. I think in general, the perception is that it is far safer to stay away from caffe.
- aub3bhat 9y agoCaffe 1 is developed by Berkeley and I think Apache or BSD licensed. The Patents.txt issue occurs with Caffe 2 which is developed by Facebook.