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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) 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

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this is pretty cool! why do you use multiple packages like torch and tensorflow ?

Certain 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.

coming 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.

Caffe 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.

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