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I figure out a way that may get multiple GPU support with the latest CUDA. If I built a tensorflow 1.15 configured for CUDA 10.2 from source, I'll be able to build the PIP package .whl. My questions is once I have the PIP package, how to I point the DSS code env to import it as the tensorflow package to use?
Hi,
As stated in my previous answer, in the case of the Visual Deep Learning in DSS, the latest versions we support are:
- tensorflow 1.15
- keras 2.3
- CUDA 10.0
- cuDNN 7.6
If you use these versions specifically, you will be able to build your code-env directly from pip. This way you'll be able to create a managed code-env in DSS.
I would not recommend building tensorflow from source (unless there is a specific feature of CUDA 10.2 which is not available in CUDA 10.0).
Cheers,
Alex