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I been working with vscode development containers. I've managed to build 2 separate containers to leverage gpu support inside of the container.

The first container built tensorflow-gpu into a cuda:11.5.2-cudnn8 runtime image.

With the other container I'm using cudf, and I've tried a couple variations of builds from the install rapidsai guide. How ever installing both tensorflow-gpu and cudf into the same environment has been troublesome due to package conflicts notably with protobuff.

I did at one point get them to install into the same image using a rapidsai devel image but conda took well over an hour to resolve and the final image was something like 30gb and there were still some bugs.

Anyone tips one getting cudf and tensorflow-gpu to run in the same environment?

Jason Leaver
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To get RAPIDS and Tensorflow into the same container, use CUDA Toolkit (CTK) 11.2. I think this is the only CTK version compatible with both libraries right now.

TaureanDyerNV
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