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Separate dev baseline and cuda layers #47
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/cc @fsx950223 let me know if you have any feedback |
What, specifically, could be accomplished with this change that could not be done with the current set of images? |
It was discussed already in the forum thread and in the mentioned ticket. The CPU/baseline could be also useful later to create other kind of images that are not CUDA centric.. eg. ROCM etc.. Preparing many PR doesn't requires the CUDA overhead and could be prepared on CPU only machine with a baseline image. Also If you develop your PR on the cloud you could just save disk space/costs. We need to support developers diversity and this is not going to create a tool large overhead as it is simply an intermediate stage/target over the original design. |
Ok, let's put this idea on hold until the size prevents us from doing something we otherwise would do. For example, if we're unable to run tests or provide some other utility because the size of the container is too large. For this quarter, I am restricting all development on these images to what my team uses in CI. Our CI doesn't need small CPU images, so any work towards those is going to create dead / unsupported extra containers, which I'm not willing to do until we have a lot more information about usage, needs, etc. |
If 6 years of TF activities are not enough for you to support this it is ok. |
This was gone a little bit on drift over the time cause we had other commit on master. |
@deven-amd Are you interested to have a CPU only stage? Could the ROCm image rely on this? |
As nobody is interested to reuse a common and shared CPU stage/image baseline I'am going to close this. |
This pull request is going to separate baseline and GPU layers to conditionally build GPU and GPU images with a subsequent PR.
See more at:
https://discuss.tensorflow.org/t/adopting-open-source-dockerfiles-for-official-tf-nightly-ci/6050/4
tensorflow/addons#2613