I am looking for a way to set up or modify an existing Docker image for installing tensorflow that will install it such that the SSE4, AVX, AVX2, and FMA instructions can be utilized for CPU speed up. So far I have found how to install from source using bazel How to Compile Tensorflow... and CPU instructions not compiled.... Neither of these explain how to do this within Docker. So I think what I am looking for is what you need to add to an existing docker image that installs without these options so that you can get a compile version of tensorflow with the CPU options enabled. The existing docker images do not do this because they want the image to run on as many machines as possible. I am using Ubuntu 14.04 on linux PC. I am new to docker but have installed tensorflow and have it working without getting the CPU warnings I get when I use the docker images. I may not need this for speed, but I have seen posts that claim the speed up can be significant. I searched for existing docker images that do this and could not find anything. I need this to work with gpu so needs to be compatible with nvidia-docker.

I just found this docker support for bazel and it might provide an answer, however I do not understand it well enough to know for sure. I believe this is saying that you can not build tensorflow with bazel inside a Dockerfile. You have to build a Dockerfile using bazel. Is my understanding correct and is this the only way to get a docker image with tensorflow compiled from source? If so, I could still use help in how to do it and still get the other dependencies that I would get if using an existing docker image for tensorflow.