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| author | Mark Peschel | 2023-07-07 21:34:59 -0400 |
|---|---|---|
| committer | GitHub | 2023-07-07 21:34:59 -0400 |
| commit | 5e111f936e5b984f8d62cb6a63b13346ec18e3cf (patch) | |
| tree | 0e5cb731d5c04d2121ecbadf3b41ee670647b293 | |
| parent | b3bd540e3141f49764914171442d3f575bc1291d (diff) | |
| download | aur-5e111f936e5b984f8d62cb6a63b13346ec18e3cf.tar.gz | |
Add suggestions for fixing this build when it breaks.
| -rw-r--r-- | README.md | 7 |
1 files changed, 7 insertions, 0 deletions
diff --git a/README.md b/README.md index d77e7ed95ca1..938901839091 100644 --- a/README.md +++ b/README.md @@ -58,4 +58,11 @@ export HSA_OVERRIDE_GFX_VERSION=10.3.0 ``` You can find your gfx by running `/opt/rocm/bin/rocminfo | grep gfx` after installing `rocminfo`. +## Fixing this PKGBUILD when it inevitably breaks +To learn what the build environment is supposed to look like, see the official Dockerfile for building tensorflow: [ROCmSoftwarePlatform/tensorflow-upstream in tensorflow/tools/ci_build/Dockerfile.rocm](https://github.com/ROCmSoftwarePlatform/tensorflow-upstream/blob/develop-upstream/tensorflow/tools/ci_build/Dockerfile.rocm). That's where I found out about `target.lst` among other things; hopefully it helps. + +If you are unable to build this, you may have luck with installing the python wheels. pip seems to think tensorflow-rocm is [only supported up to python 3.10](https://pypi.org/project/tensorflow-rocm/), so you will have to download the wheel [directly from AMD's website](http://ml-ci.amd.com:21096/job/tensorflow/job/release-rocmfork-r212-rocm-enhanced/job/release-build-whl/lastSuccessfulBuild/) and install it: `pip install tensorflow_rocm-2.12*cp311-cp311-manylinux2014_x86_64.whl` + +Lastly, it appears the officially intended way to use TensorFlow on ROCm is by a docker image. It takes forever to download, so your system clock may desynchronize with the server, so you may get random permission errors while downloading. If you do, `sudo systemctl start systemd-timesyncd`. Otherwise, follow [the official instructions here](https://hub.docker.com/r/rocm/tensorflow) or [my longer tutorial here.](https://github.com/mpeschel10/test-tensorflow-rocm) + ### Pull requests welcome. |