Recently we've been able to add GPU-enabled TensorFlow builds to conda-forge! This was quite a journey, with multiple contributors trying different ways to convince the Bazel-based build system of TensorFlow to build CUDA-enabled packages. But we managed, and the pull request got merged.
As 2020 winds down, the Core team thought it'd be fun to review some of the big accomplishments our community has made this year.
Various members of the community have raised questions publicly and
privately about the implications of Anaconda's new Terms of Service
(TOS) on anaconda.com. First of all, we understand your concerns. We
would like to explain a bit how conda-forge works, how the TOS change
affects us and conda-forge users, and what our plans as a community
are for the future.
A new platform osx-arm64 has been added to the build matrix of
conda-forge. osx-arm64 packages are built to run on upcoming macOS
arm64 processors marketed as Apple Silicon. An installer for this
platform can be found
here.
tl;dr Depending on specific version numbers of underlying libraries may be too inaccurate and cause headaches as upstream libraries evolve and change. A more detailed approach is needed. In this post I outline current and potential work on a path towards a more complete inspection of requirements based on APIs and dynamic pinning of libraries.
Recently I've been thinking about operational risk (op. risk). Operational risks arise from failures of processes, for instance a missing email, or an automated software system not running properly. Many commercial institutions are interested in minimizing op. risk, since it is risk that produces no value, as opposed to risks associated with investing. This is also something I think about in my job at Lab49, where I'm a software engineering consultant focusing on financial institutions. I think there is also a good analogy for Conda-Forge, even though we are not a commercial outfit. In this case the risk we incur isn't the potential for lost earnings but frustration for our users and maintainers in the form of bugs and lackluster user experience. In this post I explore three main sources of operational risk for Conda-Forge: Automation, Top-Down Control, and Self-Service Structure.