Hi all, trying to pull together a few separate discussions into a single thread here.
The main issue is that currently PEP 508 does not provide environment markers for GPU/CUDA availability, which leads to problems for projects that want to provide distributions for environments with and without GPU support. As far as I can tell, there's been multiple suggestions to bring this issue to distutils-sig, but no one has actually done it. Relevant issues: (closed) "How should Python packages depending on TensorFlow structure their requirements?" https://github.com/tensorflow/tensorflow/issues/7166 (closed) "Adding gpu or cuda specification in PEP 508" https://github.com/python/peps/issues/581 (closed) "More support for conditional installation" https://github.com/pypa/pipenv/issues/1353 (no response) "Adding gpu or cuda markers in PEP 508" https://github.com/pypa/interoperability-peps/issues/68 There is now a third-party project which attempts to amend this for tensorflow (https://github.com/akatrevorjay/tensorflow-auto-detect) but this approach is somewhat fragile (depends on version numbers being in sync), doesn't directly scale to all similar projects, and would require maintainers for a given project to maintain _three_ separate projects, instead of just one. I'm not intimately familiar with PEP 508, so my questions for this list: * Is the demand sufficient to justify supporting this use case? * Is it possible to add support for GPU Environment markers? * If so, what would need to be done? * If implemented, what should the transition look like for projects like tensorflow? Thanks! D. -- Distutils-SIG mailing list -- distutils-sig@python.org To unsubscribe send an email to distutils-sig-le...@python.org https://mail.python.org/mm3/mailman3/lists/distutils-sig.python.org/ Message archived at https://mail.python.org/mm3/archives/list/distutils-sig@python.org/message/LXLF4YSC4WUZOYRX65DW7CESIX7UUBK5/
