Automatically download a default checkpoint if it is not provided #48
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AustinT
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PR #48 added a new CI pipeline that covers single-step model inference, but it only tested half of the single-step models as the other ones did not work on CPU. This PR fixes this, making all models work on CPU, which mostly required making sure the right device is correctly propagated into all of the model internals. I then extended the test which now checks all `pip`-installable models we support. Additionally, I also merged the two CI pipelines into one, as this allows for generating a combined coverage report that takes into account all tests. This does not affect testing speed, as the different test jobs still run in parallel. Finally, I also noticed that the `.coveragerc` configuration was not quite right, as the files with 0% coverage were not being discovered; after a minor change to the configuration this is now fixed.
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This PR extends the single-step model classes to automatically download the default (trained on USPTO-50K) model checkpoint if no model directory is provided. This makes it even easier to get started with
syntheseusas one does not have to manually download and unzip the files. Once downloaded, the checkpoints are cached.On top of this, I also extend the integration CI to run a new single-step model test that checks that the supported models do run and return reasonable predictions for a simple input. While locally the test works for all 6
pip-installable models, on GitHub the GPU is not available, and settingdevice="cpu"uncovers that some of the models appear to only work on GPU. Thus, for now the test only covers Chemformer, LocalRetro and MEGAN; the other models will be added in the future.When running those tests, I found that the links we provided for LocalRetro and RetroKNN were not quite correct (the initial upload missed some of the files, which I later corrected, but the links were still pointing to the first upload rather than the corrected one). Morever, I found that RetroKNN was zipped using a method that
pythoncould not deal with, so I re-generated the file and re-uploaded it (again fixing the link).The changes are separated into reasonable commits for easier reviewing.