Fix numerical issues and efficiency issues #19
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1. Changes to `get_one_hot` Problems are given in: - #14 - #17 - #13 I discarded the changes in the PRs and and added more comprehensive handling of the input data in the `SmilesDataset` class and the `get_one_hot` function. 2. Imaginary components Frechet distance calculation fails to work for some cases because of badly conditioned matrices, as described here #15. Could not reproduce the error locally, but could do so on colab. Fixed it in `calculate_frechet_distance` by checking if the first `covmean` computation is real add a small value to the diagonal. This made it work for me and I got the same result as the original implementation run locally. 3. Added some more tests and changed to pytest 4. As described in #16 I changed the data type of the activations to float32 in the `get_predictions` function, which saves memory for larger datasets. 5. Change to pyproject.toml
Change version number Add two workflows that run tests on the dev and master branches and added some shields to the README.md file.
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Fix numerical issues and efficiency issues
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Fix numerical issues and efficiency issues
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Fix numerical issues and efficiency issues
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Fix numerical issues and efficiency issues
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Fix numerical issues and efficiency issues
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Fix numerical issues and efficiency issues
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Apr 1, 2024
Fix numerical issues and efficiency issues
renzph
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Apr 1, 2024
Fix numerical issues and efficiency issues
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Apr 1, 2024
Fix numerical issues and efficiency issues
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Apr 1, 2024
Fix numerical issues and efficiency issues
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Fix some numerical issues and do some argument checking in bf69345.
Automate tests and add some shields in 2c45937