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README.md 2025-08-01 3.2 kB
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Cuik-molmaker

Chemprop can now use cuik-molmaker (https://github.com/NVIDIA-Digital-Bio/cuik-molmaker), a C++/python package that accelerates atom and bond featurization. Usage of cuik-molmaker accelerates Chemprop training by 1.6X and inference by 2.4X. In addition, memory usage is reduced by ~80% enables larger-scale training and inference workloads. It can be used as a drop in replacement for the featurization classes implemented in Chemprop. Use chemprop/scripts/check_and_install_cuik_molmaker.py to install the correct version for your environment. Then specify --use-cuikmolmaker-featurization if using the command line. Or if you are using chemprop in a python script, import data.LazyMoleculeDatapoint, data.CuikmolmakerDataset, and featurizers.CuikmolmakerMolGraphFeaturizer.

Other notable changes

We continue to make the command line interface easier to use. The train command, chemprop train, no longer requires a test set. Additionally, datapoint descriptors (e.g., temperature, pressure) can now be included in the main input file using a command similar to chemprop train --data-path input.csv --descriptors-columns temperature pressure.

There are also several bug fixes in this release. See the detailed PR list below.

What's Changed

New Contributors

Full Changelog: https://github.com/chemprop/chemprop/compare/v2.2.0...v2.2.1

Source: README.md, updated 2025-08-01