Welcome to ChemTorch!

ChemTorch is a modular open-source research framework for deep learning of chemical reactions.

• 🚀 Streamline your research workflow: seamlessly assemble modular deep learning pipelines, track experiments, conduct hyperparameter sweeps, and run benchmarks.

• 💡 Multiple reaction representations with baseline implementations including SMILES tokenizations, molecular graphs, 3D geometries, and fingerprint descriptors.

• ⚙️ Preconfigured data pipelines for common benchmark datasets including RDB7, cycloadditions, USPTO-1k, and more.

• 🔬 OOD evaluation via chemically informed data splitters (size, target, scaffold, reaction core, …).

• 🗂️ Extensible component library (growing) for all parts of the ChemTorch pipeline.

• 🔄 Reproducibility by design with Weights & Biases experiment tracking and a guide for setting up reproducibility tests.

Ready? Start with the Quick Start. For a few examples of what you can already do with ChemTorch read the white paper on ChemRxiv.