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torchdrug

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About torchdrug

T

torchdrug

Builds and troubleshoots TorchDrug 0.2.1 workflows for molecular graphs

torchdrug is an agent skill for building and troubleshooting TorchDrug 0.2.1 workflows on molecular graphs. TorchDrug is a modular PyTorch stack for graph learning in chemistry and biology. A workflow loads a dataset, chooses a representation model, wraps it in a task objective, and then trains and evaluates it with the Engine. The skill covers property prediction, self-supervised pretraining, molecule generation and retrosynthesis. The current official documentation and the latest published release are both 0.2.1, released in July 2023 and rechecked on 1 October 2026. The skill treats newer Python or PyTorch combinations as unverified rather than assuming they work. It begins with a version check, so you inspect the environment before any code is generated or debugged. Because the project has not released for a long time, the skill suggests testing your exact versions before relying on them. Use it for molecular property prediction or generation with graph neural networks in PyTorch. It is part of the k-dense-ai scientific agent skills repository on GitHub, which has about 49,600 stars. The listing shows it as free, and it has about 1,800 installs.

Price
Free
Made by
k-dense-ai
Category
AI Skills
Website
github.com/k-dense-ai/scientific-agent-skills/torchdrug