Linux / arm64
Linux / amd64
This container image includes the complete source of the NVIDIA version of PyG in /opt/pyg/pytorch_geometric. It is prebuilt and installed as a system Python module. The /workspace/examples folder is copied from /opt/pyg/pytorch_geometric/examples for users starting to run PyG. For an introductory example about training a GCN, try python /workspace/examples/gcn.py
See /workspace/README.md for details
The container also uses torch-geometric 2.4.0 and pyg-lib 0.2.0. This container also contains the GNN Platform (/opt/pyg/gnn-platform), an NVIDIA project that provides a low-code API for rapid GNN experimentation and training/deploying end-to-end GNN pipelines. Examples can be found at /workspace/gnn-platform-examples. For more details about the GNN Platform, see /opt/pyg/gnn-platform/README.md.
This container is built on NVIDIA PyTorch container. For the full list of contents see the PyG Container Release Notes.
Use the following commands to run the container, where <xx.xx> is the container version.
docker run --gpus all -it --rm nvcr.io/nvidia/pyg:xx.xx-py3
For example, 23.11 for November 2023 release:
docker run --gpus all -it --rm nvcr.io/nvidia/pyg:23.11-py3
To review known CVEs on this image, refer to the Security Scanning tab on this page.
By pulling and using the container, you accept the terms and conditions of this End User License Agreement.