dhi.io/pytorch
PyTorch
A python-based machine learning framework, providing tensors, dynamic neural networks and strong GPU acceleration.
pushed 2 days ago
linux/amd64, linux/arm64
6.09 GB
for linux/amd64
255
for linux/amd64
Active support
python, pip, torch, torchvision, torchaudio, torchelastic, triton
Build Level 3
Tamper-evident proof of how and from what sources this image was built. Build Level 3 is the highest the SLSA build track defines.
CycloneDX SBOM + SPDX SBOM
A software bill of materials in both CycloneDX and SPDX formats so it drops straight into your existing tooling. Audit exactly what you're shipping.
A Vulnerability Exploitability exchange document, Docker's assessment of which CVEs actually affect this image and which don't apply, so you can focus on real risk instead of chasing false positives.
Available
A link to everything used to build the image, package source code, Git repos, and build files, so you can audit or reproduce the build and stay compliant with open source licenses.
Every known vulnerability in this image, shown in full rather than hidden. The VEX data flags which ones actually apply, so you can tell real exposure from noise before you ship.
Exactly what changed in this build, down to the package bumps and fixes behind the version you're pulling.
Verifies no keys, tokens, or credentials were accidentally baked into the image.
The image layers were scanned for known malware signatures before publishing.
About PyTorch
PyTorch is an open-source machine learning framework that provides a flexible and powerful platform for building deep learning models. It offers dynamic computational graphs, automatic differentiation, and native GPU acceleration through CUDA. PyTorch is widely used in research and production for tasks ranging from computer vision to natural language processing and reinforcement learning.
Key features include:
- Dynamic computational graphs for flexible model building
- Strong GPU acceleration with CUDA support
- Extensive ecosystem including TorchVision for computer vision and TorchAudio for audio processing
- TorchScript for production deployment
- Native support for distributed training
For more information, visit https://pytorch.org/docs/.
About Docker Hardened Images
Docker Hardened Images are built to meet the highest security and compliance standards. They provide a trusted foundation for containerized workloads by incorporating security best practices from the start.
Why use Docker Hardened Images?
These images are published with zero-known CVEs, include signed provenance, and come with a complete Software Bill of Materials (SBOM) and VEX metadata. They're designed to secure your software supply chain while fitting seamlessly into existing Docker workflows.
Trademarks
PyTorch, the PyTorch logo and any related marks are trademarks of The Linux Foundation.
NVIDIA®, the NVIDIA® logo, and CUDA® are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated.
This listing is prepared by Docker. All third-party product names, logos, and trademarks are the property of their respective owners and are used solely for identification. Docker claims no interest in those marks, and no affiliation, sponsorship, or endorsement is implied.