ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Find a file
Christian Larson ac6fe48375
Adjust max chunk size to fix error limit check from DX12 for large resources that are CPU accessible. (#22680)
Adjust max chunk size to fix error limit check from DX12 for large
resources that are CPU accessible.

### Description
Current agility SDK restricts CPU visible buffers to 0xFFFF0000 bytes or
slightly smaller than 4GiB. Verified restriction is still in latest
Agility SDK 1.614.1.


### Motivation and Context
Allocation of Resources 4GiB or larger fail in DX12 verification layer.

---------

Co-authored-by: Dwayne Robinson <dwayner@microsoft.com>
2024-11-03 18:08:12 -08:00
.config Add an 1ES PT baseline file (#22587) 2024-10-25 09:18:30 -07:00
.devcontainer
.gdn
.github [CI] Set up proper permissions for linting workflow (#22696) 2024-11-01 18:14:52 -07:00
.pipelines [DML EP] Update DML to 1.15.4 (#22635) 2024-10-29 17:13:57 -07:00
.vscode Stop VSCode appending file associations to settings.json (#21944) 2024-08-31 19:04:12 -07:00
cgmanifests Remove nsync (#20413) 2024-10-21 15:32:14 -07:00
cmake Add implementation of WebGPU EP (#22591) 2024-10-29 18:29:40 -07:00
csharp Rework the native library usage so that a pre-built ORT native package can be easily used (#22345) 2024-11-01 11:03:33 -07:00
dockerfiles [ROCm] Python 3.10 in ROCm CI, and ROCm 6.2.3 in MigraphX CI (#22527) 2024-10-25 11:47:16 -07:00
docs [Doc] Add I/O binding example using onnx data type in python API summary (#22695) 2024-11-02 12:51:37 -07:00
include/onnxruntime/core [CoreML] ML Program more ops (2/N) (#22480) 2024-11-01 08:37:56 +08:00
java Build CUDA and DML together (#22602) 2024-10-31 15:51:13 -07:00
js [js/webgpu] Optimize MatMul with M = 1 (#22577) 2024-11-01 08:04:42 -07:00
objectivec [CoreML ML Program] support acclerators selector (#22383) 2024-10-15 11:50:11 +08:00
onnxruntime Adjust max chunk size to fix error limit check from DX12 for large resources that are CPU accessible. (#22680) 2024-11-03 18:08:12 -08:00
orttraining enable serialize prepacked weights into data file (#22256) 2024-10-24 22:24:48 -07:00
rust Fix typos according to reviewdog report. (#21335) 2024-07-22 13:37:32 -07:00
samples
tools [CoreML] ML Program more ops (2/N) (#22480) 2024-11-01 08:37:56 +08:00
winml Fix warnings (#21809) 2024-08-21 14:23:37 -07:00
.clang-format
.clang-tidy
.dockerignore
.gitattributes Fix typos according to reviewdog report. (#21335) 2024-07-22 13:37:32 -07:00
.gitignore
.gitmodules Revert "Upgrade emsdk from 3.1.59 to 3.1.62" (#21817) 2024-08-22 11:21:00 -07:00
.lintrunner.toml [js] change default formatter for JavaScript/TypeScript from clang-format to Prettier (#21728) 2024-08-14 16:51:22 -07:00
build.bat
build.sh
build_arm64x.bat
CITATION.cff
CODEOWNERS
CONTRIBUTING.md
lgtm.yml
LICENSE
NuGet.config Update C# test projects (#21631) 2024-09-05 08:21:23 +10:00
ort.wprp
ORT_icon_for_light_bg.png
packages.config [DML EP] Update DML to 1.15.4 (#22635) 2024-10-29 17:13:57 -07:00
pyproject.toml Ignore ruff rule N813 (#21477) 2024-07-24 17:48:22 -07:00
README.md Update README.md with release roadmap info (#22486) 2024-10-18 11:00:43 -07:00
requirements-dev.txt
requirements-doc.txt
requirements-lintrunner.txt Update lintrunner requirements (#22185) 2024-09-23 18:27:16 -07:00
requirements-training.txt
requirements.txt Add compatibility for NumPy 2.0 (#21085) 2024-06-27 13:50:53 -07:00
SECURITY.md
setup.py Update CMake to 3.31.0rc1 (#22433) 2024-10-16 11:50:13 -07:00
ThirdPartyNotices.txt Remove nsync (#20413) 2024-10-21 15:32:14 -07:00
VERSION_NUMBER bumps up version in main from 1.20 -> 1.21 (#22482) 2024-10-17 12:32:35 -07:00

ONNX Runtime is a cross-platform inference and training machine-learning accelerator.

ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. Learn more →

ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Learn more →

Get Started & Resources

Builtin Pipeline Status

System Inference Training
Windows Build Status
Build Status
Build Status
Linux Build Status
Build Status
Build Status
Build Status
Build Status
Build Status
Build Status
Build Status
Mac Build Status
Android Build Status
iOS Build Status
Web Build Status
Other Build Status

This project is tested with BrowserStack.

Third-party Pipeline Status

System Inference Training
Linux Build Status

Releases

The current release and past releases can be found here: https://github.com/microsoft/onnxruntime/releases.

For details on the upcoming release, including release dates, announcements, features, and guidance on submitting feature requests, please visit the release roadmap: https://onnxruntime.ai/roadmap.

Data/Telemetry

Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the privacy statement for more details.

Contributions and Feedback

We welcome contributions! Please see the contribution guidelines.

For feature requests or bug reports, please file a GitHub Issue.

For general discussion or questions, please use GitHub Discussions.

Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

License

This project is licensed under the MIT License.