ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Scott McKay e1a9f2ed6d
Fix insufficient space error in Android CI (#17423)
### Description
<!-- Describe your changes. -->
Remove onnxruntime_test_all from emulator once tests have finished as
it's 1.2GB and takes up too much space given the 2GB maximum partition
size for the emulator.

Side issue is the java build isn't able to strip the binaries in the
java apk which causes that to be 800MB (exceeding the 2GB max). That may
require an Android/Gradle fix as I don't think we can hardcode an NDK
version into our build files.
https://issuetracker.google.com/issues/237187538?pli=1


### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Fix Android CI build failures for
2023-09-06 10:12:05 +10:00
.config
.devcontainer
.gdn Update win-ci-pipeline.yml: enable xnnpack tests (#16244) 2023-06-14 19:12:42 -07:00
.github Add website publish placeholder (#17318) 2023-08-30 11:01:54 -07:00
.pipelines Bump DirectML version from 1.12.0 to 1.12.1 (#17225) 2023-08-20 09:55:38 -07:00
.vscode Broadcasting for SLN for CPU and CUDA (#16510) 2023-08-07 09:55:42 -07:00
cgmanifests Move composable_kernel to deps.txt (#17245) 2023-08-23 17:39:16 -07:00
cmake Fix git working dir for ORT_BUILD_INFO (fixes #17197) (#17198) 2023-09-05 09:20:49 -07:00
csharp Build nuget pkg for ROCm (#16791) 2023-08-28 13:35:08 +08:00
dockerfiles Enable model subgraph execution in OVEP and setting the OpenVINO dll's to the path from the OpenVINO pypi packge in OVEP and fix OVEP windows io buffer sample (#16147) 2023-06-16 19:47:09 -07:00
docs Sign CUDA Kernel (#17293) 2023-08-28 21:03:58 -07:00
include/onnxruntime/core Fix a memleak in RunAsync python (#17326) 2023-08-30 12:54:17 -07:00
java [java] Relaxing CoreML test (#16777) 2023-08-09 11:43:05 -07:00
js [js/webgpu] Fix bug in conv2dByMatMul path (#17369) 2023-09-02 00:16:28 -07:00
objectivec Objective-C Add Support to Create and Query String ORTValues (#16764) 2023-07-20 17:39:29 -07:00
onnxruntime Reduce GPU memory for Whisper models converted to ONNX (#17378) 2023-09-05 16:24:20 -07:00
orttraining Change RuntimeError to ImportError (#17380) 2023-09-01 09:56:40 +08:00
rust
samples
swift/OnnxRuntimeBindingsTests
tools Fix insufficient space error in Android CI (#17423) 2023-09-06 10:12:05 +10:00
winml Improve comments in winml/ (#17163) 2023-08-15 23:30:56 -04:00
.clang-format Prevent GSL_SUPPRESS arguments from being modified by clang-format (#17242) 2023-08-22 18:26:53 -07:00
.clang-tidy
.dockerignore
.gitattributes
.gitignore
.gitmodules [wasm] upgrade emsdk to 3.1.44 (#17069) 2023-08-10 16:08:36 -07:00
.lintrunner.toml Format c++ code under winml/ (#16660) 2023-07-25 21:56:50 -07:00
build.bat try to find patch.exe in git default installation folder (#17106) 2023-08-10 21:48:13 -07:00
build.sh Upgrade old Python version in packaging pipeline (#16667) 2023-07-17 08:24:47 -07:00
CITATION.cff
CODEOWNERS
CONTRIBUTING.md
lgtm.yml
LICENSE
NuGet.config
ort.wprp
ORT_icon_for_light_bg.png
Package.swift Objective-C Add Support to Create and Query String ORTValues (#16764) 2023-07-20 17:39:29 -07:00
packages.config Bump DirectML version from 1.12.0 to 1.12.1 (#17225) 2023-08-20 09:55:38 -07:00
pyproject.toml Updating QDQ to support Float8E4M3FN (#16550) 2023-08-08 12:18:48 +02:00
README.md
requirements-dev.txt
requirements-doc.txt
requirements-lintrunner.txt Bump clang-format to 16.0.6 in CI (#17099) 2023-08-10 13:53:04 -07:00
requirements-training.txt
requirements.txt.in
SECURITY.md
setup.py Upgrade Centos7 to Alamlinux8 (#16907) 2023-08-29 21:05:36 -07:00
ThirdPartyNotices.txt Flash Attention v2 MHA (#17227) 2023-08-31 13:52:21 -07:00
VERSION_NUMBER

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

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System Inference Training
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Third-party Pipeline Status

System Inference Training
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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.