ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Scott McKay 565da71275
Make 'env' argument to Session const (#13362)
### Description
<!-- Describe your changes. -->
The Env argument does not need to be mutable to call the underlying C
API. Update the Ort::Session ctor to have a const Env.

All other changes are from clang-format running. 

### 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. -->
Cleanup
2022-10-19 14:23:24 +10:00
.config Update TSA path to new ADO project (#12902) 2022-10-03 22:54:42 -07:00
.devcontainer
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.github Update Win_GPU_CI trigger (#13290) 2022-10-12 15:22:42 +08:00
.pipelines Publish WinML Nuget package to ORT-Nightly ADO feed (#12904) 2022-09-15 12:10:27 -07:00
.vscode
cgmanifests Upgrade protobuf version (#13100) 2022-09-26 21:30:28 -07:00
cmake MIGraphX Execution Provider: Stream Synchronization (#12899) 2022-10-14 10:23:51 -07:00
csharp uset SearchOption for dotframework (#13321) 2022-10-14 10:22:05 -07:00
dockerfiles Openvino GPU Unit/Python Tests fix failure (#13122) 2022-09-28 16:00:06 -07:00
docs skip windows GPU check if changes only in doc (#13248) 2022-10-11 13:51:44 +08:00
include/onnxruntime/core Make 'env' argument to Session const (#13362) 2022-10-19 14:23:24 +10:00
java [Java] Fix OnnxSequence semantics (#13012) 2022-09-28 15:53:30 -07:00
js [React Native CI] Record more info to debug E2E test (#13329) 2022-10-18 17:21:28 -07:00
objectivec Deprecate CustomApi and refactor public API for better safety and consistency (#13215) 2022-10-06 14:57:37 -07:00
onnxruntime Add Symbolic Shape and Type Infer for aten::group_norm (#13348) 2022-10-19 10:37:33 +08:00
orttraining update the nightly build to use the latest ptca image. (#13309) 2022-10-17 14:12:03 -07:00
package/rpm
samples
tools [React Native CI] Record more info to debug E2E test (#13329) 2022-10-18 17:21:28 -07:00
winml Fix SDL Unmatched Annotation Errors (#13162) 2022-09-30 15:36:30 -07:00
.clang-format
.clang-tidy Create clang-tidy CI (#12653) 2022-09-30 08:05:38 -07:00
.dockerignore
.flake8 Remove miscellaneous nuphar configs (#13070) 2022-09-26 13:41:28 -07:00
.gitattributes
.gitignore Ignore settings.json in git (#12988) 2022-09-19 12:05:43 -07:00
.gitmodules
build.amd64.1411.bat
build.bat
build.sh
CITATION.cff
CODEOWNERS Add cgmanifest file in codeowner list (#13042) 2022-09-22 18:58:01 -07:00
CONTRIBUTING.md
lgtm.yml
LICENSE
NuGet.config
ort.wprp
ORT_icon_for_light_bg.png
packages.config Update DML 1.9.0 to 1.9.1 (#12966) 2022-09-15 10:54:22 -07:00
pyproject.toml
README.md Remove miscellaneous nuphar configs (#13070) 2022-09-26 13:41:28 -07:00
requirements-dev.txt
requirements-doc.txt
requirements-training.txt
requirements.txt.in
SECURITY.md
setup.py Add Utils for federated learning scenarios (#13014) 2022-10-17 12:39:43 -07:00
ThirdPartyNotices.txt
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

General Information: onnxruntime.ai

Usage documention and tutorials: onnxruntime.ai/docs

Companion sample repositories:

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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.