809c504d0a
* Initial summary dumper implementation * Handle Tensoriterator body + add parser script * Add support of XML reports merging + report OP names with versions * Remove debug device name change * Fix windows building issue * Add --disable_test_skips command line option * Gtest failure with logging * Change skipping logic and resolve linkage errors caused by extern * Get graph body from Loop * Fix disable_tests_skipping symbol redefinition * Fix inline for currentTestIsDisabled * Rollback get_body for Loop * Handle cases with skip in test SetUp * Report Loop and TI ops along with ops in subgraph body * Resolve some PR comments * Dummy commit to kick pre-commit validation Co-authored-by: Efode, Irina <irina.efode@intel.com> |
||
|---|---|---|
| .ci | ||
| .github | ||
| cmake | ||
| docs | ||
| inference-engine | ||
| licensing | ||
| model-optimizer | ||
| ngraph | ||
| openvino | ||
| scripts | ||
| tests | ||
| tools | ||
| .gitattributes | ||
| .gitignore | ||
| .gitmodules | ||
| build-instruction.md | ||
| CMakeLists.txt | ||
| CODEOWNERS | ||
| CONTRIBUTING_DOCS.md | ||
| CONTRIBUTING.md | ||
| get-started-linux.md | ||
| install_build_dependencies.sh | ||
| Jenkinsfile | ||
| LICENSE | ||
| README.md | ||
| SECURITY.md | ||
OpenVINO™ Toolkit - Deep Learning Deployment Toolkit repository
This toolkit allows developers to deploy pre-trained deep learning models through a high-level C++ Inference Engine API integrated with application logic.
This open source version includes two components: namely Model Optimizer and Inference Engine, as well as CPU, GPU and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. It supports pre-trained models from the Open Model Zoo, along with 100+ open source and public models in popular formats such as Caffe*, TensorFlow*, MXNet* and ONNX*.
Repository components:
License
Deep Learning Deployment Toolkit is licensed under Apache License Version 2.0. By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms.
Documentation
- OpenVINO™ Release Notes
- OpenVINO™ Inference Engine Build Instructions
- Get Started with Deep Learning Deployment Toolkit on Linux*
- Introduction to Deep Learning Deployment Toolkit
- Inference Engine Developer Guide
- Model Optimizer Developer Guide
- Get Started with DockerHub CI for OpenVINO™ toolkit
How to Contribute
See CONTRIBUTING for contribution to the code. See CONTRIBUTING_DOCS for contribution to the documentation. Thank you!
Support
Please report questions, issues and suggestions using:
- The
openvinotag on StackOverflow* - GitHub* Issues
- Forum
* Other names and brands may be claimed as the property of others.