ea52dd2642
* sequences to ti transformations, support for seq_lengths input, update reference implemetations, add new tests * fix python api, update sequences to ti transformation * transition from cnn to ngraph transformations for cpu, gpu, vpu plugins * fix convert_ti_to_sequence transformation * fix naming issue in unroll transformation * test pure TensorIterator in vpu plugin * fix sequences to ti transformation * Update sequences to TI transformation: fix reverse sequence support * update single layer tests, fix TI reference impl, fix Sequences to TI transformations * ngraph code style * fix build * fix ngraph python api * resolver review comments, refactoring * revert vpu changes * disable/fix tests * refactoring * Resolve review remarks * optimization of LSTMSeq -> LSTMSeq IE: remove unnecessary Transpose ops * Refactoring of transformation pipeline in cpu and gpu plugins, align GRU/RNN -> GRU/RNN IE with LSTM -> LSTM IE * update TensorIterator tests, refactoring * fix typo * Fix unit tests, delete unnecessary callbacks * Refactoring: delete commented code * Add FullyConnected to skipConstInfer list for legacy ConstFolding * disable legacy cnn unit tests * delete xfail * fix for backward compatibility with opset1::LSTMCell * delete xfail * fix build, remove Reshape layer from skipConstInfer list |
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| cmake | ||
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| inference-engine | ||
| licensing | ||
| model-optimizer | ||
| ngraph | ||
| openvino | ||
| scripts | ||
| tests | ||
| tools | ||
| .gitattributes | ||
| .gitignore | ||
| .gitmodules | ||
| CMakeLists.txt | ||
| CODEOWNERS | ||
| install_build_dependencies.sh | ||
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| LICENSE | ||
| README.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 several components: namely Model Optimizer, ngraph and Inference Engine, as well as CPU, GPU, MYRIAD, multi device 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.
Resources:
- Docs: https://docs.openvinotoolkit.org/
- Wiki: https://github.com/openvinotoolkit/openvino/wiki
- Issue tracking: https://github.com/openvinotoolkit/openvino/issues
- Additional OpenVINO modules: https://github.com/openvinotoolkit/openvino_contrib
- HomePage
- OpenVINO™ Release Notes
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.