* [FrontEnd]enable pdpd ops conversion part3 * Add adaptive pool2d op conversion (#1) * param support tensor (#2) * add missing sync_batch_norm * Update pow.cpp * deal empty axis (#5) * deal empty axis * apply review comments * fix code style * fix code style * change shape to i32 * fix code in shape * fix code style * fix paddle code style * remove redandent ops * fix maxAdativePool * fix expand_v2 * remove redandent code Co-authored-by: Mang Guo <mang.guo@intel.com> Co-authored-by: Luo Cheng <cheng.luo@intel.com> |
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inference-engine | ||
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openvino | ||
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SECURITY.md |
OpenVINO™ Toolkit
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
- Storage: https://storage.openvinotoolkit.org/
- Additional OpenVINO™ modules: https://github.com/openvinotoolkit/openvino_contrib
- Intel® Distribution of OpenVINO™ toolkit Product Page
- Intel® Distribution of OpenVINO™ toolkit Release Notes
Support
Please report questions, issues and suggestions using:
- The
openvino
tag on StackOverflow* - GitHub* Issues
- Forum
* Other names and brands may be claimed as the property of others.