* Update SelectDevice policy in auto plugin Signed-off-by: Zhengtian Xie <zhengtian.xie@intel.com> * Implement limit device list for AUTO plugin Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Add tests for AUTO limit device feature Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Add gpu tests for auto-plugin Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Fix CI cpuFuncTests issue due to BATCHED_BLOB Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Override LoadNetwork(modelPath, config) in AUTO plugin Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Update SelectDevice() logic for LoadNetwork(model, config) Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Update GetNetworkPrecision logic for auto-plugin Signed-off-by: Zhengtian Xie <zhengtian.xie@intel.com> * Address reviewers' comments Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Add tests for AUTO:GPU,CPU case Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Update logic in GetNetworkPrecision for auto-plugin Signed-off-by: Zhengtian Xie <zhengtian.xie@intel.com> * Address reviewer's comment: clean and simplify code Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Fix wrong usage of convolution weight index Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Address reviewer comment: fix get network precision logic Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Fix rebase issue Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> * Fix ie_core.cpp header change Signed-off-by: Shoujiang Ma <shoujiang.ma@intel.com> Co-authored-by: zhengtian.xie <zhengtian.xie@intel.com>
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
openvinotag on StackOverflow* - GitHub* Issues
- Forum
* Other names and brands may be claimed as the property of others.